Allocation of Resources Without Limits or Throttling Affecting keras package, versions *
Threat Intelligence
The probability is the direct output of the EPSS model, and conveys an overall sense of the threat of exploitation in the wild. The percentile measures the EPSS probability relative to all known EPSS scores. Note: This data is updated daily, relying on the latest available EPSS model version. Check out the EPSS documentation for more details.
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Test your applications- Snyk IDSNYK-DEBIAN11-KERAS-18601995
- published10 Aug 2026
- disclosed10 Aug 2026
Introduced: 10 Aug 2026
NewCVE-2026-12570 (opens in a new tab)How to fix?
There is no fixed version for Debian:11 keras.
NVD Description
Note: Versions mentioned in the description apply only to the upstream keras package and not the keras package as distributed by Debian.
See How to fix? for Debian:11 relevant fixed versions and status.
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.