ludwig
Low-code framework for building custom LLMs, neural networks, and other AI models
View on Github
Activity
- Latest release
- 4d ago
- Total releases
- 79
- Cadence
- ~7 days
- Last 12 months
- 23
Reach
- Stars
- 11.8k
Details
- License
- Apache-2.0
- First release
- Feb 11, 2019
| Version | Released | |
|---|---|---|
0.17.10
patch
| ||
0.17.9
patch
| ||
0.17.8
patch
| ||
0.17.7
patch
| ||
0.17.6
patch
| ||
0.17.5
patch
| ||
0.17.3
patch
| ||
0.17.2
patch
| ||
0.17.1
minor
| ||
0.16.2
patch
| ||
0.16.1
patch
| ||
0.16.0
minor
| ||
0.15.1
patch
| ||
0.15.0
minor
| ||
0.14.1
patch
| ||
0.14.0
minor
| ||
0.13.0
minor
| ||
0.12.0
minor
| ||
0.11.4
patch
| ||
0.11.3
patch
| ||
0.11.2
patch
| ||
0.11.1
patch
| ||
0.11.0
minor
| ||
0.10.4
patch
2 CVEs
CVE-2026-31237
PYSEC-2026-404
GHSA-wcr3-gm9f-f87q
Jun 29, 2026
Ludwig framework is vulnerable to insecure deserialization through its predict() method.
9.8
/ 10
Critical
Network
Low
None
None
Unchanged
High
High
High
The Ludwig framework thru 0.10.4 is vulnerable to insecure deserialization (CWE-502) through its predict() method. When a user provides a dataset file path to the predict() method, the framework automatically determines the file format. If the file is a pickle (.pkl) file, it is loaded using pandas.read_pickle() without any validation or security restrictions. This allows the deserialization of arbitrary Python objects via the unsafe pickle module. A remote attacker can exploit this by providing a maliciously crafted pickle file, leading to arbitrary code execution on the system running the Ludwig prediction. Affected versions
0.1.0
0.1.1
0.1.2
0.10.0
0.10.1
0.10.2
0.10.3
0.10.4
0.2
0.2.1
0.2.2
0.2.2.2
+ 44 more Show less
0.2.2.3
0.2.2.4
0.2.2.5
0.2.2.6
0.2.2.7
0.2.2.8
0.3
0.3.1
0.3.2
0.3.3
0.4
0.4.1
0.4rc1
0.5
0.5.1
0.5.2
0.5.3
0.5.4
0.5.5
0.5rc1
0.5rc2
0.6
0.6.1
0.6.2
0.6.3
0.6.4
0.7
0.7.1
0.7.2
0.7.3
0.7.4
0.7.5
0.8
0.8.1
0.8.1.post1
0.8.2
0.8.3
0.8.4
0.8.5
0.8.6
0.9
0.9.1
0.9.2
0.9.3
References Updated Jul 01, 2026 · Source: OSV.dev
CVE-2026-31238
PYSEC-2026-405
GHSA-xp5q-5q7g-q26r
Jun 29, 2026
Ludwig framework is vulnerable to insecure deserialization in its model serving component
9.8
/ 10
Critical
Network
Low
None
None
Unchanged
High
High
High
The Ludwig framework thru 0.10.4 is vulnerable to insecure deserialization (CWE-502) in its model serving component. When starting a model server with the ludwig serve command, the framework loads model weight files using torch.load() without enabling the security-restrictive weights_only=True parameter. This default behavior allows the deserialization of arbitrary Python objects via the pickle module. An attacker can exploit this by providing a maliciously crafted PyTorch model file, leading to arbitrary code execution on the system hosting the Ludwig model server. Affected versions
0.1.0
0.1.1
0.1.2
0.10.0
0.10.1
0.10.2
0.10.3
0.10.4
0.2
0.2.1
0.2.2
0.2.2.2
+ 44 more Show less
0.2.2.3
0.2.2.4
0.2.2.5
0.2.2.6
0.2.2.7
0.2.2.8
0.3
0.3.1
0.3.2
0.3.3
0.4
0.4.1
0.4rc1
0.5
0.5.1
0.5.2
0.5.3
0.5.4
0.5.5
0.5rc1
0.5rc2
0.6
0.6.1
0.6.2
0.6.3
0.6.4
0.7
0.7.1
0.7.2
0.7.3
0.7.4
0.7.5
0.8
0.8.1
0.8.1.post1
0.8.2
0.8.3
0.8.4
0.8.5
0.8.6
0.9
0.9.1
0.9.2
0.9.3
References Updated Jul 01, 2026 · Source: OSV.dev | ||
0.10.3
patch
2 CVEs
CVE-2026-31237
PYSEC-2026-404
GHSA-wcr3-gm9f-f87q
Jun 29, 2026
Ludwig framework is vulnerable to insecure deserialization through its predict() method.
9.8
/ 10
Critical
Network
Low
None
None
Unchanged
High
High
High
The Ludwig framework thru 0.10.4 is vulnerable to insecure deserialization (CWE-502) through its predict() method. When a user provides a dataset file path to the predict() method, the framework automatically determines the file format. If the file is a pickle (.pkl) file, it is loaded using pandas.read_pickle() without any validation or security restrictions. This allows the deserialization of arbitrary Python objects via the unsafe pickle module. A remote attacker can exploit this by providing a maliciously crafted pickle file, leading to arbitrary code execution on the system running the Ludwig prediction. Affected versions
0.1.0
0.1.1
0.1.2
0.10.0
0.10.1
0.10.2
0.10.3
0.10.4
0.2
0.2.1
0.2.2
0.2.2.2
+ 44 more Show less
0.2.2.3
0.2.2.4
0.2.2.5
0.2.2.6
0.2.2.7
0.2.2.8
0.3
0.3.1
0.3.2
0.3.3
0.4
0.4.1
0.4rc1
0.5
0.5.1
0.5.2
0.5.3
0.5.4
0.5.5
0.5rc1
0.5rc2
0.6
0.6.1
0.6.2
0.6.3
0.6.4
0.7
0.7.1
0.7.2
0.7.3
0.7.4
0.7.5
0.8
0.8.1
0.8.1.post1
0.8.2
0.8.3
0.8.4
0.8.5
0.8.6
0.9
0.9.1
0.9.2
0.9.3
References Updated Jul 01, 2026 · Source: OSV.dev
CVE-2026-31238
PYSEC-2026-405
GHSA-xp5q-5q7g-q26r
Jun 29, 2026
Ludwig framework is vulnerable to insecure deserialization in its model serving component
9.8
/ 10
Critical
Network
Low
None
None
Unchanged
High
High
High
The Ludwig framework thru 0.10.4 is vulnerable to insecure deserialization (CWE-502) in its model serving component. When starting a model server with the ludwig serve command, the framework loads model weight files using torch.load() without enabling the security-restrictive weights_only=True parameter. This default behavior allows the deserialization of arbitrary Python objects via the pickle module. An attacker can exploit this by providing a maliciously crafted PyTorch model file, leading to arbitrary code execution on the system hosting the Ludwig model server. Affected versions
0.1.0
0.1.1
0.1.2
0.10.0
0.10.1
0.10.2
0.10.3
0.10.4
0.2
0.2.1
0.2.2
0.2.2.2
+ 44 more Show less
0.2.2.3
0.2.2.4
0.2.2.5
0.2.2.6
0.2.2.7
0.2.2.8
0.3
0.3.1
0.3.2
0.3.3
0.4
0.4.1
0.4rc1
0.5
0.5.1
0.5.2
0.5.3
0.5.4
0.5.5
0.5rc1
0.5rc2
0.6
0.6.1
0.6.2
0.6.3
0.6.4
0.7
0.7.1
0.7.2
0.7.3
0.7.4
0.7.5
0.8
0.8.1
0.8.1.post1
0.8.2
0.8.3
0.8.4
0.8.5
0.8.6
0.9
0.9.1
0.9.2
0.9.3
References Updated Jul 01, 2026 · Source: OSV.dev | ||
0.10.2
patch
2 CVEs
CVE-2026-31237
PYSEC-2026-404
GHSA-wcr3-gm9f-f87q
Jun 29, 2026
Ludwig framework is vulnerable to insecure deserialization through its predict() method.
9.8
/ 10
Critical
Network
Low
None
None
Unchanged
High
High
High
The Ludwig framework thru 0.10.4 is vulnerable to insecure deserialization (CWE-502) through its predict() method. When a user provides a dataset file path to the predict() method, the framework automatically determines the file format. If the file is a pickle (.pkl) file, it is loaded using pandas.read_pickle() without any validation or security restrictions. This allows the deserialization of arbitrary Python objects via the unsafe pickle module. A remote attacker can exploit this by providing a maliciously crafted pickle file, leading to arbitrary code execution on the system running the Ludwig prediction. Affected versions
0.1.0
0.1.1
0.1.2
0.10.0
0.10.1
0.10.2
0.10.3
0.10.4
0.2
0.2.1
0.2.2
0.2.2.2
+ 44 more Show less
0.2.2.3
0.2.2.4
0.2.2.5
0.2.2.6
0.2.2.7
0.2.2.8
0.3
0.3.1
0.3.2
0.3.3
0.4
0.4.1
0.4rc1
0.5
0.5.1
0.5.2
0.5.3
0.5.4
0.5.5
0.5rc1
0.5rc2
0.6
0.6.1
0.6.2
0.6.3
0.6.4
0.7
0.7.1
0.7.2
0.7.3
0.7.4
0.7.5
0.8
0.8.1
0.8.1.post1
0.8.2
0.8.3
0.8.4
0.8.5
0.8.6
0.9
0.9.1
0.9.2
0.9.3
References Updated Jul 01, 2026 · Source: OSV.dev
CVE-2026-31238
PYSEC-2026-405
GHSA-xp5q-5q7g-q26r
Jun 29, 2026
Ludwig framework is vulnerable to insecure deserialization in its model serving component
9.8
/ 10
Critical
Network
Low
None
None
Unchanged
High
High
High
The Ludwig framework thru 0.10.4 is vulnerable to insecure deserialization (CWE-502) in its model serving component. When starting a model server with the ludwig serve command, the framework loads model weight files using torch.load() without enabling the security-restrictive weights_only=True parameter. This default behavior allows the deserialization of arbitrary Python objects via the pickle module. An attacker can exploit this by providing a maliciously crafted PyTorch model file, leading to arbitrary code execution on the system hosting the Ludwig model server. Affected versions
0.1.0
0.1.1
0.1.2
0.10.0
0.10.1
0.10.2
0.10.3
0.10.4
0.2
0.2.1
0.2.2
0.2.2.2
+ 44 more Show less
0.2.2.3
0.2.2.4
0.2.2.5
0.2.2.6
0.2.2.7
0.2.2.8
0.3
0.3.1
0.3.2
0.3.3
0.4
0.4.1
0.4rc1
0.5
0.5.1
0.5.2
0.5.3
0.5.4
0.5.5
0.5rc1
0.5rc2
0.6
0.6.1
0.6.2
0.6.3
0.6.4
0.7
0.7.1
0.7.2
0.7.3
0.7.4
0.7.5
0.8
0.8.1
0.8.1.post1
0.8.2
0.8.3
0.8.4
0.8.5
0.8.6
0.9
0.9.1
0.9.2
0.9.3
References Updated Jul 01, 2026 · Source: OSV.dev | ||
0.10.1
patch
2 CVEs
CVE-2026-31237
PYSEC-2026-404
GHSA-wcr3-gm9f-f87q
Jun 29, 2026
Ludwig framework is vulnerable to insecure deserialization through its predict() method.
