HighVulnerability

CVE-2026-11816: Keras path traversal in archive extraction utilities

Source: NVD(opens in a new tab)
Identifier: CVE-2026-11816
Published: June 11, 2026
Record updated: October 9, 2026

Affected: keras < 3.14.0
Fixed in: 3.14.0
Known exploitation: Not listed in the CISA Known Exploited Vulnerabilities catalog at the last check.
EPSS: 0.6%

Summary

Keras versions prior to 3.14.0 contain a path traversal flaw in the archive extraction utilities in `keras/src/utils/file_utils.py`. The functions `filter_safe_tarinfos()` and `filter_safe_zipinfos()` check archive member paths against the process current working directory instead of the extraction destination, so when the working directory is `/`, as is common in Docker containers, CI/CD runners and Jupyter environments, traversal paths bypass the check. An attacker can cause arbitrary file writes outside the extraction directory, enabling overwrites of configuration files, malicious code injection or corruption of machine learning datasets and pipelines.

Mitigation

Fixed in 3.14.0.

Details

Scores and exploitation

Patch available: Yes
EPSS: 0.6%Estimated probability that this CVE is exploited in the next 30 days, from the FIRST Exploit Prediction Scoring System. Read on October 26, 2026.
Disclosure date: June 11, 2026

Weaknesses and techniques

Weakness (CWE): CWE-22
Attack pattern (CAPEC): CAPEC-126

Affected

Packages: keras@< 3.14.0 (fixed: 3.14.0)
Vendors: Google

Classification

Attack type: Other
Attack sophistication: Moderate
AI component targeted: Framework
Impact: Integrity,
Availability
Labels: security

How this record was produced

Summaries, mitigations and labels on this page are generated automatically from the source. The linked source is authoritative. The source gives this advisory a description and no title, so the title above is a headline generated from the source text.

Original source: https://nvd.nist.gov/vuln/detail/CVE-2026-11816

First tracked: June 12, 2026 at 08:08 AM ET, from NVD/CVE Database

Classifier: claude-haiku-5-5, prompt v4

Classifier confidence: 90% (self-assessed)

Affected packages in the Exposure Registry

Matched by package name and ecosystem. Each entry shows whether the package delegates to a language model and how many tracked packages depend on it.

kerasPyPINo LLM dependency detected · 6 tracked dependents

Summary

Mitigation

Affected packages in the Exposure Registry

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