CVE-2026-11816
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.
Schwachstellenklasse
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.
Betroffene Produkte
- keras keras
Quellen
- https://github.com/keras-team/keras/commit/2465b6657b02c8eed308759b7e800e295ae01888
- https://huntr.com/bounties/a07e3983-7158-4419-af2b-38f1dea01a4f
- https://access.redhat.com/errata/RHSA-2026:42644
- https://access.redhat.com/security/cve/CVE-2026-11816
- https://bugzilla.redhat.com/show_bug.cgi?id=2487912
- https://huntr.com/bounties/a07e3983-7158-4419-af2b-38f1dea01a4f
Finden Sie die Schwachstelle, bevor es ein Angreifer tut.
Melden Sie sich mit GitHub an und starten Sie Ihr erstes Audit in weniger als einer Minute. Für den kostenlosen Plan ist keine Kreditkarte nötig.