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High

A Server-Side Request Forgery (SSRF) vulnerability exists in MLflow versions prior to 3.9.0. The `_create_webhook()` function in `mlflow/server/handlers.py` accepts a user-controlled `url` parameter w

  • Disclosed: 11.05.2026
  • Updated: 11.10.2026 14:18

A Server-Side Request Forgery (SSRF) vulnerability exists in MLflow versions prior to 3.9.0. The _create_webhook() function in mlflow/server/handlers.py accepts a user-controlled url parameter without validation, and the _send_webhook_request() function in mlflow/webhooks/delivery.py 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.

Affected software

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PlatformPackageVulnerable versionsFixed in
Python (PyPI) mlflow < 3.9.0 3.9.0

References

CVSS score 7.1/10
CVSS vector
CVSS:3.0/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:L/A:N
Weakness (CWE)
CWE-918
Platform
Python (PyPI)
Package
mlflow
Disclosed
11.05.2026
Updated
11.10.2026 14:18

Sources and licenses

OSV / GitHub Advisory Database - GHSA-65h7-c7c4-mghx - CC BY 4.0

OSV / GitHub Advisory Database - PYSEC-2026-2219 - PyPA Advisory Database; CC BY 4.0

Vulnerability history: mlflow

All published vulnerabilities of this package (Python (PyPI)), newest first. Shows whether this is a one-off slip or a package that needs watching.

All (82) in the archive
Total entries
82
First → latest
02.2022 09.2026
Without a fix
18
Exploited in attacks
1

Severity breakdown

  • Critical 20
  • High 48
  • Medium 13
  • Low 1

Disclosures per year

Severity:
  1. MLFLOW_ALLOW_PICKLE_DESERIALIZATION=False safety control bypassed by mlflow.statsmodels flavor — RCE via crafted model artifact
    High · 8.8 ghsa-gqvg-gmmx-x4hm >= 2.1.0, < 3.15.0 3.15.0
  2. MLflow: Unauthenticated full-read SSRF in webhook delivery: _validate_webhook_url bypassed via unvalidated HTTP redirects (and DNS rebinding)
    Critical · 9.3 Exploited in attacks CVE-2026-64849 >= 3.3.0, < 3.15.0 3.15.0
  3. MLflow AI Gateway permits SSRF through an unvalidated api_base
    High · 7.1 CVE-2026-71211 >= 3.13.0, <= 3.15.2 no fix
  4. MLflow: trace API endpoints lack proper authorization validators
    High · 8.1 CVE-2026-8147 >= 2.14.0rc0, < 3.13.0rc0 3.13.0rc0
  5. A vulnerability in mlflow/mlflow versions prior to 3.11.0 allows for the resolution of environment variables in AI Gateway secrets, which can be exploited to exfiltrate sensitive server-side environme
    High · 7.7 CVE-2026-4035 < 3.11.0 3.11.0
  6. MLflow allows unauthorized access to multipart upload endpoints when the `--serve-artifacts` mode is enabled
    Critical · 9.0 CVE-2026-2651 < 3.10.0 3.10.0
  7. MLflow: Improper Origin Validation in MLflow Assistant /ajax-api Endpoints Enables Browser-Mediated Local Command Execution
    Critical · 9.6 CVE-2026-2611 >= 3.9.0, < 3.10.0 3.10.0
  8. MLFlow Creates a Temporary File With Insecure Permissions
    High · 7.0 CVE-2026-4137 >= 1.26.0, < 3.11.0 3.11.0
  9. A vulnerability in mlflow/mlflow versions 3.9.0 and earlier allows unauthenticated access to certain FastAPI routes when the server is started with authentication enabled (`--app-name basic-auth`) and
    High · 8.6 CVE-2026-2652 < 3.10.0 3.10.0
  10. MLflow allows an unauthenticated remote attacker to read arbitrary files from the server's filesystem
    High · 7.5 CVE-2026-2614 < 3.10.0 3.10.0
  11. A Server-Side Request Forgery (SSRF) vulnerability exists in MLflow versions prior to 3.9.0. The `_create_webhook()` function in `mlflow/server/handlers.py` accepts a user-controlled `url` parameter w this entry
    High · 7.1 CVE-2026-2393 < 3.9.0 3.9.0
  12. mlflow: FastAPI job endpoints under `/ajax-api/3.0/jobs/*` are not protected by authentication or authorization
    Critical · 9.1 CVE-2026-0545 <= 3.10.1 no fix
  13. Mlflow: Command Injection when serving models with enable_mlserver=True
    Critical · 9.6 CVE-2026-0596 < 3.9.0 3.9.0
  14. MLflow Command Injection vulnerability
    Critical · 10.0 CVE-2025-15379 < 3.8.1 3.8.1
  15. MLFlow path traversal vulnerability
    Critical · 9.6 CVE-2025-15036 < 3.9.0rc0 3.9.0rc0
  16. MLFlow allows Tracing + Assessments Access
    High · 8.1 CVE-2025-15381 <= 3.8.1 no fix
  17. Arbitrary file write via tar traversal in mlflow
    High · 8.1 CVE-2025-15031 < 3.9.0rc0 3.9.0rc0
  18. MLflow has a command injection in mlflow/sagemaker/__init__.py
    High · 7.5 CVE-2025-14287 < 3.8.0rc0 3.8.0rc0
  19. MLflow Tracking Server Artifact Handler Directory Traversal Remote Code Execution Vulnerability
    High · 8.1 CVE-2026-2033 < 3.8.0rc0 3.8.0rc0
  20. MLflow Use of Default Password Authentication Bypass Vulnerability
    Critical · 9.8 CVE-2026-2635 < 3.8.0rc0 3.8.0rc0
Show more (20) Showing 20 of 68

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