Ludwig is a low-code framework for building custom LLMs, neural networks, and other AI models

Why it is Amber

• CVSS 8.1 high
• Remotely exploitable without logging in

References

• https://github.com/ludwig-ai/ludwig/commit/7f534f31e725cc5362c8f6f85537488443de279a
• https://github.com/ludwig-ai/ludwig/releases/tag/v0.17.8
• https://github.com/ludwig-ai/ludwig/security/advisories/GHSA-qvrm-3x4c-rcxf

Original description

Ludwig is a low-code framework for building custom LLMs, neural networks, and other AI models. Prior to 0.17.8, ludwig.datasets.archives.extract_archive() validated tar member names before calling TarFile.extractall() but did not validate symlink members or hard-link members. A crafted archive could create a link that escaped the extraction directory and then write a later member through that link, placing attacker-controlled content at an arbitrary filesystem path with the extracting process's privileges. The same containment check used os.path.commonprefix, so a sibling path sharing the destination's character prefix could also pass. The dataset-loading path can download and extract configured archive URLs, but exploitation requires a user to process an archive from a source controlled or compromised by the attacker on supported Python 3.12 and 3.13 runtimes. Python 3.14 is not affected because its default tar data filter rejects escaping links. This issue is fixed in version 0.17.8.