CVE-2026-96804
Description
A flaw was found in MLflow. The statsmodel component of MLflow fails to enforce a security control that prevents insecure deserialization during model loading. This allows a remote attacker to execute arbitrary code by submitting a specially crafted MLmodel artifact. This vulnerability can lead to a complete compromise of the affected system.
Statement
This vulnerability is rated as Important rather than Moderate because successful exploitation permits arbitrary code execution within the container workload, though it requires an attacker to supply a malicious model artifact. In Red Hat OpenShift AI environments, MLflow is deployed across workbench images and automated pipelines to manage machine learning lifecycles. The security risk is realized only when a user or automated job processes an untrusted statsmodels artifact, constraining the impact to the privileges of the executing container.
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).
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 | N/A | 8.8 |
| Attack Vector | Network | N/A | Network |
| Attack Complexity | Low | N/A | Low |
| Privileges Required | Low | N/A | Low |
| User Interaction | None | N/A | None |
| Scope | Unchanged | N/A | Unchanged |
| Confidentiality | High | N/A | High |
| Integrity Impact | High | N/A | High |
| Availability Impact | High | N/A | High |
Vector
Red Hat: CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
cve.org: CVSS:3.1/AV:N/AC:L/PR:L/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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