CVE-2026-104103

Ludwig is a low-code framework for building custom LLMs, neural networks, and other AI models. Prior to 0.17.8, ludwig.datasets.archives.extractarchive validated tar member names before calling TarFile.extractall but did not validate symlink members or hard-link members. A crafted archive could...

EUVD-2026-101522

Ludwig is a low-code framework for building custom LLMs, neural networks, and other AI models. Prior to 0.17.8, ludwig.datasets.archives.extractarchive validated tar member names before calling TarFile.extractall but did not validate symlink members or hard-link members. A crafted archive could...

CVE-2026-104103

The Ludwig low-code AI framework (prior to version 0.17.8 ) is vulnerable to a path traversal flaw in the ludwig.datasets.archives.extract_archive() function. The root cause is the failure to validate symlink and hard-link members before calling TarFile.extractall(). An attacker can provide a cra...

CVE-2026-104103 Ludwig: Path traversal in dataset archive extraction allows arbitrary file write via symlink members

Ludwig is a low-code framework for building custom LLMs, neural networks, and other AI models. Prior to 0.17.8, ludwig.datasets.archives.extractarchive validated tar member names before calling TarFile.extractall but did not validate symlink members or hard-link members. A crafted archive could...

Ludwig framework is vulnerable to insecure deserialization through its predict() method.

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...

PYSEC-2026-404 Ludwig framework is vulnerable to insecure deserialization through its predict() method.

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...

Ludwig framework is vulnerable to insecure deserialization in its model serving component

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 weightsonly=True...

PYSEC-2026-405 Ludwig framework is vulnerable to insecure deserialization in its model serving component

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 weightsonly=True...

PT-2026-53488

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...

PT-2026-53487

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...

PT-2026-43664

Improper Limitation of a Pathname to a Restricted Directory 'Path Traversal' vulnerability in Ludwig You QuickWebP Compress / Optimize Images & Convert WebP | SEO Friendly quickwebp allows Path Traversal.This issue affects QuickWebP Compress / Optimize Images & Convert WebP | SEO Friendly: from n...

CVE-2026-31237

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...

CVE-2026-31238

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 weightsonly=True...

Deserialization of Untrusted Data

Overview ludwig is a Declarative machine learning: End-to-end machine learning pipelines using data-driven configurations. Affected versions of this package are vulnerable to Deserialization of Untrusted Data in the model serving process. An attacker can execute arbitrary code on the system by...

Ludwig framework is vulnerable to insecure deserialization in its model serving component

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 weightsonly=True...

Ludwig framework is vulnerable to insecure deserialization through its predict() method.

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...

EUVD-2026-29560

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...

EUVD-2026-29561

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 weightsonly=True...

Deserialization of Untrusted Data

Overview ludwig is a Declarative machine learning: End-to-end machine learning pipelines using data-driven configurations. Affected versions of this package are vulnerable to Deserialization of Untrusted Data via the predict method. An attacker can execute arbitrary code by supplying a maliciousl...

GHSA-WCR3-GM9F-F87Q Ludwig framework is vulnerable to insecure deserialization through its predict() method.

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...