MLflow: Arbitrary file read on unauthenticated MLflow servers via prompt model version source
CVSS score
7.5
EPSS probability
—
Risk score
0.8
Published
3 h ago
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Vulnerability description
DayBreach AI Explanation
Verified against sourcesSources read
1
Source agreement
Tam uyum
Evidence confidence
%55
Short explanation
A vulnerability in MLflow allows remote arbitrary file reading on unauthenticated servers.
This flaw enables attackers to gain unauthorized access to sensitive files accessible to the MLflow server process.
What should be done?
- Follow vendor advisory guidance
- Update the MLflow installation
Chain of evidence and sources
MLflow 3.10.0 ile 3.17.0 sürümleri arasındaki prompt dalı, şemasız göreceli kaynakları kabul eder.
Varsayılan kimlik doğrulamasız sunucular herhangi bir ayrıcalık gerektirmez.
Show the technical text from the sources
MLflow is an open source AI engineering platform for agents, large language models, and machine learning models. From 3.10.0 until 3.17.0, the prompt branch in _create_model_version() accepts schemeless relative sources because path validation runs only when a source has a URL scheme, and mlflow.prompt.is_prompt is interpreted by tag presence rather than a true value. A remote caller can store a server-local path as the model version artifact location and use /api/2.0/mlflow/model-versions/get-artifact to read files accessible to the MLflow server process. Default unauthenticated servers require no privileges, while basic-auth deployments are exposed to authenticated users who can create registered models. This issue is fixed in version 3.17.0.
CVSS vector: CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:N
CWE: CWE-22
This explanation was compiled automatically from the source records. Scores, active exploitation, patch and exploit status come straight from the sources.
IMPACT: Affected Products and Software
RED HAT CSAF/VEX: Product Impact Check
SCORING: CVSS from Multiple Sources
CVSS Scores
The Common Vulnerability Scoring System is a standardised framework for assessing the severity of vulnerabilities in software and systems. We collect and display CVSS scores from several sources for each CVE.
| SCORE | VERSION | SEVERITY | VECTOR | SOURCE |
|---|---|---|---|---|
| 7.5 | CVSS V31 | HIGH | CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:N | NVD |
| 7.5 | CVSS V3_1 | HIGH | CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:N | CVE CNA |
| 7.5 | CVSS 3.x | — | Vector not published | GitHub Advisory |
| 0.0 | CVSS 4.0 | — | Vector not published | GitHub Advisory |
Patch and Remediation Guide
Solution & Remediation Advisory
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Public exploit and active exploitation status
Verified exploit intelligence
No verified public PoC, exploit repository or Metasploit module has been found for this CVE yet.
Weakness Classification and Attack Patterns (CWE & CAPEC)
CWE - Common Weakness Enumeration
While CVE identifies specific instances of vulnerabilities, CWE categorises the common flaws or weaknesses that can lead to vulnerabilities. CVE-2026-116690 is associated with the following CWEs:
Common Attack Pattern Enumeration and Classification (CAPEC)
Common Attack Pattern Enumeration and Classification (CAPEC) stores attack patterns, which are descriptions of the common attributes and approaches employed by adversaries to exploit the CVE-2026-116690 weaknesses.
Attack Vector and Accessibility
Official Sources and Advisories
Similar Vulnerabilities
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