CVE-2026-12481
Description
A flaw was found in the Keras deep learning library. This vulnerability allows a remote attacker to execute arbitrary code on the system by exploiting improper handling of deserialization in the Lambda layer. Specifically, a security safeguard designed to prevent unsafe deserialization is bypassed when the safe_mode setting is not explicitly enabled, allowing malicious code to be processed. This can lead to complete compromise of the affected server or user process.
Statement
This is an Important arbitrary code execution vulnerability in the Keras deep learning library, impacting Red Hat OpenShift AI components. The flaw arises from improper deserialization in the Lambda layer, where a security safeguard is bypassed if safe_mode is not explicitly enabled. Exploitation requires user interaction, such as loading a specially crafted Keras model.
Mitigation
To reduce exposure, only deserialize Keras models from trusted sources. When deserializing models, explicitly enable `safe_mode` by wrapping the deserialization call within a `SafeModeScope(True)` context. This ensures the deserialization safeguard is enforced, preventing the execution of arbitrary code.
Common Vulnerability Scoring System (CVSS) Score Details
Info alert:Important note
CVSS scores for open source components depend on vendor-specific factors (e.g. version or build chain). Therefore, Red Hat's score and impact rating can be different from NVD and other vendors. Red Hat remains the authoritative CVE Naming Authority (CNA) source for its products and services (see Red Hat classifications).
The following CVSS metrics and score provided are preliminary and subject to review.
CVSS v3 Score Breakdown
| Red Hat | NVD | cve.org | |
|---|---|---|---|
| Base Score | 8.8 | 9.8 | 8.8 |
| Attack Vector | Network | Network | Network |
| Attack Complexity | Low | Low | Low |
| Privileges Required | None | None | None |
| User Interaction | Required | None | Required |
| Scope | Unchanged | Unchanged | Unchanged |
| Confidentiality | High | High | High |
| Integrity Impact | High | High | High |
| Availability Impact | High | High | High |
Vector
Red Hat: CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H
NVD: CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H
cve.org: CVSS:3.0/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H
Understanding the Weakness (CWE)
Integrity
Technical Impact: Modify Application Data; Unexpected State
Attackers can modify unexpected objects or data that was assumed to be safe from modification. Deserialized data or code could be modified without using the provided accessor functions, or unexpected functions could be invoked.
Availability
Technical Impact: DoS: Resource Consumption (CPU)
If a function is making an assumption on when to terminate, based on a sentry in a string, it could easily never terminate.
Other
Technical Impact: Varies by Context
The consequences can vary widely, because it depends on which objects or methods are being deserialized, and how they are used. Making an assumption that the code in the deserialized object is valid is dangerous and can enable exploitation. One example is attackers using gadget chains to perform unauthorized actions, such as generating a shell.
Frequently Asked Questions
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