CVE-2026-10803: Use of Weak Hash in MLflow
A flaw has been found in MLflow up to 3.10.0. This issue affects the function mlflow.data.digest_utils of the file mlflow/data/digest_utils.py of the component Dataset Digest Computation. This manipulation causes use of weak hash. It is possible to launch the attack on the local host. The attack is considered to have high complexity. The exploitability is assessed as difficult. The exploit has been published and may be used. The project was informed of the problem early through a pull request but has not reacted yet.
AI Analysis
Technical Summary
CVE-2026-10803 identifies a weakness in MLflow's dataset digest computation due to the use of a weak hash function in the mlflow.data.digest_utils module. This vulnerability affects all MLflow versions from 3.0 through 3.10.0. The attack requires local access and is considered complex and difficult to exploit. Despite early notification to the project via a pull request, no remediation has been issued. The CVSS 4.0 vector indicates low severity with local attack vector, high attack complexity, and limited impact on confidentiality, integrity, and availability.
Potential Impact
The use of a weak hash function may reduce the cryptographic strength of dataset digest computations, potentially allowing an attacker with local access to manipulate or spoof dataset digests. However, the impact is limited due to the high complexity and difficulty of exploitation, and no known active exploitation has been observed. The vulnerability does not affect cloud services and does not escalate privileges or cause denial of service directly.
Mitigation Recommendations
No official fix or patch is currently available for this vulnerability. Users should monitor the MLflow project for updates or patches addressing this issue. Given the high complexity and local access requirement, immediate risk is low, but applying any future official fixes promptly is recommended once released.
CVE-2026-10803: Use of Weak Hash in MLflow
Description
A flaw has been found in MLflow up to 3.10.0. This issue affects the function mlflow.data.digest_utils of the file mlflow/data/digest_utils.py of the component Dataset Digest Computation. This manipulation causes use of weak hash. It is possible to launch the attack on the local host. The attack is considered to have high complexity. The exploitability is assessed as difficult. The exploit has been published and may be used. The project was informed of the problem early through a pull request but has not reacted yet.
CVSS v4.0
Score 2.0low
AI-Powered Analysis
Machine-generated threat intelligence
Technical Analysis
CVE-2026-10803 identifies a weakness in MLflow's dataset digest computation due to the use of a weak hash function in the mlflow.data.digest_utils module. This vulnerability affects all MLflow versions from 3.0 through 3.10.0. The attack requires local access and is considered complex and difficult to exploit. Despite early notification to the project via a pull request, no remediation has been issued. The CVSS 4.0 vector indicates low severity with local attack vector, high attack complexity, and limited impact on confidentiality, integrity, and availability.
Potential Impact
The use of a weak hash function may reduce the cryptographic strength of dataset digest computations, potentially allowing an attacker with local access to manipulate or spoof dataset digests. However, the impact is limited due to the high complexity and difficulty of exploitation, and no known active exploitation has been observed. The vulnerability does not affect cloud services and does not escalate privileges or cause denial of service directly.
Mitigation Recommendations
No official fix or patch is currently available for this vulnerability. Users should monitor the MLflow project for updates or patches addressing this issue. Given the high complexity and local access requirement, immediate risk is low, but applying any future official fixes promptly is recommended once released.
Technical Details
- Data Version
- 5.2
- Assigner Short Name
- VulDB
- Date Reserved
- 2026-06-04T05:06:53.422Z
- Cvss Version
- 4.0
- State
- PUBLISHED
- Remediation Level
- null
Threat ID: 6a216d2ae29bf47b509f3ad6
Added to database: 6/4/2026, 12:18:50 PM
Last enriched: 6/4/2026, 12:34:06 PM
Last updated: 6/4/2026, 1:42:07 PM
Views: 3
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