9.8
/ 10
Critical
Network
Low
None
None
Unchanged
High
High
High
The Ludwig framework thru 0.10.4 is vulnerable to insecure deserialization (CWE-502) through its predict() method. When a user provides a dataset file path to the predict() method, the framework automatically determines the file format. If the file is a pickle (.pkl) file, it is loaded using pandas.read_pickle() without any validation or security restrictions. This allows the deserialization of arbitrary Python objects via the unsafe pickle module. A remote attacker can exploit this by providing a maliciously crafted pickle file, leading to arbitrary code execution on the system running the Ludwig prediction. Affected versions
0.1.0
0.1.1
0.1.2
0.10.0
0.10.1
0.10.2
0.10.3
0.10.4
0.2
0.2.1
0.2.2
0.2.2.2
+ 44 more Show less
0.2.2.3
0.2.2.4
0.2.2.5
0.2.2.6
0.2.2.7
0.2.2.8
0.3
0.3.1
0.3.2
0.3.3
0.4
0.4.1
0.4rc1
0.5
0.5.1
0.5.2
0.5.3
0.5.4
0.5.5
0.5rc1
0.5rc2
0.6
0.6.1
0.6.2
0.6.3
0.6.4
0.7
0.7.1
0.7.2
0.7.3
0.7.4
0.7.5
0.8
0.8.1
0.8.1.post1
0.8.2
0.8.3
0.8.4
0.8.5
0.8.6
0.9
0.9.1
0.9.2
0.9.3
References Updated Jul 01, 2026 · Source: OSV.dev
CVE-2026-31238
PYSEC-2026-405
GHSA-xp5q-5q7g-q26r
Jun 29, 2026
Ludwig framework is vulnerable to insecure deserialization in its model serving component
9.8
/ 10
Critical
Network
Low
None
None
Unchanged
High
High
High
The Ludwig framework thru 0.10.4 is vulnerable to insecure deserialization (CWE-502) in its model serving component. When starting a model server with the ludwig serve command, the framework loads model weight files using torch.load() without enabling the security-restrictive weights_only=True parameter. This default behavior allows the deserialization of arbitrary Python objects via the pickle module. An attacker can exploit this by providing a maliciously crafted PyTorch model file, leading to arbitrary code execution on the system hosting the Ludwig model server. Affected versions
0.1.0
0.1.1
0.1.2
0.10.0
0.10.1
0.10.2
0.10.3
0.10.4
0.2
0.2.1
0.2.2
0.2.2.2
+ 44 more Show less
0.2.2.3
0.2.2.4
0.2.2.5
0.2.2.6
0.2.2.7
0.2.2.8
0.3
0.3.1
0.3.2
0.3.3
0.4
0.4.1
0.4rc1
0.5
0.5.1
0.5.2
0.5.3
0.5.4
0.5.5
0.5rc1
0.5rc2
0.6
0.6.1
0.6.2
0.6.3
0.6.4
0.7
0.7.1
0.7.2
0.7.3
0.7.4
0.7.5
0.8
0.8.1
0.8.1.post1
0.8.2
0.8.3
0.8.4
0.8.5
0.8.6
0.9
0.9.1
0.9.2
0.9.3
References Updated Jul 01, 2026 · Source: OSV.dev | ||
0.10.0
minor
2 CVEs
CVE-2026-31237
PYSEC-2026-404
GHSA-wcr3-gm9f-f87q
Jun 29, 2026
Ludwig framework is vulnerable to insecure deserialization through its predict() method.
9.8
/ 10
Critical
Network
Low
None
None
Unchanged
High
High
High
The Ludwig framework thru 0.10.4 is vulnerable to insecure deserialization (CWE-502) through its predict() method. When a user provides a dataset file path to the predict() method, the framework automatically determines the file format. If the file is a pickle (.pkl) file, it is loaded using pandas.read_pickle() without any validation or security restrictions. This allows the deserialization of arbitrary Python objects via the unsafe pickle module. A remote attacker can exploit this by providing a maliciously crafted pickle file, leading to arbitrary code execution on the system running the Ludwig prediction. Affected versions
0.1.0
0.1.1
0.1.2
0.10.0
0.10.1
0.10.2
0.10.3
0.10.4
0.2
0.2.1
0.2.2
0.2.2.2
+ 44 more Show less
0.2.2.3
0.2.2.4
0.2.2.5
0.2.2.6
0.2.2.7
0.2.2.8
0.3
0.3.1
0.3.2
0.3.3
0.4
0.4.1
0.4rc1
0.5
0.5.1
0.5.2
0.5.3
0.5.4
0.5.5
0.5rc1
0.5rc2
0.6
0.6.1
0.6.2
0.6.3
0.6.4
0.7
0.7.1
0.7.2
0.7.3
0.7.4
0.7.5
0.8
0.8.1
0.8.1.post1
0.8.2
0.8.3
0.8.4
0.8.5
0.8.6
0.9
0.9.1
0.9.2
0.9.3
References Updated Jul 01, 2026 · Source: OSV.dev
CVE-2026-31238
PYSEC-2026-405
GHSA-xp5q-5q7g-q26r
Jun 29, 2026
Ludwig framework is vulnerable to insecure deserialization in its model serving component
9.8
/ 10
Critical
Network
Low
None
None
Unchanged
High
High
High
The Ludwig framework thru 0.10.4 is vulnerable to insecure deserialization (CWE-502) in its model serving component. When starting a model server with the ludwig serve command, the framework loads model weight files using torch.load() without enabling the security-restrictive weights_only=True parameter. This default behavior allows the deserialization of arbitrary Python objects via the pickle module. An attacker can exploit this by providing a maliciously crafted PyTorch model file, leading to arbitrary code execution on the system hosting the Ludwig model server. Affected versions
0.1.0
0.1.1
0.1.2
0.10.0
0.10.1
0.10.2
0.10.3
0.10.4
0.2
0.2.1
0.2.2
0.2.2.2
+ 44 more Show less
0.2.2.3
0.2.2.4
0.2.2.5
0.2.2.6
0.2.2.7
0.2.2.8
0.3
0.3.1
0.3.2
0.3.3
0.4
0.4.1
0.4rc1
0.5
0.5.1
0.5.2
0.5.3
0.5.4
0.5.5
0.5rc1
0.5rc2
0.6
0.6.1
0.6.2
0.6.3
0.6.4
0.7
0.7.1
0.7.2
0.7.3
0.7.4
0.7.5
0.8
0.8.1
0.8.1.post1
0.8.2
0.8.3
0.8.4
0.8.5
0.8.6
0.9
0.9.1
0.9.2
0.9.3
References Updated Jul 01, 2026 · Source: OSV.dev | ||
0.9.3
patch
2 CVEs
CVE-2026-31237
PYSEC-2026-404
GHSA-wcr3-gm9f-f87q
Jun 29, 2026
Ludwig framework is vulnerable to insecure deserialization through its predict() method.
9.8
/ 10
Critical
Network
Low
None
None
Unchanged
High
High
High
The Ludwig framework thru 0.10.4 is vulnerable to insecure deserialization (CWE-502) through its predict() method. When a user provides a dataset file path to the predict() method, the framework automatically determines the file format. If the file is a pickle (.pkl) file, it is loaded using pandas.read_pickle() without any validation or security restrictions. This allows the deserialization of arbitrary Python objects via the unsafe pickle module. A remote attacker can exploit this by providing a maliciously crafted pickle file, leading to arbitrary code execution on the system running the Ludwig prediction. Affected versions
0.1.0
0.1.1
0.1.2
0.10.0
0.10.1
0.10.2
0.10.3
0.10.4
0.2
0.2.1
0.2.2
0.2.2.2
+ 44 more Show less
0.2.2.3
0.2.2.4
0.2.2.5
0.2.2.6
0.2.2.7
0.2.2.8
0.3
0.3.1
0.3.2
0.3.3
0.4
0.4.1
0.4rc1
0.5
0.5.1
0.5.2
0.5.3
0.5.4
0.5.5
0.5rc1
0.5rc2
0.6
0.6.1
0.6.2
0.6.3
0.6.4
0.7
0.7.1
0.7.2
0.7.3
0.7.4
0.7.5
0.8
0.8.1
0.8.1.post1
0.8.2
0.8.3
0.8.4
0.8.5
0.8.6
0.9
0.9.1
0.9.2
0.9.3
References Updated Jul 01, 2026 · Source: OSV.dev
CVE-2026-31238
PYSEC-2026-405
GHSA-xp5q-5q7g-q26r
Jun 29, 2026
Ludwig framework is vulnerable to insecure deserialization in its model serving component
9.8
/ 10
Critical
Network
Low
None
None
Unchanged
High
High
High
The Ludwig framework thru 0.10.4 is vulnerable to insecure deserialization (CWE-502) in its model serving component. When starting a model server with the ludwig serve command, the framework loads model weight files using torch.load() without enabling the security-restrictive weights_only=True parameter. This default behavior allows the deserialization of arbitrary Python objects via the pickle module. An attacker can exploit this by providing a maliciously crafted PyTorch model file, leading to arbitrary code execution on the system hosting the Ludwig model server. Affected versions
0.1.0
0.1.1
0.1.2
0.10.0
0.10.1
0.10.2
0.10.3
0.10.4
0.2
0.2.1
0.2.2
0.2.2.2
+ 44 more Show less
0.2.2.3
0.2.2.4
0.2.2.5
0.2.2.6
0.2.2.7
0.2.2.8
0.3
0.3.1
0.3.2
0.3.3
0.4
0.4.1
0.4rc1
0.5
0.5.1
0.5.2
0.5.3
0.5.4
0.5.5
0.5rc1
0.5rc2
0.6
0.6.1
0.6.2
0.6.3
0.6.4
0.7
0.7.1
0.7.2
0.7.3
0.7.4
0.7.5
0.8
0.8.1
0.8.1.post1
0.8.2
0.8.3
0.8.4
0.8.5
0.8.6
0.9
0.9.1
0.9.2
0.9.3
References Updated Jul 01, 2026 · Source: OSV.dev | ||
0.9.2
patch
2 CVEs
CVE-2026-31237
PYSEC-2026-404
GHSA-wcr3-gm9f-f87q
Jun 29, 2026
Ludwig framework is vulnerable to insecure deserialization through its predict() method.
