CVE-2024-27133
Insufficient sanitization in MLflow leads to XSS when running a recipe that uses an untrusted dataset.
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.
Attack profile
How easy it is to exploit
- Attack vector
- Network
- Complexity
- High
- Privileges needed
- None
- User interaction
- Required
What an attacker can affect
- Confidentiality
- High
- Integrity
- High
- Availability
- High
Exploit likelihood
What each source reports
CVE List Score used
Insufficient sanitization in MLflow leads to XSS when running a recipe that uses an untrusted dataset.
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.
- Record
CVE-2024-27133- CVSS 3.1
- 7.5 High
CVSS:3.1/AV:N/AC:H/PR:N/UI:R/S:U/C:H/I:H/A:H - Weakness
- CWE-79
- Updated
- 2026-11-02
EUVDEUVD-2024-0494
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.
- Record
EUVD-2024-0494- CVSS 3.1
- 7.5 High
CVSS:3.1/AV:N/AC:H/PR:N/UI:R/S:U/C:H/I:H/A:H - Updated
- 2026-11-03
GitHub AdvisoriesGHSA-3v79-q7ph-j75h
MLFlow Cross-site Scripting vulnerability leads to client-side Remote Code Execution
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.
- Record
GHSA-3v79-q7ph-j75h- CVSS 3.1
- 9.6 Critical
CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:C/C:H/I:H/A:H - Weakness
- CWE-79
- Updated
- 2026-11-02
NVD
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.
- Record
CVE-2024-27133- CVSS 3.1
- 7.5 High
CVSS:3.1/AV:N/AC:H/PR:N/UI:R/S:U/C:H/I:H/A:H - CVSS 3.1
- 9.6 Critical
CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:C/C:H/I:H/A:H - Weakness
- CWE-79
- Updated
- 2026-11-02
OSV
Insufficient sanitization in MLflow leads to XSS when running a recipe that uses an untrusted dataset.
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.
- Record
CVE-2024-27133- CVSS 3.1
- 7.5 High
CVSS:3.1/AV:N/AC:H/PR:N/UI:R/S:U/C:H/I:H/A:H - Weakness
- CWE-79
- Updated
- 2026-11-02
OSVGHSA-3v79-q7ph-j75h
MLFlow Cross-site Scripting vulnerability leads to client-side Remote Code Execution
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.
- Record
GHSA-3v79-q7ph-j75h- CVSS 3.1
- 9.6 Critical
CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:C/C:H/I:H/A:H - Weakness
- CWE-79
- Updated
- 2026-11-02
OSVPYSEC-2024-241
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.
- Record
PYSEC-2024-241- CVSS 3.1
- 9.6 Critical
CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:C/C:H/I:H/A:H - Updated
- 2026-11-02
OSVBIT-mlflow-2024-27133 No score
Insufficient sanitization in MLflow leads to XSS when running a recipe that uses an untrusted dataset.
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.
- Record
BIT-mlflow-2024-27133- Updated
- 2026-11-02
OSVCLSA-2026-1775781174 No score
TuxCare security update for mlflow (14 CVEs)
TuxCare rebuilt mlflow to address 14 CVEs. Fixed in 2.9.1.post2+tuxcare.
- Record
CLSA-2026-1775781174- Updated
- 2026-11-02
Affected products
Affected packages
| Package | Affected | Fixed |
|---|---|---|
mlflowPyPI |
before 2.10.0 | 2.10.0 |
mlflowBitnami |
before 2.10.0 | 2.10.0 |
mlflowTuxCare:PyPI From an advisory covering 14 CVEs |
2.9.1 up to 2.9.1.post2+tuxcare, plus listed versions 2.9.1.post1+tuxcare |
2.9.1.post2+tuxcare |
mlflowPyPI |
before 2.10.0, plus listed versions 0.0.10.1.00.2.00.2.10.3.0 Show 45 moreShow less0.4.00.4.10.4.20.5.00.5.10.5.20.6.00.7.00.8.00.8.10.8.20.9.00.9.0.10.9.11.0.01.1.01.1.1.dev01.10.01.11.01.12.01.12.11.131.13.11.14.01.14.11.15.01.16.01.17.01.18.01.19.01.2.01.20.01.20.11.20.21.21.01.22.01.23.01.23.11.24.01.25.01.25.11.26.01.26.11.27.01.28.0 |
2.10.0 |
History
| Recorded | Changed | Sources |
|---|---|---|
| affected, facts | ||
| aliases, published | EUVD | |
| first indexed | CVE List, GitHub Advisories, NVD, OSV |
Dates are when Every CVE recorded each change. Upstream dates may differ.
In short
CVE-2024-27133 is a high vulnerability (CVSS 7.5) in Lfprojects Mlflow, published February 23, 2024. No source lists public exploit code. EPSS puts the chance of exploitation in the next 30 days at 0.65%, the 51st percentile. Fixed in mlflow 2.10.0.
References
research.jfrog.com/vulnerabilities/mlflow-untrusted-dataset-xss-jfsa-2024-000631932
github.com/mlflow/mlflow/pull/10893
nvd.nist.gov/vuln/detail/CVE-2024-27133
Left out here: 36 versions. The JSON record has them.