PatchSiren

PatchSiren cyber security CVE debrief

CVE-2026-115886 mlflow CVE debrief

CVE-2026-115886 debrief based on the supplied source corpus. The CVE record was published on 2026-10-23T22:07:26.000Z and has not been modified since then. The vulnerability is a Server-Side Request Forgery (SSRF) in MLflow's unauthenticated tracking servers. An unauthenticated attacker can force the server to make an outbound HTTP request to an arbitrary host, carrying attacker-controlled headers, resulting in a SSRF vulnerability. Defenders should prioritize verifying exposure of unauthenticated MLflow servers, especially those with the optional `trulens` + `trulens-providers-litellm` packages installed, and assess the need for compensating controls or monitoring.

Vendor
mlflow
Product
Unknown
CVSS
MEDIUM 6.5
CISA KEV
Not listed in stored evidence
Original CVE published
2026-10-23
Original CVE updated
2026-10-23
Advisory published
2026-10-23
Advisory updated
2026-10-23

Who should care

Defenders responsible for MLflow deployments, especially those with unauthenticated servers and the optional `trulens` + `trulens-providers-litellm` packages installed, should assess exposure and prioritize verification and remediation efforts.

Why it matters

CVE-2026-115886 is a SSRF vulnerability in MLflow's unauthenticated tracking servers. Defenders should verify exposure, prioritize remediation, and implement compensating controls to prevent potential attacks.

  • Potential for SSRF attacks on unauthenticated MLflow servers
  • Need for verification of exposure and compensating controls
  • Possible data breaches or system compromise
  • Required updates to affected MLflow versions

Technical summary

The MLflow tracking server exposes an unauthenticated `POST /ajax-api/3.0/mlflow/scorer/invoke` endpoint that reflectively instantiates an attacker-named class from attacker-supplied JSON with unconstrained constructor kwargs. With the optional `trulens` + `trulens-providers-litellm` packages installed, an unauthenticated attacker can force the server to make an outbound HTTP request to an arbitrary host, carrying attacker-controlled headers, resulting in a Server-Side Request Forgery (SSRF) vulnerability.

Defensive priority

Defenders should prioritize verifying exposure of unauthenticated MLflow servers, especially those with the optional `trulens` + `trulens-providers-litellm` packages installed, and assess the need for compensating controls or monitoring.

Recommended defensive actions

  • Verify exposure of unauthenticated MLflow servers
  • Assess the need for compensating controls or monitoring
  • Inventory and update affected MLflow versions
  • Implement additional security measures for MLflow deployments
  • Review compensating controls for exposed systems while remediation is scheduled and verified
  • Track exceptions, retest remediated assets, and close the item only after evidence is documented
  • Confirm whether affected product deployments exist in managed environments and assign an owner for follow-up

Evidence notes

The source corpus provides details on the vulnerability in MLflow's tracking server, specifically in the `POST /ajax-api/3.0/mlflow/scorer/invoke` endpoint, which allows for SSRF attacks with attacker-controlled headers when the optional `trulens` + `trulens-providers-litellm` packages are installed.

Sources and references

Verified primary and authoritative sources

  • CVE-2026-115886 CVE Program record

    Publisher, destination, and source semantics verified

    URL: https://www.cve.org/CVERecord?id=CVE-2026-115886

    CVE Program - Official CVE Program record with source-provided CVE metadata.

  • CVE-2026-115886 NVD vulnerability detail

    Publisher, destination, and source semantics verified

    URL: https://nvd.nist.gov/vuln/detail/CVE-2026-115886

    NIST National Vulnerability Database - Official NIST NVD detail page and source-specific vulnerability assessment.

Supplemental references

Methodology and review provenance

AI-assisted synthesis based on stored public vulnerability evidence. System validation, approval state, and publication status do not by themselves establish human review of this revision. PatchSiren helps prioritize defensive review and does not prove exposure or remediation on any system.