9.8
/ 10
Critical
Network
Low
None
None
Unchanged
High
High
High
The Ludwig framework thru 0.10.4 is vulnerable to insecure deserialization (CWE-502) through its predict() method. When a user provides a dataset file path to the predict() method, the framework automatically determines the file format. If the file is a pickle (.pkl) file, it is loaded using pandas.read_pickle() without any validation or security restrictions. This allows the deserialization of arbitrary Python objects via the unsafe pickle module. A remote attacker can exploit this by providing a maliciously crafted pickle file, leading to arbitrary code execution on the system running the Ludwig prediction. Affected versions
0.1.0
0.1.1
0.1.2
0.10.0
0.10.1
0.10.2
0.10.3
0.10.4
0.2
0.2.1
0.2.2
0.2.2.2
+ 44 more Show less
0.2.2.3
0.2.2.4
0.2.2.5
0.2.2.6
0.2.2.7
0.2.2.8
0.3
0.3.1
0.3.2
0.3.3
0.4
0.4.1
0.4rc1
0.5
0.5.1
0.5.2
0.5.3
0.5.4
0.5.5
0.5rc1
0.5rc2
0.6
0.6.1
0.6.2
0.6.3
0.6.4
0.7
0.7.1
0.7.2
0.7.3
0.7.4
0.7.5
0.8
0.8.1
0.8.1.post1
0.8.2
0.8.3
0.8.4
0.8.5
0.8.6
0.9
0.9.1
0.9.2
0.9.3
References Updated Jul 01, 2026 · Source: OSV.dev
CVE-2026-31238
PYSEC-2026-405
GHSA-xp5q-5q7g-q26r
Jun 29, 2026
Ludwig framework is vulnerable to insecure deserialization in its model serving component
9.8
/ 10
Critical
Network
Low
None
None
Unchanged
High
High
High
The Ludwig framework thru 0.10.4 is vulnerable to insecure deserialization (CWE-502) in its model serving component. When starting a model server with the ludwig serve command, the framework loads model weight files using torch.load() without enabling the security-restrictive weights_only=True parameter. This default behavior allows the deserialization of arbitrary Python objects via the pickle module. An attacker can exploit this by providing a maliciously crafted PyTorch model file, leading to arbitrary code execution on the system hosting the Ludwig model server. Affected versions
0.1.0
0.1.1
0.1.2
0.10.0
0.10.1
0.10.2
0.10.3
0.10.4
0.2
0.2.1
0.2.2
0.2.2.2
+ 44 more Show less
0.2.2.3
0.2.2.4
0.2.2.5
0.2.2.6
0.2.2.7
0.2.2.8
0.3
0.3.1
0.3.2
0.3.3
0.4
0.4.1
0.4rc1
0.5
0.5.1
0.5.2
0.5.3
0.5.4
0.5.5
0.5rc1
0.5rc2
0.6
0.6.1
0.6.2
0.6.3
0.6.4
0.7
0.7.1
0.7.2
0.7.3
0.7.4
0.7.5
0.8
0.8.1
0.8.1.post1
0.8.2
0.8.3
0.8.4
0.8.5
0.8.6
0.9
0.9.1
0.9.2
0.9.3
References Updated Jul 01, 2026 · Source: OSV.dev | ||
0.9.1
patch
2 CVEs
CVE-2026-31237
PYSEC-2026-404
GHSA-wcr3-gm9f-f87q
Jun 29, 2026
Ludwig framework is vulnerable to insecure deserialization through its predict() method.
9.8
/ 10
Critical
Network
Low
None
None
Unchanged
High
High
High
The Ludwig framework thru 0.10.4 is vulnerable to insecure deserialization (CWE-502) through its predict() method. When a user provides a dataset file path to the predict() method, the framework automatically determines the file format. If the file is a pickle (.pkl) file, it is loaded using pandas.read_pickle() without any validation or security restrictions. This allows the deserialization of arbitrary Python objects via the unsafe pickle module. A remote attacker can exploit this by providing a maliciously crafted pickle file, leading to arbitrary code execution on the system running the Ludwig prediction. Affected versions
0.1.0
0.1.1
0.1.2
0.10.0
0.10.1
0.10.2
0.10.3
0.10.4
0.2
0.2.1
0.2.2
0.2.2.2
+ 44 more Show less
0.2.2.3
0.2.2.4
0.2.2.5
0.2.2.6
0.2.2.7
0.2.2.8
0.3
0.3.1
0.3.2
0.3.3
0.4
0.4.1
0.4rc1
0.5
0.5.1
0.5.2
0.5.3
0.5.4
0.5.5
0.5rc1
0.5rc2
0.6
0.6.1
0.6.2
0.6.3
0.6.4
0.7
0.7.1
0.7.2
0.7.3
0.7.4
0.7.5
0.8
0.8.1
0.8.1.post1
0.8.2
0.8.3
0.8.4
0.8.5
0.8.6
0.9
0.9.1
0.9.2
0.9.3
References Updated Jul 01, 2026 · Source: OSV.dev
CVE-2026-31238
PYSEC-2026-405
GHSA-xp5q-5q7g-q26r
Jun 29, 2026
Ludwig framework is vulnerable to insecure deserialization in its model serving component
9.8
/ 10
Critical
Network
Low
None
None
Unchanged
High
High
High
The Ludwig framework thru 0.10.4 is vulnerable to insecure deserialization (CWE-502) in its model serving component. When starting a model server with the ludwig serve command, the framework loads model weight files using torch.load() without enabling the security-restrictive weights_only=True parameter. This default behavior allows the deserialization of arbitrary Python objects via the pickle module. An attacker can exploit this by providing a maliciously crafted PyTorch model file, leading to arbitrary code execution on the system hosting the Ludwig model server. Affected versions
0.1.0
0.1.1
0.1.2
0.10.0
0.10.1
0.10.2
0.10.3
0.10.4
0.2
0.2.1
0.2.2
0.2.2.2
+ 44 more Show less
0.2.2.3
0.2.2.4
0.2.2.5
0.2.2.6
0.2.2.7
0.2.2.8
0.3
0.3.1
0.3.2
0.3.3
0.4
0.4.1
0.4rc1
0.5
0.5.1
0.5.2
0.5.3
0.5.4
0.5.5
0.5rc1
0.5rc2
0.6
0.6.1
0.6.2
0.6.3
0.6.4
0.7
0.7.1
0.7.2
0.7.3
0.7.4
0.7.5
0.8
0.8.1
0.8.1.post1
0.8.2
0.8.3
0.8.4
0.8.5
0.8.6
0.9
0.9.1
0.9.2
0.9.3
References Updated Jul 01, 2026 · Source: OSV.dev | ||
0.9
minor
2 CVEs
CVE-2026-31237
PYSEC-2026-404
GHSA-wcr3-gm9f-f87q
Jun 29, 2026
Ludwig framework is vulnerable to insecure deserialization through its predict() method.
9.8
/ 10
Critical
Network
Low
None
None
Unchanged
High
High
High
The Ludwig framework thru 0.10.4 is vulnerable to insecure deserialization (CWE-502) through its predict() method. When a user provides a dataset file path to the predict() method, the framework automatically determines the file format. If the file is a pickle (.pkl) file, it is loaded using pandas.read_pickle() without any validation or security restrictions. This allows the deserialization of arbitrary Python objects via the unsafe pickle module. A remote attacker can exploit this by providing a maliciously crafted pickle file, leading to arbitrary code execution on the system running the Ludwig prediction. Affected versions
0.1.0
0.1.1
0.1.2
0.10.0
0.10.1
0.10.2
0.10.3
0.10.4
0.2
0.2.1
0.2.2
0.2.2.2
+ 44 more Show less
0.2.2.3
0.2.2.4
0.2.2.5
0.2.2.6
0.2.2.7
0.2.2.8
0.3
0.3.1
0.3.2
0.3.3
0.4
0.4.1
0.4rc1
0.5
0.5.1
0.5.2
0.5.3
0.5.4
0.5.5
0.5rc1
0.5rc2
0.6
0.6.1
0.6.2
0.6.3
0.6.4
0.7
0.7.1
0.7.2
0.7.3
0.7.4
0.7.5
0.8
0.8.1
0.8.1.post1
0.8.2
0.8.3
0.8.4
0.8.5
0.8.6
0.9
0.9.1
0.9.2
0.9.3
References Updated Jul 01, 2026 · Source: OSV.dev
CVE-2026-31238
PYSEC-2026-405
GHSA-xp5q-5q7g-q26r
Jun 29, 2026
Ludwig framework is vulnerable to insecure deserialization in its model serving component
9.8
/ 10
Critical
Network
Low
None
None
Unchanged
High
High
High
The Ludwig framework thru 0.10.4 is vulnerable to insecure deserialization (CWE-502) in its model serving component. When starting a model server with the ludwig serve command, the framework loads model weight files using torch.load() without enabling the security-restrictive weights_only=True parameter. This default behavior allows the deserialization of arbitrary Python objects via the pickle module. An attacker can exploit this by providing a maliciously crafted PyTorch model file, leading to arbitrary code execution on the system hosting the Ludwig model server. Affected versions
0.1.0
0.1.1
0.1.2
0.10.0
0.10.1
0.10.2
0.10.3
0.10.4
0.2
0.2.1
0.2.2
0.2.2.2
+ 44 more Show less
0.2.2.3
0.2.2.4
0.2.2.5
0.2.2.6
0.2.2.7
0.2.2.8
0.3
0.3.1
0.3.2
0.3.3
0.4
0.4.1
0.4rc1
0.5
0.5.1
0.5.2
0.5.3
0.5.4
0.5.5
0.5rc1
0.5rc2
0.6
0.6.1
0.6.2
0.6.3
0.6.4
0.7
0.7.1
0.7.2
0.7.3
0.7.4
0.7.5
0.8
0.8.1
0.8.1.post1
0.8.2
0.8.3
0.8.4
0.8.5
0.8.6
0.9
0.9.1
0.9.2
0.9.3
References Updated Jul 01, 2026 · Source: OSV.dev | ||
0.8.6
patch
2 CVEs
CVE-2026-31237
PYSEC-2026-404
GHSA-wcr3-gm9f-f87q
Jun 29, 2026
Ludwig framework is vulnerable to insecure deserialization through its predict() method.
9.8
/ 10
Critical
Network
Low
None
None
Unchanged
High
High
High
The Ludwig framework thru 0.10.4 is vulnerable to insecure deserialization (CWE-502) through its predict() method. When a user provides a dataset file path to the predict() method, the framework automatically determines the file format. If the file is a pickle (.pkl) file, it is loaded using pandas.read_pickle() without any validation or security restrictions. This allows the deserialization of arbitrary Python objects via the unsafe pickle module. A remote attacker can exploit this by providing a maliciously crafted pickle file, leading to arbitrary code execution on the system running the Ludwig prediction. Affected versions
0.1.0
0.1.1
0.1.2
0.10.0
0.10.1
0.10.2
0.10.3
0.10.4
0.2
0.2.1
0.2.2
0.2.2.2
+ 44 more Show less
0.2.2.3
0.2.2.4
0.2.2.5
0.2.2.6
0.2.2.7
0.2.2.8
0.3
0.3.1
0.3.2
0.3.3
0.4
0.4.1
0.4rc1
0.5
0.5.1
0.5.2
0.5.3
0.5.4
0.5.5
0.5rc1
0.5rc2
0.6
0.6.1
0.6.2
0.6.3
0.6.4
0.7
0.7.1
0.7.2
0.7.3
0.7.4
0.7.5
0.8
0.8.1
0.8.1.post1
0.8.2
0.8.3
0.8.4
0.8.5
0.8.6
0.9
0.9.1
0.9.2
0.9.3
References Updated Jul 01, 2026 · Source: OSV.dev
CVE-2026-31238
PYSEC-2026-405
GHSA-xp5q-5q7g-q26r
Jun 29, 2026
Ludwig framework is vulnerable to insecure deserialization in its model serving component
9.8
/ 10
Critical
Network
Low
None
None
Unchanged
High
High
High
The Ludwig framework thru 0.10.4 is vulnerable to insecure deserialization (CWE-502) in its model serving component. When starting a model server with the ludwig serve command, the framework loads model weight files using torch.load() without enabling the security-restrictive weights_only=True parameter. This default behavior allows the deserialization of arbitrary Python objects via the pickle module. An attacker can exploit this by providing a maliciously crafted PyTorch model file, leading to arbitrary code execution on the system hosting the Ludwig model server. Affected versions
0.1.0
0.1.1
0.1.2
0.10.0
0.10.1
0.10.2
0.10.3
0.10.4
0.2
0.2.1
0.2.2
0.2.2.2
+ 44 more Show less
0.2.2.3
0.2.2.4
0.2.2.5
0.2.2.6
0.2.2.7
0.2.2.8
0.3
0.3.1
0.3.2
0.3.3
0.4
0.4.1
0.4rc1
0.5
0.5.1
0.5.2
0.5.3
0.5.4
0.5.5
0.5rc1
0.5rc2
0.6
0.6.1
0.6.2
0.6.3
0.6.4
0.7
0.7.1
0.7.2
0.7.3
0.7.4
0.7.5
0.8
0.8.1
0.8.1.post1
0.8.2
0.8.3
0.8.4
0.8.5
0.8.6
0.9
0.9.1
0.9.2
0.9.3
References Updated Jul 01, 2026 · Source: OSV.dev | ||
0.8.5
patch
2 CVEs
CVE-2026-31237
PYSEC-2026-404
GHSA-wcr3-gm9f-f87q
Jun 29, 2026
Ludwig framework is vulnerable to insecure deserialization through its predict() method.
