CVE security advisories and vulnerability history for mlflow by PyPI.
Last updated
PyPI mlflow has 23 published CVE records since 2022, of which 0 are in CISA's Known Exploited Vulnerabilities catalog and 14 have a known public exploit. The average CVSS base score across scored CVEs is 7.9.
This page aggregates every publicly disclosed vulnerability (CVE) affecting PyPI mlflow, with a severity breakdown, the affected and patched versions, the most common weakness types, and the full CVE list.
How the CVSS severity of PyPI mlflow's CVEs breaks down, plus how many are exploited in the wild or have public exploit code.
In CISA’s Known Exploited Vulnerabilities catalog
0
None of PyPI mlflow's CVEs are currently listed in CISA's KEV catalog.
Public exploits
14
14 of PyPI mlflow's CVEs have a known public exploit available.
Browse every PyPI mlflow version named in a CVE, then pick one to see only the CVEs that affect it.
23 CVEs
The CWE weakness categories most often found in PyPI mlflow CVEs. Follow any weakness for its full explanation.
How many PyPI mlflow CVEs were published each year.
Browse vulnerabilities for other products by PyPI.
Common questions about PyPI mlflow vulnerabilities.
PyPI mlflow has 23 published CVE records since 2022.
None of PyPI mlflow's CVEs are currently listed in CISA's Known Exploited Vulnerabilities catalog.
Yes — 14 of PyPI mlflow's CVEs have a known public exploit.
178 distinct PyPI mlflow versions are named across its CVEs. Use the version filter above to see the CVEs affecting a specific version.
PyPI mlflow's CVEs most often map to these CWE weakness types: CWE-29 (Path Traversal: '\..\filename'), CWE-22 (Improper Limitation of a Pathname to a Restricted Directory ('Path Traversal')), CWE-79 (Improper Neutralization of Input During Web Page Generation ('Cross-site Scripting')), CWE-36 (Absolute Path Traversal).
PyPI mlflow has 8 critical and 10 high-severity CVEs.
The average CVSS base score across PyPI mlflow's scored CVEs is 7.9.
Vulnerability data is sourced from the CVE Program; severity, KEV, and exploit signals are aggregated by RadicalNotion.AI.
Monitor new PyPI mlflow vulnerabilities as they are disclosed, with AI-written analysis and remediation guidance.
