Deserialization of untrusted data can occur in versions of the MLflow platform running version 1.24.0 or newer, enabling a maliciously uploaded… (CVE-2024-37055)
A deserialization vulnerability exists in MLflow platform versions 1.24.0 and newer up to but not including 2.14.2. This flaw allows a maliciously crafted pmdarima model uploaded to the platform to execute arbitrary code on an end user’s system when the model is interacted with. The vulnerability is classified as high severity. A patch is available to remediate this issue.
AI Analysis
Technical Summary
The MLflow platform suffers from a deserialization of untrusted data vulnerability in versions >=1.24.0 and <2.14.2. This vulnerability enables an attacker to upload a malicious pmdarima model that, when deserialized by the platform, can execute arbitrary code on the system of the user interacting with the model. This can lead to remote code execution and compromise of the affected system. The vulnerability has been assigned CVE-2024-37055 and is recognized as high severity. A patch is available to fix this issue.
Potential Impact
Successful exploitation allows arbitrary code execution on the end user’s system through deserialization of a maliciously crafted pmdarima model. This can lead to full system compromise depending on the privileges of the user running the MLflow platform.
Mitigation Recommendations
A patch is available for this vulnerability. Users should upgrade MLflow to version 2.14.2 or later to remediate this issue. No additional mitigation steps are indicated beyond applying the official fix.
Deserialization of untrusted data can occur in versions of the MLflow platform running version 1.24.0 or newer, enabling a maliciously uploaded… (CVE-2024-37055)
Description
A deserialization vulnerability exists in MLflow platform versions 1.24.0 and newer up to but not including 2.14.2. This flaw allows a maliciously crafted pmdarima model uploaded to the platform to execute arbitrary code on an end user’s system when the model is interacted with. The vulnerability is classified as high severity. A patch is available to remediate this issue.
Affected software
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AI-Powered Analysis
Machine-generated threat intelligence
Technical Analysis
The MLflow platform suffers from a deserialization of untrusted data vulnerability in versions >=1.24.0 and <2.14.2. This vulnerability enables an attacker to upload a malicious pmdarima model that, when deserialized by the platform, can execute arbitrary code on the system of the user interacting with the model. This can lead to remote code execution and compromise of the affected system. The vulnerability has been assigned CVE-2024-37055 and is recognized as high severity. A patch is available to fix this issue.
Potential Impact
Successful exploitation allows arbitrary code execution on the end user’s system through deserialization of a maliciously crafted pmdarima model. This can lead to full system compromise depending on the privileges of the user running the MLflow platform.
Mitigation Recommendations
A patch is available for this vulnerability. Users should upgrade MLflow to version 2.14.2 or later to remediate this issue. No additional mitigation steps are indicated beyond applying the official fix.
Technical Details
- Gcve Source
- db.gcve.eu
- Osv Id
- BIT-mlflow-2024-37055
- Osv Schema Version
- 1.5.0
- Aliases
- ["CVE-2024-37055"]
- Ecosystems
- ["Bitnami"]
- Database Specific Severity
- High
Threat ID: 6a885f2facd9273b493f8312
Added to database: 08/21/2026, 14:22:39 UTC
Last enriched: 08/21/2026, 14:41:54 UTC
Last updated: 09/10/2026, 19:36:48 UTC
Views: 20
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