9.8
/ 10
Critical
Network
Low
None
None
Unchanged
High
High
High
The Ludwig framework thru 0.10.4 is vulnerable to insecure deserialization (CWE-502) through its predict() method. When a user provides a dataset file path to the predict() method, the framework automatically determines the file format. If the file is a pickle (.pkl) file, it is loaded using pandas.read_pickle() without any validation or security restrictions. This allows the deserialization of arbitrary Python objects via the unsafe pickle module. A remote attacker can exploit this by providing a maliciously crafted pickle file, leading to arbitrary code execution on the system running the Ludwig prediction. Affected versions
0.1.0
0.1.1
0.1.2
0.10.0
0.10.1
0.10.2
0.10.3
0.10.4
0.2
0.2.1
0.2.2
0.2.2.2
+ 44 more Show less
0.2.2.3
0.2.2.4
0.2.2.5
0.2.2.6
0.2.2.7
0.2.2.8
0.3
0.3.1
0.3.2
0.3.3
0.4
0.4.1
0.4rc1
0.5
0.5.1
0.5.2
0.5.3
0.5.4
0.5.5
0.5rc1
0.5rc2
0.6
0.6.1
0.6.2
0.6.3
0.6.4
0.7
0.7.1
0.7.2
0.7.3
0.7.4
0.7.5
0.8
0.8.1
0.8.1.post1
0.8.2
0.8.3
0.8.4
0.8.5
0.8.6
0.9
0.9.1
0.9.2
0.9.3
References Updated Jul 01, 2026 · Source: OSV.dev
CVE-2026-31238
PYSEC-2026-405
GHSA-xp5q-5q7g-q26r
Jun 29, 2026
Ludwig framework is vulnerable to insecure deserialization in its model serving component
9.8
/ 10
Critical
Network
Low
None
None
Unchanged
High
High
High
The Ludwig framework thru 0.10.4 is vulnerable to insecure deserialization (CWE-502) in its model serving component. When starting a model server with the ludwig serve command, the framework loads model weight files using torch.load() without enabling the security-restrictive weights_only=True parameter. This default behavior allows the deserialization of arbitrary Python objects via the pickle module. An attacker can exploit this by providing a maliciously crafted PyTorch model file, leading to arbitrary code execution on the system hosting the Ludwig model server. Affected versions
0.1.0
0.1.1
0.1.2
0.10.0
0.10.1
0.10.2
0.10.3
0.10.4
0.2
0.2.1
0.2.2
0.2.2.2
+ 44 more Show less
0.2.2.3
0.2.2.4
0.2.2.5
0.2.2.6
0.2.2.7
0.2.2.8
0.3
0.3.1
0.3.2
0.3.3
0.4
0.4.1
0.4rc1
0.5
0.5.1
0.5.2
0.5.3
0.5.4
0.5.5
0.5rc1
0.5rc2
0.6
0.6.1
0.6.2
0.6.3
0.6.4
0.7
0.7.1
0.7.2
0.7.3
0.7.4
0.7.5
0.8
0.8.1
0.8.1.post1
0.8.2
0.8.3
0.8.4
0.8.5
0.8.6
0.9
0.9.1
0.9.2
0.9.3
References Updated Jul 01, 2026 · Source: OSV.dev | ||
0.8.4
patch
2 CVEs
CVE-2026-31237
PYSEC-2026-404
GHSA-wcr3-gm9f-f87q
Jun 29, 2026
Ludwig framework is vulnerable to insecure deserialization through its predict() method.
9.8
/ 10
Critical
Network
Low
None
None
Unchanged
High
High
High
The Ludwig framework thru 0.10.4 is vulnerable to insecure deserialization (CWE-502) through its predict() method. When a user provides a dataset file path to the predict() method, the framework automatically determines the file format. If the file is a pickle (.pkl) file, it is loaded using pandas.read_pickle() without any validation or security restrictions. This allows the deserialization of arbitrary Python objects via the unsafe pickle module. A remote attacker can exploit this by providing a maliciously crafted pickle file, leading to arbitrary code execution on the system running the Ludwig prediction. Affected versions
0.1.0
0.1.1
0.1.2
0.10.0
0.10.1
0.10.2
0.10.3
0.10.4
0.2
0.2.1
0.2.2
0.2.2.2
+ 44 more Show less
0.2.2.3
0.2.2.4
0.2.2.5
0.2.2.6
0.2.2.7
0.2.2.8
0.3
0.3.1
0.3.2
0.3.3
0.4
0.4.1
0.4rc1
0.5
0.5.1
0.5.2
0.5.3
0.5.4
0.5.5
0.5rc1
0.5rc2
0.6
0.6.1
0.6.2
0.6.3
0.6.4
0.7
0.7.1
0.7.2
0.7.3
0.7.4
0.7.5
0.8
0.8.1
0.8.1.post1
0.8.2
0.8.3
0.8.4
0.8.5
0.8.6
0.9
0.9.1
0.9.2
0.9.3
References Updated Jul 01, 2026 · Source: OSV.dev
CVE-2026-31238
PYSEC-2026-405
GHSA-xp5q-5q7g-q26r
Jun 29, 2026
Ludwig framework is vulnerable to insecure deserialization in its model serving component
9.8
/ 10
Critical
Network
Low
None
None
Unchanged
High
High
High
The Ludwig framework thru 0.10.4 is vulnerable to insecure deserialization (CWE-502) in its model serving component. When starting a model server with the ludwig serve command, the framework loads model weight files using torch.load() without enabling the security-restrictive weights_only=True parameter. This default behavior allows the deserialization of arbitrary Python objects via the pickle module. An attacker can exploit this by providing a maliciously crafted PyTorch model file, leading to arbitrary code execution on the system hosting the Ludwig model server. Affected versions
0.1.0
0.1.1
0.1.2
0.10.0
0.10.1
0.10.2
0.10.3
0.10.4
0.2
0.2.1
0.2.2
0.2.2.2
+ 44 more Show less
0.2.2.3
0.2.2.4
0.2.2.5
0.2.2.6
0.2.2.7
0.2.2.8
0.3
0.3.1
0.3.2
0.3.3
0.4
0.4.1
0.4rc1
0.5
0.5.1
0.5.2
0.5.3
0.5.4
0.5.5
0.5rc1
0.5rc2
0.6
0.6.1
0.6.2
0.6.3
0.6.4
0.7
0.7.1
0.7.2
0.7.3
0.7.4
0.7.5
0.8
0.8.1
0.8.1.post1
0.8.2
0.8.3
0.8.4
0.8.5
0.8.6
0.9
0.9.1
0.9.2
0.9.3
References Updated Jul 01, 2026 · Source: OSV.dev | ||
0.8.3
patch
2 CVEs
CVE-2026-31237
PYSEC-2026-404
GHSA-wcr3-gm9f-f87q
Jun 29, 2026
Ludwig framework is vulnerable to insecure deserialization through its predict() method.
9.8
/ 10
Critical
Network
Low
None
None
Unchanged
High
High
High
The Ludwig framework thru 0.10.4 is vulnerable to insecure deserialization (CWE-502) through its predict() method. When a user provides a dataset file path to the predict() method, the framework automatically determines the file format. If the file is a pickle (.pkl) file, it is loaded using pandas.read_pickle() without any validation or security restrictions. This allows the deserialization of arbitrary Python objects via the unsafe pickle module. A remote attacker can exploit this by providing a maliciously crafted pickle file, leading to arbitrary code execution on the system running the Ludwig prediction. Affected versions
0.1.0
0.1.1
0.1.2
0.10.0
0.10.1
0.10.2
0.10.3
0.10.4
0.2
0.2.1
0.2.2
0.2.2.2
+ 44 more Show less
0.2.2.3
0.2.2.4
0.2.2.5
0.2.2.6
0.2.2.7
0.2.2.8
0.3
0.3.1
0.3.2
0.3.3
0.4
0.4.1
0.4rc1
0.5
0.5.1
0.5.2
0.5.3
0.5.4
0.5.5
0.5rc1
0.5rc2
0.6
0.6.1
0.6.2
0.6.3
0.6.4
0.7
0.7.1
0.7.2
0.7.3
0.7.4
0.7.5
0.8
0.8.1
0.8.1.post1
0.8.2
0.8.3
0.8.4
0.8.5
0.8.6
0.9
0.9.1
0.9.2
0.9.3
References Updated Jul 01, 2026 · Source: OSV.dev
CVE-2026-31238
PYSEC-2026-405
GHSA-xp5q-5q7g-q26r
Jun 29, 2026
Ludwig framework is vulnerable to insecure deserialization in its model serving component
9.8
/ 10
Critical
Network
Low
None
None
Unchanged
High
High
High
The Ludwig framework thru 0.10.4 is vulnerable to insecure deserialization (CWE-502) in its model serving component. When starting a model server with the ludwig serve command, the framework loads model weight files using torch.load() without enabling the security-restrictive weights_only=True parameter. This default behavior allows the deserialization of arbitrary Python objects via the pickle module. An attacker can exploit this by providing a maliciously crafted PyTorch model file, leading to arbitrary code execution on the system hosting the Ludwig model server. Affected versions
0.1.0
0.1.1
0.1.2
0.10.0
0.10.1
0.10.2
0.10.3
0.10.4
0.2
0.2.1
0.2.2
0.2.2.2
+ 44 more Show less
0.2.2.3
0.2.2.4
0.2.2.5
0.2.2.6
0.2.2.7
0.2.2.8
0.3
0.3.1
0.3.2
0.3.3
0.4
0.4.1
0.4rc1
0.5
0.5.1
0.5.2
0.5.3
0.5.4
0.5.5
0.5rc1
0.5rc2
0.6
0.6.1
0.6.2
0.6.3
0.6.4
0.7
0.7.1
0.7.2
0.7.3
0.7.4
0.7.5
0.8
0.8.1
0.8.1.post1
0.8.2
0.8.3
0.8.4
0.8.5
0.8.6
0.9
0.9.1
0.9.2
0.9.3
References Updated Jul 01, 2026 · Source: OSV.dev | ||
0.8.2
patch
2 CVEs
CVE-2026-31237
PYSEC-2026-404
GHSA-wcr3-gm9f-f87q
Jun 29, 2026
Ludwig framework is vulnerable to insecure deserialization through its predict() method.
