CVE-2024-37052
MLFlow unsafe deserialization
Deserialization of untrusted data can occur in versions of the MLflow platform running version 1.1.0 or newer, enabling a maliciously uploaded scikit-learn model to run arbitrary code on an end user’s system when interacted with.
Attack profile
How easy it is to exploit
- Attack vector
- Network
- Complexity
- Low
- 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
Deserialization of untrusted data can occur in versions of the MLflow platform running version 1.1.0 or newer, enabling a maliciously uploaded scikit-learn model to run arbitrary code on an end user’s system when interacted with.
- Record
CVE-2024-37052- CVSS 3.1
- 8.8 High
CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H - Weakness
- CWE-502
- Updated
- 2026-11-02
EUVDEUVD-2024-1956
Deserialization of untrusted data can occur in versions of the MLflow platform running version 1.1.0 or newer, enabling a maliciously uploaded scikit-learn model to run arbitrary code on an end user’s system when interacted with.
- Record
EUVD-2024-1956- CVSS 3.1
- 8.8 High
CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H - Updated
- 2026-11-03
GitHub AdvisoriesGHSA-76cg-cfhx-373f
MLFlow unsafe deserialization
Deserialization of untrusted data can occur in versions of the MLflow platform running version 1.1.0 or newer, enabling a maliciously uploaded scikit-learn model to run arbitrary code on an end user’s system when interacted with.
- Record
GHSA-76cg-cfhx-373f- CVSS 3.1
- 8.8 High
CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H - Weakness
- CWE-502
- Updated
- 2026-11-02
NVD
Deserialization of untrusted data can occur in versions of the MLflow platform running version 1.1.0 or newer, enabling a maliciously uploaded scikit-learn model to run arbitrary code on an end user’s system when interacted with.
- Record
CVE-2024-37052- CVSS 3.1
- 8.8 High
CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H - Weakness
- CWE-502
- Updated
- 2026-11-02
OSVGHSA-76cg-cfhx-373f
MLFlow unsafe deserialization
Deserialization of untrusted data can occur in versions of the MLflow platform running version 1.1.0 or newer, enabling a maliciously uploaded scikit-learn model to run arbitrary code on an end user’s system when interacted with.
- Record
GHSA-76cg-cfhx-373f- CVSS 3.1
- 8.8 High
CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H - Weakness
- CWE-502
- Updated
- 2026-11-02
OSVPYSEC-2026-1643
MLFlow unsafe deserialization
Deserialization of untrusted data can occur in versions of the MLflow platform running version 1.1.0 or newer, enabling a maliciously uploaded scikit-learn model to run arbitrary code on an end user’s system when interacted with.
- Record
PYSEC-2026-1643- CVSS 3.1
- 8.8 High
CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H - Updated
- 2026-11-02
OSVBIT-mlflow-2024-37052 No score
Deserialization of untrusted data can occur in versions of the MLflow platform running version 1.1.0 or newer, enabling a maliciously uploaded scikit-learn model to run arbitrary code on an end user’s system when interacted with.
- Record
BIT-mlflow-2024-37052- Updated
- 2026-11-02
Affected products
Affected packages
| Package | Affected | Fixed |
|---|---|---|
mlflowPyPI |
1.1.0 to 2.14.1 | None known |
mlflowBitnami |
1.1.0 up to 2.14.2 | 2.14.2 |
mlflowPyPI |
1.1.0 to 2.14.1, plus listed versions 1.1.1.dev01.10.01.11.01.12.01.12.1 Show 45 moreShow less1.131.13.11.14.01.14.11.15.01.16.01.17.01.18.01.19.01.2.01.20.01.20.11.20.21.21.01.22.01.23.01.23.11.24.01.25.01.25.11.26.01.26.11.27.01.28.01.29.01.3.01.30.01.30.11.4.01.5.01.6.01.7.01.7.11.7.21.8.01.9.01.9.12.0.02.0.0rc02.0.12.1.02.1.12.10.02.10.12.10.2 |
None known |
History
| Recorded | Changed | Sources |
|---|---|---|
| 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-2024-37052 is a high vulnerability (CVSS 8.8) in Lfprojects Mlflow, published June 4, 2024. No source lists public exploit code. EPSS puts the chance of exploitation in the next 30 days at 0.69%, the 52nd percentile. Fixed in mlflow 2.14.2.
References
Left out here: 31 versions. The JSON record has them.