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CVE-2026-0897VulnerabilityPublished Updated

CVE-2026-0897: Google Keras · Unthrottled Resource Allocation

Affects Google KerasSource CVE Database V5

0

Not known to be exploited · CVSS 7.1 High.

Data as of 26 Oct 2026, 06:26 UTC

CVSS 4.0 base score
7.1High
How severe the flaw is on the 0–10 CVSS scale.
EPSS
0.3% chance of exploitation in 30 days – higher than 25% of CVEsExploit Prediction Scoring System: the likelihood attackers will use this flaw soon.
CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:P/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N

Exploitation evidence

  1. Disclosed: evidence found.

    CVE published 15 Jan 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 2026-10-26.

What to do

Affected software

ProductAffectedFixed in
GoogleKerasAffected
  • >=3.0.0 <=3.13.0
Fixed in–
PyPIkeraspkg:pypi/kerasOther threatsAffected
  • =3.0.0
  • <=3.13.0
Fixed in–

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

AI-suggested

Red Hat has published advisories referencing this vulnerability but does not explicitly state that a fix is available. Users should monitor official Google Keras and Red Hat advisories for patches or updates addressing this issue. Until a patch is available, avoid loading untrusted .keras archives containing model.weights.h5 files with potentially large datasets.

Description

Allocation of Resources Without Limits or Throttling in the HDF5 weight loading component in Google Keras 3.0.0 through 3.13.0 on all platforms allows a remote attacker to cause a Denial of Service (DoS) through memory exhaustion and a crash of the Python interpreter via a crafted .keras archive containing a valid model.weights.h5 file whose dataset declares an extremely large shape.

References

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