CVE-2025-49655
Description
A unsafe deserialization flaw has been discovered in the Keras framework. An arbitrary code execution vulnerability exists in the TorchModuleWrapper class due to its usage of torch.load() within the from_config method. The method deserializes model data with the weights_only parameter set to False, which causes Torch to fall back on Python’s pickle module for deserialization. Since pickle is known to be unsafe and capable of executing arbitrary code during the deserialization process, a maliciously crafted model file could allow an attacker to execute arbitrary commands.
Statement
Red Hat products in their default configuration do not allow remote upload of model files.
Mitigation
Mitigation for this issue is either not available or the currently available options do not meet the Red Hat Product Security criteria comprising ease of use and deployment, applicability to widespread installation base or stability.
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).
CVSS v3 Score Breakdown
| Red Hat | NVD | cve.org | |
|---|---|---|---|
| Base Score | 8.4 | N/A | N/A |
| Attack Vector | Local | N/A | N/A |
| Attack Complexity | Low | N/A | N/A |
| Privileges Required | None | N/A | N/A |
| User Interaction | None | N/A | N/A |
| Scope | Unchanged | N/A | N/A |
| Confidentiality | High | N/A | N/A |
| Integrity Impact | High | N/A | N/A |
| Availability Impact | High | N/A | N/A |
Vector
Red Hat: CVSS:3.1/AV:L/AC:L/PR:N/UI:N/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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