HighVulnerability

CVE-2025-8747: Keras safe mode bypass in Model.load_model via crafted .keras archive

Source: NVD(opens in a new tab)
Identifier: CVE-2025-8747
Published: August 11, 2025
Record updated: October 9, 2026

Affected: keras >= 3.0.0, < 3.11.0
Fixed in: 3.11.0
released July 29, 2025, 12 days before disclosure
Known exploitation: Not listed in the CISA Known Exploited Vulnerabilities catalog at the last check.
EPSS: 0.1%

Summary

CVE-2025-8747 is a safe mode bypass in the `Model.load_model` method in Keras versions 3.0.0 through 3.10.0. An attacker who convinces a user to load a specially crafted `.keras` model archive can achieve arbitrary code execution. Google Inc. is the CNA, rating it CVSS-B 8.6 HIGH under CVSS 4.0, with CWE-502 (Deserialization of Untrusted Data).

Mitigation

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

Details

Scores and exploitation

CVSS score: 7.8(high)
Patch available: Yes
EPSS: 0.1%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-502
Attack pattern (CAPEC): CAPEC-586

Affected

Packages: keras@>= 3.0.0, < 3.11.0 (fixed: 3.11.0)
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-2025-8747

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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