Description (CNA)
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.
Affected (CNA)
| Vendor / product | Versions |
|---|---|
| keras-team / keras-team/keras | affected unspecified before 3.14.0 |
CWE
CWE-22
References
- https://huntr.com/bounties/a07e3983-7158-4419-af2b-38f1dea01a4f
- https://github.com/keras-team/keras/commit/2465b6657b02c8eed308759b7e800e295ae01888
ADP enrichment
No English description supplied.
A flaw was found in Keras. Attackers can exploit a path traversal vulnerability in the archive extraction utilities, specifically `filter_safe_tarinfos()` and `filter_safe_zipinfos()`. This occurs because the validation of archive member paths is performed against the process's current working directory (CWD) instead of the actual extraction destination. When the CWD is set to the filesystem root, this allows malicious paths to bypass security checks. Successful exploitation can lead to arbitrary file writes outside the intended directory, potentially enabling attackers to overwrite critical configuration files, inject malicious code, or corrupt machine learning data.