Critical severityOSV Advisory· Published Feb 23, 2024· Updated Aug 22, 2024
Insufficient sanitization in MLflow leads to XSS when running a recipe that uses an untrusted dataset.
CVE-2024-27133
Description
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.
AI Insight
LLM-synthesized narrative grounded in this CVE's description and references.
Affected packages
Versions sourced from the GitHub Security Advisory.
| Package | Affected versions | Patched versions |
|---|---|---|
mlflowPyPI | < 2.10.0 | 2.10.0 |
Affected products
3- osv-coords2 versions
< 2.10.0+ 1 more
- (no CPE)range: < 2.10.0
- (no CPE)range: < 2.10.0
Patches
Vulnerability mechanics
References
8- github.com/advisories/GHSA-3v79-q7ph-j75hghsaADVISORY
- nvd.nist.gov/vuln/detail/CVE-2024-27133ghsaADVISORY
- github.com/mlflow/mlflow/commit/c43823750bffa5b6abcc086683b15a068513b67bghsaWEB
- github.com/mlflow/mlflow/commit/cfa71879a884cc3520e23ccab998c9aa78fdf2b1ghsaWEB
- github.com/mlflow/mlflow/pull/10893ghsaWEB
- github.com/pypa/advisory-database/tree/main/vulns/mlflow/PYSEC-2024-241.yamlghsaWEB
- research.jfrog.com/vulnerabilities/mlflow-untrusted-dataset-xss-jfsa-2024-000631932ghsaWEB
- research.jfrog.com/vulnerabilities/mlflow-untrusted-dataset-xss-jfsa-2024-000631932/mitre
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