Vulnerability · CVE-2026-2393
A Server-Side Request Forgery (SSRF) vulnerability exists in MLflow versions prior to 3.9.0.
Published May 11, 2026 · corrected/updated Jun 17, 2026 · lfprojects mlflow · evidence confidence high
A Server-Side Request Forgery (SSRF) vulnerability exists in MLflow versions prior to 3.9.0. The function in accepts a user-controlled parameter without validation, and the function in sends HTTP POST requests to this attacker-controlled URL. This allows an authenticated attacker to force the MLflow backend to send HTTP requests to internal services, cloud metadata endpoints, or arbitrary external servers. The lack of input sanitization, URL scheme filtering, or allowlist validation on the webhook URL enables exploitation, potentially leading to cloud credential theft, internal network access, and data exfiltration.
Grounded briefings
Catalog interpretations for three audiences. Each brief cites ingested metadata and the original advisories below. They are not independent research and they do not invent exploit steps.
Executive
CVE-2026-2393 is a high public vulnerability record for lfprojects mlflow. It is not currently listed in the CISA Known Exploited catalog. Check the linked vendor or CERT advisories for patch status. This summary is a catalog interpretation of the ingested metadata and cites the original advisories below.
System administrator
Identify whether lfprojects mlflow is in your estate, then compare installed versions with the affected ranges. Affected packages or ranges on record: lfprojects/mlflow. Check the linked vendor or CERT advisories for patch status. Prefer the vendor or distribution advisory linked in Sources before changing production systems. This is a catalog interpretation, not a runbook.
Security analyst
Signals on file: CVSS 7.1, EPSS 0.3%. It is not currently listed in the CISA Known Exploited catalog. Weakness classes: CWE-918. Sources contributing to this record: cve_org, epss, nvd. Public exploit references, when present, are outbound links only and are not proof of active exploitation. This is a catalog interpretation of stored metadata.
Exploitation and remediation
Exploitation evidence
Not listed as known exploited in CISA KEV. Not in CISA KEV or VulnCheck KEV.
Patch and remediation
No required-action text is stored yet. Use the vendor or CERT links in Sources for patch availability.
Safe detection guidance
Compare installed versions with the affected ranges below and verify the advisory from the original publisher. This site stores metadata and outbound links only; it does not ship exploit code or proof-of-concept payloads.
Code
The project this record applies to. Exploit listings stay in References.
Timeline
Detection, updates, and resolution for this record.
May 11, 2026 · NIST NVD
Detected
A Server-Side Request Forgery (SSRF) vulnerability exists in MLflow versions prior to 3.9.0. The function in accepts a user-controlled parameter without validation, and the function in sends HTTP POST requests to this attacker-controlled URL. This allows an authenticated attacker to force the MLflow backend to send HTTP requests to internal services, cloud metadata endpoints, or arbitrary external
Jun 17, 2026 · NIST NVD
Updated
A Server-Side Request Forgery (SSRF) vulnerability exists in MLflow versions prior to 3.9.0. The function in accepts a user-controlled parameter without validation, and the function in sends HTTP POST requests to this attacker-controlled URL. This allows an authenticated attacker to force the MLflow backend to send HTTP requests to internal services, cloud metadata endpoints, or arbitrary external
Affected
- cpe lfprojects/mlflowversion unspecified
Sources
- CVE.orgVulnerability recordCVE-2026-2393
Official CVE identifier
cve.org - FIRST EPSSExploitation probabilityCVE-2026-2393
30-day exploitation probability 0.3%
first.org - NIST NVDVulnerability recordCVE-2026-2393
A Server-Side Request Forgery (SSRF) vulnerability exists in MLflow versions prior to 3.9.0. The function in accepts a user-controlled parameter without validation, and the function in `mlflow/webhook
nvd.nist.gov