GHSA-fmxj-6h9g-6vw3 is a critical-severity (CVSS 10) CWE-36 vulnerability in mlflow. 1 public exploit reference exists, so weaponization risk is real. A fix is available for mlflow — see the affected versions and patch details below.
MLflow Path Traversal vulnerability
Exploitation Status
Proof-of-concept exploit code exists
- CISA’s SSVC triage found public proof-of-concept exploit code for this CVE, though no confirmed active exploitation.
- CISA assesses this as automatable — exploitation doesn’t require manual, per-target effort, which raises the odds of mass scanning and opportunistic attacks.
- A successful exploit gives an attacker total control of the affected component, not partial access.
Exploitation and automatability from CISA’s SSVC triage for GHSA-fmxj-6h9g-6vw3.
EPSS Exploitation Probability
EPSS (Exploit Prediction Scoring System) is a daily probability model maintained by FIRST.org. It estimates the likelihood a CVE will be exploited in production environments within the next 30 days, derived from real-world threat intelligence signals.
How urgent is this, really
GHSA-fmxj-6h9g-6vw3 plotted by exploitation likelihood (EPSS) against impact (CVSS). The shaded corner — EPSS 50%+ and CVSS 7.0+ — is where this CVE sits: patch-first territory.
Where this sits among everything scored
Of 377,166 CVEs with a current EPSS score, this one falls in the 50–90% band (highlighted). Real counts from FIRST.org, not a sample — log-scaled since the landscape is heavily right-skewed.
Real-World Exposure
mlflowReal-time download stats are indexed for npm and PyPI packages. This vulnerability affects PyPI packages — download data is not available via public APIs for these ecosystems.
Description
Absolute Path Traversal in GitHub repository mlflow/mlflow prior to 2.5.0.
Affected Packages
| Ecosystem | Package | Vulnerable range | Fix |
|---|---|---|---|
| 🐍PyPI | mlflow | all versions | 2.5.0pip install --upgrade 'mlflow==2.5.0' |
Research use only. For defensive security, authorized penetration testing, and academic research only. Never execute exploit code against systems without explicit written authorization.
Detection & mitigation playbook
Open-source dependencyDetect
Scan your dependency tree (package-lock.json, pnpm-lock.yaml, requirements.txt, go.sum, etc.) for mlflow, including transitive dependencies — a direct dependency you never call can still pull in a vulnerable version.
Fix
Update mlflow to 2.5.0 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms GHSA-fmxj-6h9g-6vw3 is resolved across your whole dependency graph.
Workarounds
If you can't upgrade right away: gate or disable the affected feature, validate untrusted input at the boundary, and avoid passing attacker-controlled data into the vulnerable path. O3's runtime protection blocks exploitation in production as an interim safeguard until the upgrade lands.
How O3 protects you
O3 Security's impact-aware SCA analyses which vulnerable code paths your application actually calls, so a match like GHSA-fmxj-6h9g-6vw3 can be triaged on real exposure rather than presence alone.
Tailored to GHSA-fmxj-6h9g-6vw3. Runtime protection reduces exposure until a permanent patch is applied and verified — it complements patching, it doesn't replace it.
How to detect GHSA-fmxj-6h9g-6vw3
A community-maintained Nuclei template exists for this CVE. You can scan for it directly:
nuclei -id ghsa-fmxj-6h9g-6vw3 -u https://target- Template
- MLflow Absolute Path Traversal
- Severity
- critical
- Impact
- This vulnerability can lead to unauthorized access to sensitive information stored on the server.
- Remediation
- Upgrade to a patched version of MLflow to mitigate the Absolute Path Traversal vulnerability.
Template by ProjectDiscovery nuclei-templates (DhiyaneshDK), MIT licensed. View the full template. Scan only systems you are authorised to test.
Frequently Asked Questions
Is GHSA-fmxj-6h9g-6vw3 in your dependencies?
O3 Security finds GHSA-fmxj-6h9g-6vw3 across PyPI dependencies, including transitive ones, and its impact-aware SCA ranks findings by whether your code actually calls the vulnerable path.