9.8
/ 10
Critical
Network
Low
None
None
Unchanged
High
High
High
The Ludwig framework thru 0.10.4 is vulnerable to insecure deserialization (CWE-502) through its predict() method. When a user provides a dataset file path to the predict() method, the framework automatically determines the file format. If the file is a pickle (.pkl) file, it is loaded using pandas.read_pickle() without any validation or security restrictions. This allows the deserialization of arbitrary Python objects via the unsafe pickle module. A remote attacker can exploit this by providing a maliciously crafted pickle file, leading to arbitrary code execution on the system running the Ludwig prediction. Affected versions
0.1.0
0.1.1
0.1.2
0.10.0
0.10.1
0.10.2
0.10.3
0.10.4
0.2
0.2.1
0.2.2
0.2.2.2
+ 44 more Show less
0.2.2.3
0.2.2.4
0.2.2.5
0.2.2.6
0.2.2.7
0.2.2.8
0.3
0.3.1
0.3.2
0.3.3
0.4
0.4.1
0.4rc1
0.5
0.5.1
0.5.2
0.5.3
0.5.4
0.5.5
0.5rc1
0.5rc2
0.6
0.6.1
0.6.2
0.6.3
0.6.4
0.7
0.7.1
0.7.2
0.7.3
0.7.4
0.7.5
0.8
0.8.1
0.8.1.post1
0.8.2
0.8.3
0.8.4
0.8.5
0.8.6
0.9
0.9.1
0.9.2
0.9.3
References Updated Jul 01, 2026 · Source: OSV.dev
CVE-2026-31238
PYSEC-2026-405
GHSA-xp5q-5q7g-q26r
Jun 29, 2026
Ludwig framework is vulnerable to insecure deserialization in its model serving component
9.8
/ 10
Critical
Network
Low
None
None
Unchanged
High
High
High
The Ludwig framework thru 0.10.4 is vulnerable to insecure deserialization (CWE-502) in its model serving component. When starting a model server with the ludwig serve command, the framework loads model weight files using torch.load() without enabling the security-restrictive weights_only=True parameter. This default behavior allows the deserialization of arbitrary Python objects via the pickle module. An attacker can exploit this by providing a maliciously crafted PyTorch model file, leading to arbitrary code execution on the system hosting the Ludwig model server. Affected versions
0.1.0
0.1.1
0.1.2
0.10.0
0.10.1
0.10.2
0.10.3
0.10.4
0.2
0.2.1
0.2.2
0.2.2.2
+ 44 more Show less
0.2.2.3
0.2.2.4
0.2.2.5
0.2.2.6
0.2.2.7
0.2.2.8
0.3
0.3.1
0.3.2
0.3.3
0.4
0.4.1
0.4rc1
0.5
0.5.1
0.5.2
0.5.3
0.5.4
0.5.5
0.5rc1
0.5rc2
0.6
0.6.1
0.6.2
0.6.3
0.6.4
0.7
0.7.1
0.7.2
0.7.3
0.7.4
0.7.5
0.8
0.8.1
0.8.1.post1
0.8.2
0.8.3
0.8.4
0.8.5
0.8.6
0.9
0.9.1
0.9.2
0.9.3
References Updated Jul 01, 2026 · Source: OSV.dev | ||
0.8.1.post1
pre
2 CVEs
CVE-2026-31237
PYSEC-2026-404
GHSA-wcr3-gm9f-f87q
Jun 29, 2026
Ludwig framework is vulnerable to insecure deserialization through its predict() method.
9.8
/ 10
Critical
Network
Low
None
None
Unchanged
High
High
High
The Ludwig framework thru 0.10.4 is vulnerable to insecure deserialization (CWE-502) through its predict() method. When a user provides a dataset file path to the predict() method, the framework automatically determines the file format. If the file is a pickle (.pkl) file, it is loaded using pandas.read_pickle() without any validation or security restrictions. This allows the deserialization of arbitrary Python objects via the unsafe pickle module. A remote attacker can exploit this by providing a maliciously crafted pickle file, leading to arbitrary code execution on the system running the Ludwig prediction. Affected versions
0.1.0
0.1.1
0.1.2
0.10.0
0.10.1
0.10.2
0.10.3
0.10.4
0.2
0.2.1
0.2.2
0.2.2.2
+ 44 more Show less
0.2.2.3
0.2.2.4
0.2.2.5
0.2.2.6
0.2.2.7
0.2.2.8
0.3
0.3.1
0.3.2
0.3.3
0.4
0.4.1
0.4rc1
0.5
0.5.1
0.5.2
0.5.3
0.5.4
0.5.5
0.5rc1
0.5rc2
0.6
0.6.1
0.6.2
0.6.3
0.6.4
0.7
0.7.1
0.7.2
0.7.3
0.7.4
0.7.5
0.8
0.8.1
0.8.1.post1
0.8.2
0.8.3
0.8.4
0.8.5
0.8.6
0.9
0.9.1
0.9.2
0.9.3
References Updated Jul 01, 2026 · Source: OSV.dev
CVE-2026-31238
PYSEC-2026-405
GHSA-xp5q-5q7g-q26r
Jun 29, 2026
Ludwig framework is vulnerable to insecure deserialization in its model serving component
9.8
/ 10
Critical
Network
Low
None
None
Unchanged
High
High
High
The Ludwig framework thru 0.10.4 is vulnerable to insecure deserialization (CWE-502) in its model serving component. When starting a model server with the ludwig serve command, the framework loads model weight files using torch.load() without enabling the security-restrictive weights_only=True parameter. This default behavior allows the deserialization of arbitrary Python objects via the pickle module. An attacker can exploit this by providing a maliciously crafted PyTorch model file, leading to arbitrary code execution on the system hosting the Ludwig model server. Affected versions
0.1.0
0.1.1
0.1.2
0.10.0
0.10.1
0.10.2
0.10.3
0.10.4
0.2
0.2.1
0.2.2
0.2.2.2
+ 44 more Show less
0.2.2.3
0.2.2.4
0.2.2.5
0.2.2.6
0.2.2.7
0.2.2.8
0.3
0.3.1
0.3.2
0.3.3
0.4
0.4.1
0.4rc1
0.5
0.5.1
0.5.2
0.5.3
0.5.4
0.5.5
0.5rc1
0.5rc2
0.6
0.6.1
0.6.2
0.6.3
0.6.4
0.7
0.7.1
0.7.2
0.7.3
0.7.4
0.7.5
0.8
0.8.1
0.8.1.post1
0.8.2
0.8.3
0.8.4
0.8.5
0.8.6
0.9
0.9.1
0.9.2
0.9.3
References Updated Jul 01, 2026 · Source: OSV.dev | ||
0.8.1
patch
2 CVEs
CVE-2026-31237
PYSEC-2026-404
GHSA-wcr3-gm9f-f87q
Jun 29, 2026
Ludwig framework is vulnerable to insecure deserialization through its predict() method.
9.8
/ 10
Critical
Network
Low
None
None
Unchanged
High
High
High
The Ludwig framework thru 0.10.4 is vulnerable to insecure deserialization (CWE-502) through its predict() method. When a user provides a dataset file path to the predict() method, the framework automatically determines the file format. If the file is a pickle (.pkl) file, it is loaded using pandas.read_pickle() without any validation or security restrictions. This allows the deserialization of arbitrary Python objects via the unsafe pickle module. A remote attacker can exploit this by providing a maliciously crafted pickle file, leading to arbitrary code execution on the system running the Ludwig prediction. Affected versions
0.1.0
0.1.1
0.1.2
0.10.0
0.10.1
0.10.2
0.10.3
0.10.4
0.2
0.2.1
0.2.2
0.2.2.2
+ 44 more Show less
0.2.2.3
0.2.2.4
0.2.2.5
0.2.2.6
0.2.2.7
0.2.2.8
0.3
0.3.1
0.3.2
0.3.3
0.4
0.4.1
0.4rc1
0.5
0.5.1
0.5.2
0.5.3
0.5.4
0.5.5
0.5rc1
0.5rc2
0.6
0.6.1
0.6.2
0.6.3
0.6.4
0.7
0.7.1
0.7.2
0.7.3
0.7.4
0.7.5
0.8
0.8.1
0.8.1.post1
0.8.2
0.8.3
0.8.4
0.8.5
0.8.6
0.9
0.9.1
0.9.2
0.9.3
References Updated Jul 01, 2026 · Source: OSV.dev
CVE-2026-31238
PYSEC-2026-405
GHSA-xp5q-5q7g-q26r
Jun 29, 2026
Ludwig framework is vulnerable to insecure deserialization in its model serving component
9.8
/ 10
Critical
Network
Low
None
None
Unchanged
High
High
High
The Ludwig framework thru 0.10.4 is vulnerable to insecure deserialization (CWE-502) in its model serving component. When starting a model server with the ludwig serve command, the framework loads model weight files using torch.load() without enabling the security-restrictive weights_only=True parameter. This default behavior allows the deserialization of arbitrary Python objects via the pickle module. An attacker can exploit this by providing a maliciously crafted PyTorch model file, leading to arbitrary code execution on the system hosting the Ludwig model server. Affected versions
0.1.0
0.1.1
0.1.2
0.10.0
0.10.1
0.10.2
0.10.3
0.10.4
0.2
0.2.1
0.2.2
0.2.2.2
+ 44 more Show less
0.2.2.3
0.2.2.4
0.2.2.5
0.2.2.6
0.2.2.7
0.2.2.8
0.3
0.3.1
0.3.2
0.3.3
0.4
0.4.1
0.4rc1
0.5
0.5.1
0.5.2
0.5.3
0.5.4
0.5.5
0.5rc1
0.5rc2
0.6
0.6.1
0.6.2
0.6.3
0.6.4
0.7
0.7.1
0.7.2
0.7.3
0.7.4
0.7.5
0.8
0.8.1
0.8.1.post1
0.8.2
0.8.3
0.8.4
0.8.5
0.8.6
0.9
0.9.1
0.9.2
0.9.3
References Updated Jul 01, 2026 · Source: OSV.dev | ||
0.8
minor
2 CVEs
CVE-2026-31237
PYSEC-2026-404
GHSA-wcr3-gm9f-f87q
Jun 29, 2026
Ludwig framework is vulnerable to insecure deserialization through its predict() method.
9.8
/ 10
Critical
Network
Low
None
None
Unchanged
High
High
High
The Ludwig framework thru 0.10.4 is vulnerable to insecure deserialization (CWE-502) through its predict() method. When a user provides a dataset file path to the predict() method, the framework automatically determines the file format. If the file is a pickle (.pkl) file, it is loaded using pandas.read_pickle() without any validation or security restrictions. This allows the deserialization of arbitrary Python objects via the unsafe pickle module. A remote attacker can exploit this by providing a maliciously crafted pickle file, leading to arbitrary code execution on the system running the Ludwig prediction. Affected versions
0.1.0
0.1.1
0.1.2
0.10.0
0.10.1
0.10.2
0.10.3
0.10.4
0.2
0.2.1
0.2.2
0.2.2.2
+ 44 more Show less
0.2.2.3
0.2.2.4
0.2.2.5
0.2.2.6
0.2.2.7
0.2.2.8
0.3
0.3.1
0.3.2
0.3.3
0.4
0.4.1
0.4rc1
0.5
0.5.1
0.5.2
0.5.3
0.5.4
0.5.5
0.5rc1
0.5rc2
0.6
0.6.1
0.6.2
0.6.3
0.6.4
0.7
0.7.1
0.7.2
0.7.3
0.7.4
0.7.5
0.8
0.8.1
0.8.1.post1
0.8.2
0.8.3
0.8.4
0.8.5
0.8.6
0.9
0.9.1
0.9.2
0.9.3
References Updated Jul 01, 2026 · Source: OSV.dev
CVE-2026-31238
PYSEC-2026-405
GHSA-xp5q-5q7g-q26r
Jun 29, 2026
Ludwig framework is vulnerable to insecure deserialization in its model serving component
9.8
/ 10
Critical
Network
Low
None
None
Unchanged
High
High
High
The Ludwig framework thru 0.10.4 is vulnerable to insecure deserialization (CWE-502) in its model serving component. When starting a model server with the ludwig serve command, the framework loads model weight files using torch.load() without enabling the security-restrictive weights_only=True parameter. This default behavior allows the deserialization of arbitrary Python objects via the pickle module. An attacker can exploit this by providing a maliciously crafted PyTorch model file, leading to arbitrary code execution on the system hosting the Ludwig model server. Affected versions
0.1.0
0.1.1
0.1.2
0.10.0
0.10.1
0.10.2
0.10.3
0.10.4
0.2
0.2.1
0.2.2
0.2.2.2
+ 44 more Show less
0.2.2.3
0.2.2.4
0.2.2.5
0.2.2.6
0.2.2.7
0.2.2.8
0.3
0.3.1
0.3.2
0.3.3
0.4
0.4.1
0.4rc1
0.5
0.5.1
0.5.2
0.5.3
0.5.4
0.5.5
0.5rc1
0.5rc2
0.6
0.6.1
0.6.2
0.6.3
0.6.4
0.7
0.7.1
0.7.2
0.7.3
0.7.4
0.7.5
0.8
0.8.1
0.8.1.post1
0.8.2
0.8.3
0.8.4
0.8.5
0.8.6
0.9
0.9.1
0.9.2
0.9.3
References Updated Jul 01, 2026 · Source: OSV.dev | ||
0.7.5
patch
2 CVEs
CVE-2026-31237
PYSEC-2026-404
GHSA-wcr3-gm9f-f87q
Jun 29, 2026
Ludwig framework is vulnerable to insecure deserialization through its predict() method.
