CriticalVulnerability

CVE-2025-1550: Keras Model.load_model arbitrary code execution via malicious .keras archive

Source: NVD(opens in a new tab)
Identifier: CVE-2025-1550
Published: March 11, 2025
Record updated: October 9, 2026

Affected: keras >= 3.0.0, < 3.9.0
Fixed in: 3.9.0
released March 4, 2025, 7 days before disclosure
Known exploitation: Not listed in the CISA Known Exploited Vulnerabilities catalog at the last check.
EPSS: 2.6%

Summary

CVE-2025-1550 affects the Keras Model.load_model function. A manually constructed, malicious .keras archive can alter its config.json file to name arbitrary Python modules and functions, with their arguments, which are then loaded and executed during model loading, even when safe_mode=True. Google Inc. is the CNA, rating it CVSS 4.0 7.3 HIGH.

Mitigation

The source does not state a fix yet. Check the original advisory for updates.

Details

Scores and exploitation

CVSS score: 9.8(critical)
Patch available: Yes
EPSS: 2.6%Estimated probability that this CVE is exploited in the next 30 days, from the FIRST Exploit Prediction Scoring System. Read on November 4, 2026.

Weaknesses and techniques

Weakness (CWE): CWE-94
Attack pattern (CAPEC): CAPEC-242

Affected

Packages: keras@>= 3.0.0, < 3.9.0 (fixed: 3.9.0)
Vendors: Google

Classification

Attack type: Other
Attack sophistication: Moderate
AI component targeted: Framework
Impact: Confidentiality,
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-2025-1550

First tracked: February 15, 2026 at 08:42 PM ET, from NVD/CVE Database

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

Classifier confidence: 95% (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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