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.

No CVSS v4.0

No CVSS v3.1

Attack Vector Local

Attack Complexity Low

Privileges Required None

Scope Unchanged

Confidentiality Impact None

Integrity Impact None

Availability Impact High

User Interaction Required

No CVSS v2

This CVE is not in the KEV list.

The EPSS score is 0.00128.

Key SSVC decision points have not yet been added.

Default status is the baseline for the product, each version can override it (e.g. patched versions marked unaffected).

Vendor Product Default status Versions
keras-team keras-team/keras affected
Version Status Constraints
unspecified affected < 3.12.3, 3.15.0

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Advisories

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Fixes

Solution

No solution given by the vendor.

Workaround

No workaround given by the vendor.

References
Link Providers
https://github.com/keras-team/keras/commit/4933ea4a5b3fcc24ceacdc276f5bb5dfbd06756c cve-icon
https://huntr.com/bounties/a064f475-780a-409a-82f7-678512f27ad8 cve-icon
History

Mon, 10 Aug 2026 06:45:00 +0000

Type Values Removed Values Added
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.
Title Denial of Service via HDF5 Shape Bomb in keras.models.load_model() in keras-team/keras
Weaknesses CWE-770
References
Metrics cvssV3_0

{'score': 5.5, 'vector': 'CVSS:3.0/AV:L/AC:L/PR:N/UI:R/S:U/C:N/I:N/A:H'}

Projects

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cve-icon MITRE

Status: PUBLISHED

Assigner: @huntr_ai

Published:

Updated: 2026-08-10T06:29:56.111Z

Reserved: 2026-06-18T01:55:25.311Z

Link: CVE-2026-12570

cve-icon Vulnrichment

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cve-icon NVD

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cve-icon Redhat

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cve-icon OpenCVE Enrichment

Updated: 2026-08-10T07:30:14Z

Weaknesses