Deserialization of Untrusted Data Affecting keras package, versions [3.0.0, 3.12.3)[3.13.0, 3.15.0)
Threat Intelligence
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Start learning- Snyk IDSNYK-PYTHON-KERAS-17821216
- published6 Jul 2026
- disclosed3 Jul 2026
- creditTaejin Jang
Introduced: 3 Jul 2026
CVE-2026-12481 (opens in a new tab)How to fix?
Upgrade keras to version 3.12.3, 3.15.0 or higher.
Overview
keras is a Keras is a high-level neural networks API for Python..
Affected versions of this package are vulnerable to Deserialization of Untrusted Data in the deserialization process of the Lambda layer when the safe_mode safeguard is not explicitly enabled. An attacker can execute arbitrary code by tricking a user into loading a specially crafted model file containing malicious serialized data. This is only exploitable if deserialization occurs outside of a SafeModeScope(True) context or if models are loaded from untrusted sources.
Workaround
This vulnerability can be mitigated by only deserializing models from trusted sources and explicitly enabling safe_mode by wrapping deserialization calls within a SafeModeScope(True) context.
Details
Serialization is a process of converting an object into a sequence of bytes which can be persisted to a disk or database or can be sent through streams. The reverse process of creating object from sequence of bytes is called deserialization. Serialization is commonly used for communication (sharing objects between multiple hosts) and persistence (store the object state in a file or a database). It is an integral part of popular protocols like Remote Method Invocation (RMI), Java Management Extension (JMX), Java Messaging System (JMS), Action Message Format (AMF), Java Server Faces (JSF) ViewState, etc.
Deserialization of untrusted data (CWE-502) is when the application deserializes untrusted data without sufficiently verifying that the resulting data will be valid, thus allowing the attacker to control the state or the flow of the execution.