9.8
/ 10
Critical
Network
Low
None
None
Unchanged
High
High
High
The Ludwig framework thru 0.10.4 is vulnerable to insecure deserialization (CWE-502) through its predict() method. When a user provides a dataset file path to the predict() method, the framework automatically determines the file format. If the file is a pickle (.pkl) file, it is loaded using pandas.read_pickle() without any validation or security restrictions. This allows the deserialization of arbitrary Python objects via the unsafe pickle module. A remote attacker can exploit this by providing a maliciously crafted pickle file, leading to arbitrary code execution on the system running the Ludwig prediction. Affected versions
0.1.0
0.1.1
0.1.2
0.10.0
0.10.1
0.10.2
0.10.3
0.10.4
0.2
0.2.1
0.2.2
0.2.2.2
+ 44 more Show less
0.2.2.3
0.2.2.4
0.2.2.5
0.2.2.6
0.2.2.7
0.2.2.8
0.3
0.3.1
0.3.2
0.3.3
0.4
0.4.1
0.4rc1
0.5
0.5.1
0.5.2
0.5.3
0.5.4
0.5.5
0.5rc1
0.5rc2
0.6
0.6.1
0.6.2
0.6.3
0.6.4
0.7
0.7.1
0.7.2
0.7.3
0.7.4
0.7.5
0.8
0.8.1
0.8.1.post1
0.8.2
0.8.3
0.8.4
0.8.5
0.8.6
0.9
0.9.1
0.9.2
0.9.3
References Updated Jul 01, 2026 · Source: OSV.dev
CVE-2026-31238
PYSEC-2026-405
GHSA-xp5q-5q7g-q26r
Jun 29, 2026
Ludwig framework is vulnerable to insecure deserialization in its model serving component
9.8
/ 10
Critical
Network
Low
None
None
Unchanged
High
High
High
The Ludwig framework thru 0.10.4 is vulnerable to insecure deserialization (CWE-502) in its model serving component. When starting a model server with the ludwig serve command, the framework loads model weight files using torch.load() without enabling the security-restrictive weights_only=True parameter. This default behavior allows the deserialization of arbitrary Python objects via the pickle module. An attacker can exploit this by providing a maliciously crafted PyTorch model file, leading to arbitrary code execution on the system hosting the Ludwig model server. Affected versions
0.1.0
0.1.1
0.1.2
0.10.0
0.10.1
0.10.2
0.10.3
0.10.4
0.2
0.2.1
0.2.2
0.2.2.2
+ 44 more Show less
0.2.2.3
0.2.2.4
0.2.2.5
0.2.2.6
0.2.2.7
0.2.2.8
0.3
0.3.1
0.3.2
0.3.3
0.4
0.4.1
0.4rc1
0.5
0.5.1
0.5.2
0.5.3
0.5.4
0.5.5
0.5rc1
0.5rc2
0.6
0.6.1
0.6.2
0.6.3
0.6.4
0.7
0.7.1
0.7.2
0.7.3
0.7.4
0.7.5
0.8
0.8.1
0.8.1.post1
0.8.2
0.8.3
0.8.4
0.8.5
0.8.6
0.9
0.9.1
0.9.2
0.9.3
References Updated Jul 01, 2026 · Source: OSV.dev | ||
0.7.4
patch
2 CVEs
CVE-2026-31237
PYSEC-2026-404
GHSA-wcr3-gm9f-f87q
Jun 29, 2026
Ludwig framework is vulnerable to insecure deserialization through its predict() method.
9.8
/ 10
Critical
Network
Low
None
None
Unchanged
High
High
High
The Ludwig framework thru 0.10.4 is vulnerable to insecure deserialization (CWE-502) through its predict() method. When a user provides a dataset file path to the predict() method, the framework automatically determines the file format. If the file is a pickle (.pkl) file, it is loaded using pandas.read_pickle() without any validation or security restrictions. This allows the deserialization of arbitrary Python objects via the unsafe pickle module. A remote attacker can exploit this by providing a maliciously crafted pickle file, leading to arbitrary code execution on the system running the Ludwig prediction. Affected versions
0.1.0
0.1.1
0.1.2
0.10.0
0.10.1
0.10.2
0.10.3
0.10.4
0.2
0.2.1
0.2.2
0.2.2.2
+ 44 more Show less
0.2.2.3
0.2.2.4
0.2.2.5
0.2.2.6
0.2.2.7
0.2.2.8
0.3
0.3.1
0.3.2
0.3.3
0.4
0.4.1
0.4rc1
0.5
0.5.1
0.5.2
0.5.3
0.5.4
0.5.5
0.5rc1
0.5rc2
0.6
0.6.1
0.6.2
0.6.3
0.6.4
0.7
0.7.1
0.7.2
0.7.3
0.7.4
0.7.5
0.8
0.8.1
0.8.1.post1
0.8.2
0.8.3
0.8.4
0.8.5
0.8.6
0.9
0.9.1
0.9.2
0.9.3
References Updated Jul 01, 2026 · Source: OSV.dev
CVE-2026-31238
PYSEC-2026-405
GHSA-xp5q-5q7g-q26r
Jun 29, 2026
Ludwig framework is vulnerable to insecure deserialization in its model serving component
9.8
/ 10
Critical
Network
Low
None
None
Unchanged
High
High
High
The Ludwig framework thru 0.10.4 is vulnerable to insecure deserialization (CWE-502) in its model serving component. When starting a model server with the ludwig serve command, the framework loads model weight files using torch.load() without enabling the security-restrictive weights_only=True parameter. This default behavior allows the deserialization of arbitrary Python objects via the pickle module. An attacker can exploit this by providing a maliciously crafted PyTorch model file, leading to arbitrary code execution on the system hosting the Ludwig model server. Affected versions
0.1.0
0.1.1
0.1.2
0.10.0
0.10.1
0.10.2
0.10.3
0.10.4
0.2
0.2.1
0.2.2
0.2.2.2
+ 44 more Show less
0.2.2.3
0.2.2.4
0.2.2.5
0.2.2.6
0.2.2.7
0.2.2.8
0.3
0.3.1
0.3.2
0.3.3
0.4
0.4.1
0.4rc1
0.5
0.5.1
0.5.2
0.5.3
0.5.4
0.5.5
0.5rc1
0.5rc2
0.6
0.6.1
0.6.2
0.6.3
0.6.4
0.7
0.7.1
0.7.2
0.7.3
0.7.4
0.7.5
0.8
0.8.1
0.8.1.post1
0.8.2
0.8.3
0.8.4
0.8.5
0.8.6
0.9
0.9.1
0.9.2
0.9.3
References Updated Jul 01, 2026 · Source: OSV.dev | ||
0.7.3
patch
2 CVEs
CVE-2026-31237
PYSEC-2026-404
GHSA-wcr3-gm9f-f87q
Jun 29, 2026
Ludwig framework is vulnerable to insecure deserialization through its predict() method.
9.8
/ 10
Critical
Network
Low
None
None
Unchanged
High
High
High
The Ludwig framework thru 0.10.4 is vulnerable to insecure deserialization (CWE-502) through its predict() method. When a user provides a dataset file path to the predict() method, the framework automatically determines the file format. If the file is a pickle (.pkl) file, it is loaded using pandas.read_pickle() without any validation or security restrictions. This allows the deserialization of arbitrary Python objects via the unsafe pickle module. A remote attacker can exploit this by providing a maliciously crafted pickle file, leading to arbitrary code execution on the system running the Ludwig prediction. Affected versions
0.1.0
0.1.1
0.1.2
0.10.0
0.10.1
0.10.2
0.10.3
0.10.4
0.2
0.2.1
0.2.2
0.2.2.2
+ 44 more Show less
0.2.2.3
0.2.2.4
0.2.2.5
0.2.2.6
0.2.2.7
0.2.2.8
0.3
0.3.1
0.3.2
0.3.3
0.4
0.4.1
0.4rc1
0.5
0.5.1
0.5.2
0.5.3
0.5.4
0.5.5
0.5rc1
0.5rc2
0.6
0.6.1
0.6.2
0.6.3
0.6.4
0.7
0.7.1
0.7.2
0.7.3
0.7.4
0.7.5
0.8
0.8.1
0.8.1.post1
0.8.2
0.8.3
0.8.4
0.8.5
0.8.6
0.9
0.9.1
0.9.2
0.9.3
References Updated Jul 01, 2026 · Source: OSV.dev
CVE-2026-31238
PYSEC-2026-405
GHSA-xp5q-5q7g-q26r
Jun 29, 2026
Ludwig framework is vulnerable to insecure deserialization in its model serving component
9.8
/ 10
Critical
Network
Low
None
None
Unchanged
High
High
High
The Ludwig framework thru 0.10.4 is vulnerable to insecure deserialization (CWE-502) in its model serving component. When starting a model server with the ludwig serve command, the framework loads model weight files using torch.load() without enabling the security-restrictive weights_only=True parameter. This default behavior allows the deserialization of arbitrary Python objects via the pickle module. An attacker can exploit this by providing a maliciously crafted PyTorch model file, leading to arbitrary code execution on the system hosting the Ludwig model server. Affected versions
0.1.0
0.1.1
0.1.2
0.10.0
0.10.1
0.10.2
0.10.3
0.10.4
0.2
0.2.1
0.2.2
0.2.2.2
+ 44 more Show less
0.2.2.3
0.2.2.4
0.2.2.5
0.2.2.6
0.2.2.7
0.2.2.8
0.3
0.3.1
0.3.2
0.3.3
0.4
0.4.1
0.4rc1
0.5
0.5.1
0.5.2
0.5.3
0.5.4
0.5.5
0.5rc1
0.5rc2
0.6
0.6.1
0.6.2
0.6.3
0.6.4
0.7
0.7.1
0.7.2
0.7.3
0.7.4
0.7.5
0.8
0.8.1
0.8.1.post1
0.8.2
0.8.3
0.8.4
0.8.5
0.8.6
0.9
0.9.1
0.9.2
0.9.3
References Updated Jul 01, 2026 · Source: OSV.dev | ||
0.7.2
patch
2 CVEs
CVE-2026-31237
PYSEC-2026-404
GHSA-wcr3-gm9f-f87q
Jun 29, 2026
Ludwig framework is vulnerable to insecure deserialization through its predict() method.
