CVE-2026-1462
A vulnerability in the `TFSMLayer` class of the `keras` package, version 3.13.0, allows attacker-controlled TensorFlow SavedModels to be loaded during deserialization of `.keras` models, even when `safe_mode=True`. This bypasses the security guarantees of `safe_mode` and enables arbitrary attacker-controlled code execution during model inference under the victim's privileges. The issue arises due to the unconditional loading of external SavedModels, serialization of attacker-controlled file paths, and the lack of validation in the `from_config()` method.
취약점 유형
A vulnerability in the `TFSMLayer` class of the `keras` package, version 3.13.0, allows attacker-controlled TensorFlow SavedModels to be loaded during deserialization of `.keras` models, even when `safe_mode=True`. This bypasses the security guarantees of `safe_mode` and enables arbitrary attacker-controlled code execution during model inference under the victim's privileges. The issue arises due to the unconditional loading of external SavedModels, serialization of attacker-controlled file paths, and the lack of validation in the `from_config()` method.
영향받는 제품
- keras keras
- redhat openshift_ai
참고 자료
- https://github.com/keras-team/keras/commit/b6773d3decaef1b05d8e794458e148cb362f163f
- https://huntr.com/bounties/7e78d6f1-6977-4300-b595-e81bdbda331c
- https://access.redhat.com/errata/RHSA-2026:24977
- https://access.redhat.com/errata/RHSA-2026:37275
- https://access.redhat.com/security/cve/CVE-2026-1462
- https://bugzilla.redhat.com/show_bug.cgi?id=2457856
공격자보다 먼저 취약점을 찾으세요.
GitHub로 로그인하고 1분 안에 첫 감사를 실행하세요. 무료 플랜은 신용카드가 필요 없습니다.