CVE-2026-33865
Description
A flaw was found in MLflow, a platform for managing the machine learning lifecycle. This Stored Cross-Site Scripting (XSS) vulnerability, a type of injection where malicious scripts are injected into trusted websites, is caused by the unsafe parsing of YAML-based MLmodel artifacts in its web interface. An authenticated attacker can exploit this by uploading a malicious MLmodel file containing a payload. When another user views this artifact in the user interface, the payload executes, potentially leading to session hijacking or unauthorized operations on behalf of the victim.
Statement
Moderate: This Stored Cross-Site Scripting (XSS) flaw in MLflow, as deployed in Red Hat OpenShift AI, stems from insecure parsing of YAML-based MLmodel artifacts in its web interface. An authenticated attacker can upload a malicious MLmodel file; subsequent viewing by another user executes the payload, potentially leading to session hijacking or unauthorized actions within the victim's session.
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 | 4.6 | 5.4 | N/A |
| Attack Vector | Network | Network | N/A |
| Attack Complexity | Low | Low | N/A |
| Privileges Required | Low | Low | N/A |
| User Interaction | Required | Required | N/A |
| Scope | Unchanged | Changed | N/A |
| Confidentiality | Low | Low | N/A |
| Integrity Impact | Low | Low | N/A |
| Availability Impact | None | None | N/A |
Vector
Red Hat: CVSS:3.1/AV:N/AC:L/PR:L/UI:R/S:U/C:L/I:L/A:N
NVD: CVSS:3.1/AV:N/AC:L/PR:L/UI:R/S:C/C:L/I:L/A:N
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
Not sure what something means? Check out our Security Glossary.
Want to get errata notifications? Sign up here.
