Keras has a Local File Disclosure via HDF5 External Storage During Keras Weight Loading
CVE-2026-1669GHSA-3m4q-jmj6-r34q
What to do
Vendor fix available. Upgrade each affected package to the fixed version on its release line (keras 3.13.2, 3.12.1), redeploy, then verify what is actually installed.
This page has no inventory attached, so it cannot say whether you are affected. A vendor fix is not proof that your deployment is fixed.
Affected packages
PyPI keras
- Affected
- >= 3.13.0, < 3.13.2>= 3.0.0, < 3.12.1
- Fixed in
- 3.13.2, 3.12.1
Sources
- Open Source Vulnerabilities (OSV.dev), including the GitHub Advisory Database
OSV record GHSA-3m4q-jmj6-r34q lists affected ranges: PyPI keras >=3.13.0 =3.0.0 <3.12.1 (fixed)
VerifiedObserved Structured OSV record; GitHub-reviewed advisory.
- GitHub Advisory Database and maintainer security advisories on GitHub
GitHub-reviewed advisory GHSA-3m4q-jmj6-r34q lists affected ranges: PyPI keras >=3.13.0 =3.0.0 <3.12.1
VerifiedObserved Structured GitHub Advisory Database record (type=reviewed) from the GitHub REST API.
Severity and exploitation
- Exploitation
- No confirmed exploitation recorded. Patch Next marks exploitation only from CISA KEV.
- CVSS
- 7.1 · CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:L/A:N
- EPSS
- CVE-2026-1669: 0.33% estimated exploitation activity in the next 30 days; percentile 26.75 (FIRST EPSS, 2026-11-03). This is a model estimate, not proof of exploitation or customer exposure.
Source description
As published by the source; long descriptions are shortened.
Summary TensorFlow / Keras continues to honor HDF5 “external storage” and ExternalLink features when loading weights. A malicious .weights.h5 (or a .keras archive embedding such weights) can direct loadweights() to read from an arbitrary readable filesystem path. The bytes pulled from that path populate model tensors and become observable through inference or subsequent re-save operations. Keras “safe mode” only guards object deserialization and does not cover weight I/O, so this behaviour persists even with safe mode enabled. The issue is confirmed on the latest publicly released stack (tensorflow 2.20.0, keras 3.11.3, h5py 3.15.1, numpy 2.3.4). Impact - Class: CWE-200 (Exposure of Sensitive Information), CWE-73 (External Control of File Name or Path) - What leaks: Contents of any readable file on the host (e.g., /etc/hosts, /etc/passwd, /etc/hostname). - Visibility: Secrets appear in model outputs (e.g., Dense layer bias) or get embedded into newly saved artifacts. - Prerequisites:…
Dates and revisions
- Published by the source
- Last modified by the source
- Source last checked
- Revision 2 · amended ·
Amended from ghsa record GHSA-3m4q-jmj6-r34q
- Revision 1 · created ·
Published from osv record GHSA-3m4q-jmj6-r34q
Agent brief
Preview the exact text before you copy it. Commands are read-only suggestions; review them before running anything.
# Patch Next advisory brief: CVE-2026-1669 Advisory: Keras has a Local File Disclosure via HDF5 External Storage During Keras Weight Loading IDs: CVE-2026-1669, GHSA-3m4q-jmj6-r34q Record: https://patchnext.com/advisories/cve-2026-1669 (revision 2, source checked 26 Oct 2026, 13:36 UTC) Inventory: none attached. This brief comes from a public page and does not say whether any deployment is affected. Severity: High (CVSS 7.1) Exploitation: no confirmed exploitation recorded. Patch Next confirms exploitation only from CISA KEV. Vendor response: Vendor fix available; fixed versions by package: keras 3.13.2, 3.12.1. A vendor fix does not mean a deployment is fixed. ## Affected components - PyPI keras: affected >= 3.13.0, < 3.13.2; >= 3.0.0, < 3.12.1; fixed in 3.13.2, 3.12.1 ## Suggested inspection (read-only) - `python -m pip show keras`: prints the installed version. Run with the environment that serves production active. ## Supported action Upgrade each affected component to a fixed version on its release line. For a transitive dependency, upgrade the parent package or add an override or constraint, then regenerate the lockfile. Redeploy every environment that ran an affected version. ## Required regression checks - Run the test suite and a production build. - Exercise the features that depend on keras. - Repeat the inspection and confirm that only fixed versions remain installed. ## Rollback considerations - Keep the previous lockfile and deployment artifact. Rolling back reinstates the vulnerable version, so apply any documented mitigation while you fix forward. ## Unresolved questions - Which deployments run an affected version? - Exploitation status can change. Check again before lowering the priority. - Mark the work resolved only after the fixed version is verified in production. ## Sources - Verified: https://osv.dev/vulnerability/GHSA-3m4q-jmj6-r34q (OSV record GHSA-3m4q-jmj6-r34q lists affected ranges: PyPI keras >=3.13.0 =3.0.0 <3.12.1 (fixed)) - Verified: https://github.com/advisories/GHSA-3m4q-jmj6-r34q (GitHub-reviewed advisory GHSA-3m4q-jmj6-r34q lists affected ranges: PyPI keras >=3.13.0 =3.0.0 <3.12.1) Commands are suggestions: review each one before running it.
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