9.8
/ 10
Critical
Network
Low
None
None
Unchanged
High
High
High
The Ludwig framework thru 0.10.4 is vulnerable to insecure deserialization (CWE-502) through its predict() method. When a user provides a dataset file path to the predict() method, the framework automatically determines the file format. If the file is a pickle (.pkl) file, it is loaded using pandas.read_pickle() without any validation or security restrictions. This allows the deserialization of arbitrary Python objects via the unsafe pickle module. A remote attacker can exploit this by providing a maliciously crafted pickle file, leading to arbitrary code execution on the system running the Ludwig prediction. Affected versions
0.1.0
0.1.1
0.1.2
0.10.0
0.10.1
0.10.2
0.10.3
0.10.4
0.2
0.2.1
0.2.2
0.2.2.2
+ 44 more Show less
0.2.2.3
0.2.2.4
0.2.2.5
0.2.2.6
0.2.2.7
0.2.2.8
0.3
0.3.1
0.3.2
0.3.3
0.4
0.4.1
0.4rc1
0.5
0.5.1
0.5.2
0.5.3
0.5.4
0.5.5
0.5rc1
0.5rc2
0.6
0.6.1
0.6.2
0.6.3
0.6.4
0.7
0.7.1
0.7.2
0.7.3
0.7.4
0.7.5
0.8
0.8.1
0.8.1.post1
0.8.2
0.8.3
0.8.4
0.8.5
0.8.6
0.9
0.9.1
0.9.2
0.9.3
References Updated Jul 01, 2026 · Source: OSV.dev
CVE-2026-31238
PYSEC-2026-405
GHSA-xp5q-5q7g-q26r
Jun 29, 2026
Ludwig framework is vulnerable to insecure deserialization in its model serving component
9.8
/ 10
Critical
Network
Low
None
None
Unchanged
High
High
High
The Ludwig framework thru 0.10.4 is vulnerable to insecure deserialization (CWE-502) in its model serving component. When starting a model server with the ludwig serve command, the framework loads model weight files using torch.load() without enabling the security-restrictive weights_only=True parameter. This default behavior allows the deserialization of arbitrary Python objects via the pickle module. An attacker can exploit this by providing a maliciously crafted PyTorch model file, leading to arbitrary code execution on the system hosting the Ludwig model server. Affected versions
0.1.0
0.1.1
0.1.2
0.10.0
0.10.1
0.10.2
0.10.3
0.10.4
0.2
0.2.1
0.2.2
0.2.2.2
+ 44 more Show less
0.2.2.3
0.2.2.4
0.2.2.5
0.2.2.6
0.2.2.7
0.2.2.8
0.3
0.3.1
0.3.2
0.3.3
0.4
0.4.1
0.4rc1
0.5
0.5.1
0.5.2
0.5.3
0.5.4
0.5.5
0.5rc1
0.5rc2
0.6
0.6.1
0.6.2
0.6.3
0.6.4
0.7
0.7.1
0.7.2
0.7.3
0.7.4
0.7.5
0.8
0.8.1
0.8.1.post1
0.8.2
0.8.3
0.8.4
0.8.5
0.8.6
0.9
0.9.1
0.9.2
0.9.3
References Updated Jul 01, 2026 · Source: OSV.dev | ||
0.7.1
patch
2 CVEs
CVE-2026-31237
PYSEC-2026-404
GHSA-wcr3-gm9f-f87q
Jun 29, 2026
Ludwig framework is vulnerable to insecure deserialization through its predict() method.
9.8
/ 10
Critical
Network
Low
None
None
Unchanged
High
High
High
The Ludwig framework thru 0.10.4 is vulnerable to insecure deserialization (CWE-502) through its predict() method. When a user provides a dataset file path to the predict() method, the framework automatically determines the file format. If the file is a pickle (.pkl) file, it is loaded using pandas.read_pickle() without any validation or security restrictions. This allows the deserialization of arbitrary Python objects via the unsafe pickle module. A remote attacker can exploit this by providing a maliciously crafted pickle file, leading to arbitrary code execution on the system running the Ludwig prediction. Affected versions
0.1.0
0.1.1
0.1.2
0.10.0
0.10.1
0.10.2
0.10.3
0.10.4
0.2
0.2.1
0.2.2
0.2.2.2
+ 44 more Show less
0.2.2.3
0.2.2.4
0.2.2.5
0.2.2.6
0.2.2.7
0.2.2.8
0.3
0.3.1
0.3.2
0.3.3
0.4
0.4.1
0.4rc1
0.5
0.5.1
0.5.2
0.5.3
0.5.4
0.5.5
0.5rc1
0.5rc2
0.6
0.6.1
0.6.2
0.6.3
0.6.4
0.7
0.7.1
0.7.2
0.7.3
0.7.4
0.7.5
0.8
0.8.1
0.8.1.post1
0.8.2
0.8.3
0.8.4
0.8.5
0.8.6
0.9
0.9.1
0.9.2
0.9.3
References Updated Jul 01, 2026 · Source: OSV.dev
CVE-2026-31238
PYSEC-2026-405
GHSA-xp5q-5q7g-q26r
Jun 29, 2026
Ludwig framework is vulnerable to insecure deserialization in its model serving component
9.8
/ 10
Critical
Network
Low
None
None
Unchanged
High
High
High
The Ludwig framework thru 0.10.4 is vulnerable to insecure deserialization (CWE-502) in its model serving component. When starting a model server with the ludwig serve command, the framework loads model weight files using torch.load() without enabling the security-restrictive weights_only=True parameter. This default behavior allows the deserialization of arbitrary Python objects via the pickle module. An attacker can exploit this by providing a maliciously crafted PyTorch model file, leading to arbitrary code execution on the system hosting the Ludwig model server. Affected versions
0.1.0
0.1.1
0.1.2
0.10.0
0.10.1
0.10.2
0.10.3
0.10.4
0.2
0.2.1
0.2.2
0.2.2.2
+ 44 more Show less
0.2.2.3
0.2.2.4
0.2.2.5
0.2.2.6
0.2.2.7
0.2.2.8
0.3
0.3.1
0.3.2
0.3.3
0.4
0.4.1
0.4rc1
0.5
0.5.1
0.5.2
0.5.3
0.5.4
0.5.5
0.5rc1
0.5rc2
0.6
0.6.1
0.6.2
0.6.3
0.6.4
0.7
0.7.1
0.7.2
0.7.3
0.7.4
0.7.5
0.8
0.8.1
0.8.1.post1
0.8.2
0.8.3
0.8.4
0.8.5
0.8.6
0.9
0.9.1
0.9.2
0.9.3
References Updated Jul 01, 2026 · Source: OSV.dev | ||
0.7
minor
2 CVEs
CVE-2026-31237
PYSEC-2026-404
GHSA-wcr3-gm9f-f87q
Jun 29, 2026
Ludwig framework is vulnerable to insecure deserialization through its predict() method.
9.8
/ 10
Critical
Network
Low
None
None
Unchanged
High
High
High
The Ludwig framework thru 0.10.4 is vulnerable to insecure deserialization (CWE-502) through its predict() method. When a user provides a dataset file path to the predict() method, the framework automatically determines the file format. If the file is a pickle (.pkl) file, it is loaded using pandas.read_pickle() without any validation or security restrictions. This allows the deserialization of arbitrary Python objects via the unsafe pickle module. A remote attacker can exploit this by providing a maliciously crafted pickle file, leading to arbitrary code execution on the system running the Ludwig prediction. Affected versions
0.1.0
0.1.1
0.1.2
0.10.0
0.10.1
0.10.2
0.10.3
0.10.4
0.2
0.2.1
0.2.2
0.2.2.2
+ 44 more Show less
0.2.2.3
0.2.2.4
0.2.2.5
0.2.2.6
0.2.2.7
0.2.2.8
0.3
0.3.1
0.3.2
0.3.3
0.4
0.4.1
0.4rc1
0.5
0.5.1
0.5.2
0.5.3
0.5.4
0.5.5
0.5rc1
0.5rc2
0.6
0.6.1
0.6.2
0.6.3
0.6.4
0.7
0.7.1
0.7.2
0.7.3
0.7.4
0.7.5
0.8
0.8.1
0.8.1.post1
0.8.2
0.8.3
0.8.4
0.8.5
0.8.6
0.9
0.9.1
0.9.2
0.9.3
References Updated Jul 01, 2026 · Source: OSV.dev
CVE-2026-31238
PYSEC-2026-405
GHSA-xp5q-5q7g-q26r
Jun 29, 2026
Ludwig framework is vulnerable to insecure deserialization in its model serving component
9.8
/ 10
Critical
Network
Low
None
None
Unchanged
High
High
High
The Ludwig framework thru 0.10.4 is vulnerable to insecure deserialization (CWE-502) in its model serving component. When starting a model server with the ludwig serve command, the framework loads model weight files using torch.load() without enabling the security-restrictive weights_only=True parameter. This default behavior allows the deserialization of arbitrary Python objects via the pickle module. An attacker can exploit this by providing a maliciously crafted PyTorch model file, leading to arbitrary code execution on the system hosting the Ludwig model server. Affected versions
0.1.0
0.1.1
0.1.2
0.10.0
0.10.1
0.10.2
0.10.3
0.10.4
0.2
0.2.1
0.2.2
0.2.2.2
+ 44 more Show less
0.2.2.3
0.2.2.4
0.2.2.5
0.2.2.6
0.2.2.7
0.2.2.8
0.3
0.3.1
0.3.2
0.3.3
0.4
0.4.1
0.4rc1
0.5
0.5.1
0.5.2
0.5.3
0.5.4
0.5.5
0.5rc1
0.5rc2
0.6
0.6.1
0.6.2
0.6.3
0.6.4
0.7
0.7.1
0.7.2
0.7.3
0.7.4
0.7.5
0.8
0.8.1
0.8.1.post1
0.8.2
0.8.3
0.8.4
0.8.5
0.8.6
0.9
0.9.1
0.9.2
0.9.3
References Updated Jul 01, 2026 · Source: OSV.dev | ||
0.6.4
patch
2 CVEs
CVE-2026-31237
PYSEC-2026-404
GHSA-wcr3-gm9f-f87q
Jun 29, 2026
Ludwig framework is vulnerable to insecure deserialization through its predict() method.
9.8
/ 10
Critical
Network
Low
None
None
Unchanged
High
High
High
The Ludwig framework thru 0.10.4 is vulnerable to insecure deserialization (CWE-502) through its predict() method. When a user provides a dataset file path to the predict() method, the framework automatically determines the file format. If the file is a pickle (.pkl) file, it is loaded using pandas.read_pickle() without any validation or security restrictions. This allows the deserialization of arbitrary Python objects via the unsafe pickle module. A remote attacker can exploit this by providing a maliciously crafted pickle file, leading to arbitrary code execution on the system running the Ludwig prediction. Affected versions
0.1.0
0.1.1
0.1.2
0.10.0
0.10.1
0.10.2
0.10.3
0.10.4
0.2
0.2.1
0.2.2
0.2.2.2
+ 44 more Show less
0.2.2.3
0.2.2.4
0.2.2.5
0.2.2.6
0.2.2.7
0.2.2.8
0.3
0.3.1
0.3.2
0.3.3
0.4
0.4.1
0.4rc1
0.5
0.5.1
0.5.2
0.5.3
0.5.4
0.5.5
0.5rc1
0.5rc2
0.6
0.6.1
0.6.2
0.6.3
0.6.4
0.7
0.7.1
0.7.2
0.7.3
0.7.4
0.7.5
0.8
0.8.1
0.8.1.post1
0.8.2
0.8.3
0.8.4
0.8.5
0.8.6
0.9
0.9.1
0.9.2
0.9.3
References Updated Jul 01, 2026 · Source: OSV.dev
CVE-2026-31238
PYSEC-2026-405
GHSA-xp5q-5q7g-q26r
Jun 29, 2026
Ludwig framework is vulnerable to insecure deserialization in its model serving component
9.8
/ 10
Critical
Network
Low
None
None
Unchanged
High
High
High
The Ludwig framework thru 0.10.4 is vulnerable to insecure deserialization (CWE-502) in its model serving component. When starting a model server with the ludwig serve command, the framework loads model weight files using torch.load() without enabling the security-restrictive weights_only=True parameter. This default behavior allows the deserialization of arbitrary Python objects via the pickle module. An attacker can exploit this by providing a maliciously crafted PyTorch model file, leading to arbitrary code execution on the system hosting the Ludwig model server. Affected versions
0.1.0
0.1.1
0.1.2
0.10.0
0.10.1
0.10.2
0.10.3
0.10.4
0.2
0.2.1
0.2.2
0.2.2.2
+ 44 more Show less
0.2.2.3
0.2.2.4
0.2.2.5
0.2.2.6
0.2.2.7
0.2.2.8
0.3
0.3.1
0.3.2
0.3.3
0.4
0.4.1
0.4rc1
0.5
0.5.1
0.5.2
0.5.3
0.5.4
0.5.5
0.5rc1
0.5rc2
0.6
0.6.1
0.6.2
0.6.3
0.6.4
0.7
0.7.1
0.7.2
0.7.3
0.7.4
0.7.5
0.8
0.8.1
0.8.1.post1
0.8.2
0.8.3
0.8.4
0.8.5
0.8.6
0.9
0.9.1
0.9.2
0.9.3
References Updated Jul 01, 2026 · Source: OSV.dev | ||
0.6.3
patch
2 CVEs
CVE-2026-31237
PYSEC-2026-404
GHSA-wcr3-gm9f-f87q
Jun 29, 2026
Ludwig framework is vulnerable to insecure deserialization through its predict() method.
