CVE-2024-27133 json
Insufficient sanitization in MLflow leads to XSS when running a recipe that uses an untrusted dataset.
published 2024-02-23 2 y ago modified 2026-09-08 2 mo ago also BIT-mlflow-2024-27133 , EUVD-2024-0494 , GHSA-3v79-q7ph-j75h , PYSEC-2024-241
- cvss
- 7.5
- version 3.1, CNA
- cisa kev
- Not listed
- not in CISA's catalog
- epss
- 0.7%
- EPSS 0.7% chance of exploitation in 30 days, percentile 51%
- public exploits
- 0
- none known
Summary
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.
Patch / fix
- pypi mlflow 2.10.0
- bitnami mlflow 2.10.0
- lfprojects mlflow 2.10.0
- github.com/mlflow/mlflow@c438237 commit
- github.com/mlflow/mlflow@cfa7187 commit
- github.com/mlflow/mlflow#10893 pull request
CISA SSVC
- Exploitation
- Proof of concept is public
- Automatable
- no
- Technical impact
- partial
- Assessed
- 2 y ago
Exploit prediction
0.65% chance of exploitation in the next 30 days, higher than 51% of all scored CVEs (FIRST EPSS, 2026-11-08).
Exploits and checks
- research.jfrog.com https://research.jfrog.com/vulnerabilities/mlflow-untrusted-dataset-xss-jfsa-2024-000631932/ referenced PoC, tagged "exploit" by a source, unverified
CVSS scores
| assigned by | version | score | vector |
|---|---|---|---|
| CNA | 3.1 | 7.5 | CVSS:3.1/AV:N/AC:H/PR:N/UI:R/S:U/C:H/I:H/A:H |
| GitHub | 3.1 | 9.6 | CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:C/C:H/I:H/A:H |
| NVD | 3.1 | 9.6 | CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:C/C:H/I:H/A:H |
| OSV | 3.1 | 9.6 | CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:C/C:H/I:H/A:H |
Affected packages
| ecosystem | package | affected | fixed in |
|---|---|---|---|
| pypi | mlflow | <2.10.0 |
2.10.0 |
| bitnami | mlflow | <2.10.0 |
2.10.0 |
Affected products
- lfprojects mlflow
Classification
- Weakness
-
- CWE-79 Improper Neutralization of Input During Web Page Generation
References
-
github.com
/mlflow/mlflow/pull/10893
web, issue-tracking, patch, report
-
github.com
/mlflow/mlflow/commit/c43823750bffa5b6abcc086683b15a068513b67b
web
-
github.com
/mlflow/mlflow/commit/cfa71879a884cc3520e23ccab998c9aa78fdf2b1
web
-
research.jfrog.com
/vulnerabilities/mlflow-untrusted-dataset-xss-jfsa-2024-000631932/
exploit, third-party-advisory, advisory, evidence, web
-
nvd.nist.gov
/vuln/detail/CVE-2024-27133
advisory, web
-
github.com
/mlflow/mlflow
package
-
github.com
/pypa/advisory-database/tree/main/vulns/mlflow/PYSEC-2024-241.yaml
web
-
research.jfrog.com
/vulnerabilities/mlflow-untrusted-dataset-xss-jfsa-2024-000631932
web
-
github.com
/advisories/GHSA-3v79-q7ph-j75h
web, advisory
Sources
- CVE List CVE-2024-27133
- GitHub Advisory GHSA-3v79-q7ph-j75h
- NVD CVE-2024-27133
- OSV BIT-mlflow-2024-27133
- OSV PYSEC-2024-241
Fencer Vulns keeps one entry per vulnerability: the CVE id wins, then GHSA, and records that alias each other are merged, except that two CVEs always keep separate entries. The same data is available as JSON.
CPEs and fixed versions use Anchore's correction of NVD's data: Added CPE configurations because not yet analyzed by NVD.