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VulnerabilityPublished Updated

CVE-2026-12570: Keras model loading is vulnerable to denial of service through HDF5 shape bombs

Affects kerasSource GCVE Database

0

Mentioned vulnerabilities

Authoritative record:CVE-2026-12570· Medium 5.5

Not known to be exploited · CVSS 5.5 Medium : upgrade to 3.15.0 when convenient.

Data as of 26 Oct 2026, 17:16 UTC

CVSS 3.0 base score
5.5Medium
How severe the flaw is on the 0–10 CVSS scale.
EPSS
0.1% chance of exploitation in 30 days – higher than 8% of CVEsExploit Prediction Scoring System: the likelihood attackers will use this flaw soon.
Patch
Available – fixed in 3.15.0
CVSS:3.0/AV:L/AC:L/PR:N/UI:R/S:U/C:N/I:N/A:H

Exploitation evidence

  1. Disclosed: evidence found.

    CVE published 10 Aug 2026

  2. Detectable: no evidence on record.

    No public nuclei template indexed

  3. Weaponised: no evidence on record.

    No public exploit code indexed in Metasploit or Exploit-DB

  4. Exploited in the wild: no evidence on record.

    Not in CISA KEV and no source reports exploitation

  5. Observed by OffSeq Mirage: no evidence on record.

    No attack traffic recorded by OffSeq Mirage sensors

A missing step is not evidence of safety. Sources: cve.org (opens in a new tab), the Metasploit, Exploit-DB and nuclei-templates index as of 26 Oct 2026.

What to do

Upgrade keras to 3.15.0.

Affected software

ProductAffectedFixed in
PyPIkerasAffected
  • <3.15.0
Fixed in
  • 3.15.0

Check your own hosts for these packages with threat-finder (opens in a new tab), our free open-source scanner.

Description

A vulnerability in keras-team/keras versions < 3.15.0 allows for a denial of service (DoS) attack when loading malicious .keras model files via the keras.models.load_model() function. The H5IOStore.__getitem__ method in keras/src/saving/saving_lib.py does not validate the shape or size of datasets, leading to unbounded memory allocation. A specially crafted .keras file can exploit this flaw to trigger an out-of-memory (OOM) condition, causing the process to be terminated (exit code 137). This issue bypasses the fix for CVE-2026-0897, which only addressed a similar vulnerability in KerasFileEditor. The attack vector includes poisoned models from public repositories or malicious model registries, posing a risk to machine learning pipelines that process untrusted models.

References

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