9.8
/ 10
Critical
Network
Low
None
None
Unchanged
High
High
High
The Ludwig framework thru 0.10.4 is vulnerable to insecure deserialization (CWE-502) through its predict() method. When a user provides a dataset file path to the predict() method, the framework automatically determines the file format. If the file is a pickle (.pkl) file, it is loaded using pandas.read_pickle() without any validation or security restrictions. This allows the deserialization of arbitrary Python objects via the unsafe pickle module. A remote attacker can exploit this by providing a maliciously crafted pickle file, leading to arbitrary code execution on the system running the Ludwig prediction. Affected versions
0.1.0
0.1.1
0.1.2
0.10.0
0.10.1
0.10.2
0.10.3
0.10.4
0.2
0.2.1
0.2.2
0.2.2.2
+ 44 more Show less
0.2.2.3
0.2.2.4
0.2.2.5
0.2.2.6
0.2.2.7
0.2.2.8
0.3
0.3.1
0.3.2
0.3.3
0.4
0.4.1
0.4rc1
0.5
0.5.1
0.5.2
0.5.3
0.5.4
0.5.5
0.5rc1
0.5rc2
0.6
0.6.1
0.6.2
0.6.3
0.6.4
0.7
0.7.1
0.7.2
0.7.3
0.7.4
0.7.5
0.8
0.8.1
0.8.1.post1
0.8.2
0.8.3
0.8.4
0.8.5
0.8.6
0.9
0.9.1
0.9.2
0.9.3
References Updated Jul 01, 2026 · Source: OSV.dev
CVE-2026-31238
PYSEC-2026-405
GHSA-xp5q-5q7g-q26r
Jun 29, 2026
Ludwig framework is vulnerable to insecure deserialization in its model serving component
9.8
/ 10
Critical
Network
Low
None
None
Unchanged
High
High
High
The Ludwig framework thru 0.10.4 is vulnerable to insecure deserialization (CWE-502) in its model serving component. When starting a model server with the ludwig serve command, the framework loads model weight files using torch.load() without enabling the security-restrictive weights_only=True parameter. This default behavior allows the deserialization of arbitrary Python objects via the pickle module. An attacker can exploit this by providing a maliciously crafted PyTorch model file, leading to arbitrary code execution on the system hosting the Ludwig model server. Affected versions
0.1.0
0.1.1
0.1.2
0.10.0
0.10.1
0.10.2
0.10.3
0.10.4
0.2
0.2.1
0.2.2
0.2.2.2
+ 44 more Show less
0.2.2.3
0.2.2.4
0.2.2.5
0.2.2.6
0.2.2.7
0.2.2.8
0.3
0.3.1
0.3.2
0.3.3
0.4
0.4.1
0.4rc1
0.5
0.5.1
0.5.2
0.5.3
0.5.4
0.5.5
0.5rc1
0.5rc2
0.6
0.6.1
0.6.2
0.6.3
0.6.4
0.7
0.7.1
0.7.2
0.7.3
0.7.4
0.7.5
0.8
0.8.1
0.8.1.post1
0.8.2
0.8.3
0.8.4
0.8.5
0.8.6
0.9
0.9.1
0.9.2
0.9.3
References Updated Jul 01, 2026 · Source: OSV.dev | ||
0.6.2
patch
2 CVEs
CVE-2026-31237
PYSEC-2026-404
GHSA-wcr3-gm9f-f87q
Jun 29, 2026
Ludwig framework is vulnerable to insecure deserialization through its predict() method.
9.8
/ 10
Critical
Network
Low
None
None
Unchanged
High
High
High
The Ludwig framework thru 0.10.4 is vulnerable to insecure deserialization (CWE-502) through its predict() method. When a user provides a dataset file path to the predict() method, the framework automatically determines the file format. If the file is a pickle (.pkl) file, it is loaded using pandas.read_pickle() without any validation or security restrictions. This allows the deserialization of arbitrary Python objects via the unsafe pickle module. A remote attacker can exploit this by providing a maliciously crafted pickle file, leading to arbitrary code execution on the system running the Ludwig prediction. Affected versions
0.1.0
0.1.1
0.1.2
0.10.0
0.10.1
0.10.2
0.10.3
0.10.4
0.2
0.2.1
0.2.2
0.2.2.2
+ 44 more Show less
0.2.2.3
0.2.2.4
0.2.2.5
0.2.2.6
0.2.2.7
0.2.2.8
0.3
0.3.1
0.3.2
0.3.3
0.4
0.4.1
0.4rc1
0.5
0.5.1
0.5.2
0.5.3
0.5.4
0.5.5
0.5rc1
0.5rc2
0.6
0.6.1
0.6.2
0.6.3
0.6.4
0.7
0.7.1
0.7.2
0.7.3
0.7.4
0.7.5
0.8
0.8.1
0.8.1.post1
0.8.2
0.8.3
0.8.4
0.8.5
0.8.6
0.9
0.9.1
0.9.2
0.9.3
References Updated Jul 01, 2026 · Source: OSV.dev
CVE-2026-31238
PYSEC-2026-405
GHSA-xp5q-5q7g-q26r
Jun 29, 2026
Ludwig framework is vulnerable to insecure deserialization in its model serving component
9.8
/ 10
Critical
Network
Low
None
None
Unchanged
High
High
High
The Ludwig framework thru 0.10.4 is vulnerable to insecure deserialization (CWE-502) in its model serving component. When starting a model server with the ludwig serve command, the framework loads model weight files using torch.load() without enabling the security-restrictive weights_only=True parameter. This default behavior allows the deserialization of arbitrary Python objects via the pickle module. An attacker can exploit this by providing a maliciously crafted PyTorch model file, leading to arbitrary code execution on the system hosting the Ludwig model server. Affected versions
0.1.0
0.1.1
0.1.2
0.10.0
0.10.1
0.10.2
0.10.3
0.10.4
0.2
0.2.1
0.2.2
0.2.2.2
+ 44 more Show less
0.2.2.3
0.2.2.4
0.2.2.5
0.2.2.6
0.2.2.7
0.2.2.8
0.3
0.3.1
0.3.2
0.3.3
0.4
0.4.1
0.4rc1
0.5
0.5.1
0.5.2
0.5.3
0.5.4
0.5.5
0.5rc1
0.5rc2
0.6
0.6.1
0.6.2
0.6.3
0.6.4
0.7
0.7.1
0.7.2
0.7.3
0.7.4
0.7.5
0.8
0.8.1
0.8.1.post1
0.8.2
0.8.3
0.8.4
0.8.5
0.8.6
0.9
0.9.1
0.9.2
0.9.3
References Updated Jul 01, 2026 · Source: OSV.dev | ||
0.6.1
patch
2 CVEs
CVE-2026-31237
PYSEC-2026-404
GHSA-wcr3-gm9f-f87q
Jun 29, 2026
Ludwig framework is vulnerable to insecure deserialization through its predict() method.
9.8
/ 10
Critical
Network
Low
None
None
Unchanged
High
High
High
The Ludwig framework thru 0.10.4 is vulnerable to insecure deserialization (CWE-502) through its predict() method. When a user provides a dataset file path to the predict() method, the framework automatically determines the file format. If the file is a pickle (.pkl) file, it is loaded using pandas.read_pickle() without any validation or security restrictions. This allows the deserialization of arbitrary Python objects via the unsafe pickle module. A remote attacker can exploit this by providing a maliciously crafted pickle file, leading to arbitrary code execution on the system running the Ludwig prediction. Affected versions
0.1.0
0.1.1
0.1.2
0.10.0
0.10.1
0.10.2
0.10.3
0.10.4
0.2
0.2.1
0.2.2
0.2.2.2
+ 44 more Show less
0.2.2.3
0.2.2.4
0.2.2.5
0.2.2.6
0.2.2.7
0.2.2.8
0.3
0.3.1
0.3.2
0.3.3
0.4
0.4.1
0.4rc1
0.5
0.5.1
0.5.2
0.5.3
0.5.4
0.5.5
0.5rc1
0.5rc2
0.6
0.6.1
0.6.2
0.6.3
0.6.4
0.7
0.7.1
0.7.2
0.7.3
0.7.4
0.7.5
0.8
0.8.1
0.8.1.post1
0.8.2
0.8.3
0.8.4
0.8.5
0.8.6
0.9
0.9.1
0.9.2
0.9.3
References Updated Jul 01, 2026 · Source: OSV.dev
CVE-2026-31238
PYSEC-2026-405
GHSA-xp5q-5q7g-q26r
Jun 29, 2026
Ludwig framework is vulnerable to insecure deserialization in its model serving component
9.8
/ 10
Critical
Network
Low
None
None
Unchanged
High
High
High
The Ludwig framework thru 0.10.4 is vulnerable to insecure deserialization (CWE-502) in its model serving component. When starting a model server with the ludwig serve command, the framework loads model weight files using torch.load() without enabling the security-restrictive weights_only=True parameter. This default behavior allows the deserialization of arbitrary Python objects via the pickle module. An attacker can exploit this by providing a maliciously crafted PyTorch model file, leading to arbitrary code execution on the system hosting the Ludwig model server. Affected versions
0.1.0
0.1.1
0.1.2
0.10.0
0.10.1
0.10.2
0.10.3
0.10.4
0.2
0.2.1
0.2.2
0.2.2.2
+ 44 more Show less
0.2.2.3
0.2.2.4
0.2.2.5
0.2.2.6
0.2.2.7
0.2.2.8
0.3
0.3.1
0.3.2
0.3.3
0.4
0.4.1
0.4rc1
0.5
0.5.1
0.5.2
0.5.3
0.5.4
0.5.5
0.5rc1
0.5rc2
0.6
0.6.1
0.6.2
0.6.3
0.6.4
0.7
0.7.1
0.7.2
0.7.3
0.7.4
0.7.5
0.8
0.8.1
0.8.1.post1
0.8.2
0.8.3
0.8.4
0.8.5
0.8.6
0.9
0.9.1
0.9.2
0.9.3
References Updated Jul 01, 2026 · Source: OSV.dev |