HighVulnerability

CVE-2025-12060: Keras get_file path traversal via tar archive extraction

Source: NVD(opens in a new tab)
Identifier: CVE-2025-12060
Published: October 30, 2025
Record updated: October 9, 2026

Affected: keras <= 3.11.3
Fixed in: 3.12.0
released October 27, 2025, 3 days before disclosure
Known exploitation: Not listed in the CISA Known Exploited Vulnerabilities catalog at the last check.
EPSS: 0.6%

Summary

The keras.utils.get_file API in Keras, when called with extract=True on tar archives, is vulnerable to path traversal because it uses Python's tarfile.extractall without filter="data". A remote attacker can supply a malicious tar archive with crafted symlinks that, when extracted, writes arbitrary files outside the intended destination folder. The flaw is linked to the underlying Python tarfile weakness CVE-2025-4517.

Mitigation

Upgrading Python to a version that fixes CVE-2025-4517 (e.g. Python 3.13.4) is not enough. Upgrade Keras to a version with the fix (Keras 3.12).

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 November 3, 2026.

Weaknesses and techniques

Weakness (CWE): CWE-22
Attack pattern (CAPEC): CAPEC-126
AI threat technique (MITRE ATLAS): AML.T0010

Affected

Packages: keras@<= 3.11.3 (fixed: 3.12.0)
Vendors: Google

Classification

Attack type: Supply chain
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-2025-12060

First tracked: February 15, 2026 at 08:42 PM 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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