HighVulnerability

GHSA-mgx6-5cf9-rr43: Keras vulnerable to DoS via Malicious .keras Model (HDF5 Shape Bomb Causes Petabyte Allocation in KerasFileEditor)

Source: GitHub Advisory(opens in a new tab)
Identifiers: CVE-2026-0897GHSA-mgx6-5cf9-rr43
Published: May 6, 2026
Record updated: October 9, 2026

Affected: keras >= 3.13.0, < 3.13.2, fixed in 3.13.2, released January 29, 2026, 96 days before disclosure
keras >= 3.0.0, <= 3.12.0, fixed in 3.12.1, released January 30, 2026, 96 days before disclosure
Known exploitation: Not listed in the CISA Known Exploited Vulnerabilities catalog at the last check.
EPSS: 0.3%

Summary

The Keras model loader, KerasFileEditor, reads HDF5 weight files inside user-supplied .keras archives without validating dataset metadata. A crafted model.weights.h5 declaring a dataset shape of (50000000, 50000000) with only a few bytes of stored data triggers a full-shape allocation via value[()] in h5py, producing an attempted 8.88 PiB allocation that crashes the process. The advisory describes the impact as denial of service for any environment or pipeline that loads untrusted .keras models.

Mitigation

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

Details

Scores and exploitation

Patch available: Yes
EPSS: 0.3%Estimated probability that this CVE is exploited in the next 30 days, from the FIRST Exploit Prediction Scoring System. Read on November 12, 2026.
Disclosure date: May 6, 2026

Affected

Packages: keras@>= 3.13.0, < 3.13.2 (fixed: 3.13.2)
keras@>= 3.0.0, <= 3.12.0 (fixed: 3.12.1)
Vendors: Google

Classification

Attack type: Denial of service
Attack sophistication: Trivial
AI component targeted: Framework
Impact: 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.

Original source: https://github.com/advisories/GHSA-mgx6-5cf9-rr43

First tracked: May 6, 2026 at 08:00 PM ET, from GitHub Advisory 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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