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.
CVSS Details
- CVSS 3.0 Base Score: 5.5
- CVSS 3.0 Vector: (CVSS:3.0/AV:L/AC:L/PR:N/UI:R/S:U/C:N/I:N/A:H)
Prioritise with Active Threat Intelligence
With curated Threat Intelligence, you can see which vulnerabilities truly put you at risk, prioritize what matters most, and act before attackers do.
Explore Intelligence Hub