Vulnerability 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.
CVSS Score
MEDIUM
Related Weaknesses (CWE)
References
- https://github.com/keras-team/keras/commit/4933ea4a5b3fcc24ceacdc276f5bb5dfbd067
- https://huntr.com/bounties/a064f475-780a-409a-82f7-678512f27ad8
- https://huntr.com/bounties/a064f475-780a-409a-82f7-678512f27ad8
FAQ
What is CVE-2026-12570?
CVE-2026-12570 is a vulnerability with a CVSS score of 5.5 (MEDIUM). 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._...
How severe is CVE-2026-12570?
CVE-2026-12570 has been rated MEDIUM with a CVSS base score of 5.5/10. Review the CVSS metrics above for detailed severity breakdown.
Is there a patch for CVE-2026-12570?
Check the references section above for vendor advisories and patch information. Review vendor security bulletins for remediation guidance.