keras-team keras up to 3.13.x Archive Extraction file_utils.py filter_safe_tarinfos path traversal

Summaryinfo

A vulnerability has been found in keras-team keras up to 3.13.x and classified as critical. The affected element is the function filter_safe_tarinfos of the file keras/src/utils/file_utils.py of the component Archive Extraction Handler. This manipulation causes path traversal. This vulnerability is tracked as CVE-2026-11816. The attack is possible to be carried out remotely. No exploit exists. The affected component should be upgraded.

Detailsinfo

A vulnerability classified as critical was found in keras-team keras up to 3.13.x. Affected by this vulnerability is the function filter_safe_tarinfos of the file keras/src/utils/file_utils.py of the component Archive Extraction Handler. The manipulation with an unknown input leads to a path traversal vulnerability. The CWE definition for the vulnerability is CWE-22. The product uses external input to construct a pathname that is intended to identify a file or directory that is located underneath a restricted parent directory, but the product does not properly neutralize special elements within the pathname that can cause the pathname to resolve to a location that is outside of the restricted directory. As an impact it is known to affect confidentiality, integrity, and availability. The summary by CVE is:

Keras versions prior to 3.14.0 are vulnerable to a path traversal issue in the archive extraction utilities located in `keras/src/utils/file_utils.py`. The functions `filter_safe_tarinfos()` and `filter_safe_zipinfos()` validate archive member paths against the process current working directory (CWD) instead of the actual extraction destination. When the process runs with CWD set to `/`, which is common in Docker containers, CI/CD runners, and Jupyter environments, the validation boundary becomes the filesystem root, allowing traversal paths to bypass the security check. Additionally, the zip filter contains a bug that causes an `AttributeError` when a blocked entry is encountered, leading to incomplete extraction. Furthermore, Python 3.11 installations lack the `filter="data"` safety net, leaving them entirely reliant on the flawed CWD-based filter. Exploitation of this vulnerability can result in arbitrary file writes outside the intended extraction directory, enabling attackers to overwrite configuration files, inject malicious code, or corrupt machine learning datasets and pipelines.

It is possible to read the advisory at huntr.com. This vulnerability is known as CVE-2026-11816 since 06/09/2026. The exploitation appears to be easy. The attack can be launched remotely. The exploitation doesn't need any form of authentication. It demands that the victim is doing some kind of user interaction. Technical details of the vulnerability are known, but there is no available exploit. The attack technique deployed by this issue is T1006 according to MITRE ATT&CK.

Upgrading to version 3.14.0 eliminates this vulnerability. Applying the patch 2465b6657b02c8eed308759b7e800e295ae01888 is able to eliminate this problem. The bugfix is ready for download at github.com. The best possible mitigation is suggested to be upgrading to the latest version.

The vulnerability is also documented in the vulnerability database at EUVD (EUVD-2026-36244). Statistical analysis made it clear that VulDB provides the best quality for vulnerability data.

Productinfo

Vendor

• keras-team

Name

• keras

Version

• 3.0
• 3.1
• 3.2
• 3.3
• 3.4
• 3.5
• 3.6
• 3.7
• 3.8
• 3.9
• 3.10
• 3.11
• 3.12
• 3.13

License

• open-source

Website

• Product: https://github.com/keras-team/keras/

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Statistical analysis made it clear that VulDB provides the best quality for vulnerability data.

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