CVE-2026-115886 json
MLflow: SSRF on unauthenticated MLflow servers via third-party scorer kwargs in the scorer invoke, register, and GenAI evaluate endpoints
published 2026-10-23 16 d ago modified 2026-10-29 10 d ago also BIT-mlflow-2026-115886 , EUVD-2026-109184 , GHSA-2wqp-q3c6-ccj5
- cvss
- 6.5
- version 3.1, CNA
- cisa kev
- Not listed
- not in CISA's catalog
- epss
- 0.7%
- EPSS 0.7% chance of exploitation in 30 days, percentile 52%
- public exploits
- 0
- none known, plus a Nuclei check
Summary
MLflow is an open source AI engineering platform for agents, large language models, and machine learning models. From 3.12.0rc0 until 3.17.0, the scorer invoke, register, and GenAI evaluate endpoints, including unauthenticated POST /ajax-api/3.0/mlflow/scorer/invoke, accept serialized third-party scorer data that Scorer.model_validate_json resolves using a module-path allowlist without constraining the selected class or its constructor arguments. When optional trulens and trulens-providers-litellm packages are installed, an attacker can select mlflow.genai.scorers.trulens, choose a model URI outside MLflow's native provider registry so execution uses the LiteLLM fallback, and supply api_base and api_key values that cause the server to send an outbound request to an attacker-chosen or internal host with attacker-controlled headers and body. The vulnerable deserialization occurs before a tracking-store lookup or job submission. This issue is fixed in version 3.17.0.
Patch / fix
- pypi mlflow 3.17.0
- bitnami mlflow 3.17.0
- lfprojects mlflow 3.17.0
- github.com/mlflow/mlflow@bac30b4 commit
- github.com/mlflow/mlflow#25890 pull request
- github.com/mlflow/mlflow/releases/tag/v3.17.0 release
Vendor advisories
What the vendors themselves say about their products: affected, fixed or not affected, and what to do.
red hat product security vex CVE-2026-115886 updated cvss 6.5
mlflow: mlflow: Server-Side Request Forgery via insecure scorer deserialization
-
Red Hat OpenShift AI (RHOAI) rhoai/odh-mlflow-rhel9, rhoai/odh-th-torch-cpu-py312-rhel9, rhoai/odh-th-torch-cuda-py312-rhel9, rhoai/odh-th-torch-rocm-py312-rhel9, rhoai/odh-th06-cpu-torch210-py312-rhel9, rhoai/odh-th06-rocm64-torch291-py312-rhel9, +16 moreaffected: no fix available “Fix deferred”
Red Hat CSAF VEX © Red Hat, Inc., from https://security.access.redhat.com/data/csaf/v2/vex/; changed: reduced to product statuses and remediations. CC BY 4.0 · csaf
CISA SSVC
- Exploitation
- Proof of concept is public
- Automatable
- yes
- Technical impact
- partial
- Assessed
- 10 d ago
Exploit prediction
0.68% chance of exploitation in the next 30 days, higher than 52% of all scored CVEs (FIRST EPSS, 2026-11-08).
Exploits and checks
- Nuclei template MLflow <3.17.0 - Unauthenticated SSRF via Third-Party (TruLens) Scorer nuclei detection template
- github.com https://github.com/mlflow/mlflow/security/advisories/GHSA-2wqp-q3c6-ccj5 referenced PoC, tagged "exploit" by a source, unverified
CVSS scores
| assigned by | version | score | vector |
|---|---|---|---|
| CNA | 3.1 | 6.5 | CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:L/A:N |
| GitHub | 3.1 | 6.5 | CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:L/A:N |
| OSV | 3.1 | 6.5 | CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:L/A:N |
Affected packages
| ecosystem | package | affected | fixed in |
|---|---|---|---|
| pypi | mlflow | >=3.12.0rc0, <3.17.0 |
3.17.0 |
| bitnami | mlflow | >=3.12.0, <3.17.0 |
3.17.0 |
Affected products
- mlflow mlflow
Classification
References
-
github.com
/mlflow/mlflow/pull/25890
web
-
github.com
/mlflow/mlflow/commit/bac30b4148c4f40045b4d4db07ae60ab3838803f
web
-
github.com
/mlflow/mlflow/security/advisories/GHSA-2wqp-q3c6-ccj5
exploit, web
-
github.com
/mlflow/mlflow/releases/tag/v3.17.0
web
-
github.com
/mlflow/mlflow
package
-
nvd.nist.gov
/vuln/detail/CVE-2026-115886
web
Sources
- CVE List CVE-2026-115886
- GitHub Advisory GHSA-2wqp-q3c6-ccj5
- NVD CVE-2026-115886
- OSV BIT-mlflow-2026-115886
Fencer Vulns keeps one entry per vulnerability: the CVE id wins, then GHSA, and records that alias each other are merged, except that two CVEs always keep separate entries. The same data is available as JSON.
CPEs and fixed versions use Anchore's correction of NVD's data: Added CPE configurations because not yet analyzed by NVD.