Deserialization of Untrusted Data
CVE-2026-1462
Summary
A vulnerability in the `TFSMLayer` class of the `keras` package, version prior to 3.13.2, 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.
- LOW
- NETWORK
- HIGH
- UNCHANGED
- REQUIRED
- NONE
- HIGH
- HIGH
CWE-502 - Deserialization of Untrusted Data
Deserialization of untrusted data vulnerabilities enable an attacker to replace or manipulate a serialized object, replacing it with malicious data. When the object is deserialized at the victim's end the malicious data is able to compromise the victim’s system. The exploit can be devastating, its impact may range from privilege escalation, broken access control, or denial of service attacks to allowing unauthorized access to the application's internal code and logic which can compromise the entire system.
References
Advisory Timeline
- Published