XSS in Lfprojects Mlflow
CVE-2024-27133
Insufficient sanitization in MLflow leads to XSS when running a recipe that uses an untrusted dataset. This issue leads to a client-side RCE when running the recipe in Jupyter Notebook. The vulnerability stems from lack of sanitization over dataset table fields.
Vulnerability class: XSS (Cross-Site Scripting)
Published · last modified .
CVSS v3 metric
CVSS v3 base score 7.5 (High). Vector: CVSS:3.1/AV:N/AC:H/PR:N/UI:R/S:U/C:H/I:H/A:H.
EPSS exploit prediction
EPSS: 0.007 (49.4th percentile), scored .
Very low probability of exploitation in the next 30 days; routine patching cadence is appropriate. 49th percentile — 49.4% of CVEs in the catalogue have a lower EPSS than this one. How to read EPSS.
EPSS over last 30 days · oldest: 0.007 · newest: 0.007 · change: 0.000
Affected products
Weakness classification (CWE)
Public proof-of-concept exploits
References
- research.jfrog.com/vulnerabilities/mlflow-untrusted-dataset-xss-jfsa-2024-00063… (Exploit, Third Party Advisory)
- github.com/mlflow/mlflow/pull/10893 (Patch, Issue Tracking)
Frequently asked questions
- What is CVE-2024-27133?
- CVE-2024-27133 is a high-severity vulnerability in Lfprojects Mlflow, classified under Cross-site Scripting. CVSS score: 7.5/10. Published 2024-02-23.
- How severe is CVE-2024-27133?
- High severity. CVSS v3 base score is 7.5 out of 10.
- Is CVE-2024-27133 known to be exploited?
- 1 public proof-of-concept repositories are indexed. Not currently listed in the CISA KEV catalog.