CVE-2026-12570
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.
What this means for your business
- An attacker can use it only with access to the machine itself, without a login, but only after tricking someone into an action such as opening a file or a link.
What to do
- 1Ask your IT team or provider whether any of your systems use the affected product.
- 2If you do, follow the vendor's guidance. No patch reference has been published yet.
Not sure if your company is exposed?
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Scoring
- CVSS
- 5.5 (v3.0)
- Vector
CVSS:3.0/AV:L/AC:L/PR:N/UI:R/S:U/C:N/I:N/A:H- Weakness
- CWE-770
- Assigned by
- security@huntr.dev
Dates
- Published
- 2026-08-10
- Last modified
- 2026-09-03
- Sources
- NVD