CVE-2026-10766: Use of Weak Hash in mlrun
A vulnerability has been found in mlrun up to 1.12.0-rc3. This impacts the function mlrun.utils.helpers.calculate_dataframe_hash of the file mlrun/utils/helpers.py of the component DataFrame Hash Handler. The manipulation leads to use of weak hash. The attack can only be performed from a local environment. The complexity of an attack is rather high. The exploitability is said to be difficult. The exploit has been disclosed to the public and may be used. The pull request to fix this issue awaits acceptance.
AI Analysis
Technical Summary
CVE-2026-10766 identifies a vulnerability in mlrun versions 1.12.0-rc1 through 1.12.0-rc3 where the function calculate_dataframe_hash in mlrun.utils.helpers uses a weak hash algorithm. This weakness could potentially allow an attacker with local access to manipulate or predict hash values, though the attack complexity is high and exploitation is difficult. The vulnerability has been publicly disclosed, and a pull request containing a fix is pending acceptance. No official patch or remediation is currently available.
Potential Impact
The vulnerability involves the use of a weak hash function, which may reduce the integrity guarantees of the DataFrame Hash Handler. However, exploitation requires local access and is considered difficult, limiting the practical impact. There are no known exploits in the wild. The overall severity is low according to the CVSS score of 2.0.
Mitigation Recommendations
No official fix or patch is currently available. A pull request to address the issue has been submitted but is not yet merged. Users should monitor the mlrun project for updates and apply the fix once it is officially released. Until then, limiting local access to trusted users can reduce risk.
CVE-2026-10766: Use of Weak Hash in mlrun
Description
A vulnerability has been found in mlrun up to 1.12.0-rc3. This impacts the function mlrun.utils.helpers.calculate_dataframe_hash of the file mlrun/utils/helpers.py of the component DataFrame Hash Handler. The manipulation leads to use of weak hash. The attack can only be performed from a local environment. The complexity of an attack is rather high. The exploitability is said to be difficult. The exploit has been disclosed to the public and may be used. The pull request to fix this issue awaits acceptance.
CVSS v4.0
Score 2.0low
Affected software
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AI-Powered Analysis
Machine-generated threat intelligence
Technical Analysis
CVE-2026-10766 identifies a vulnerability in mlrun versions 1.12.0-rc1 through 1.12.0-rc3 where the function calculate_dataframe_hash in mlrun.utils.helpers uses a weak hash algorithm. This weakness could potentially allow an attacker with local access to manipulate or predict hash values, though the attack complexity is high and exploitation is difficult. The vulnerability has been publicly disclosed, and a pull request containing a fix is pending acceptance. No official patch or remediation is currently available.
Potential Impact
The vulnerability involves the use of a weak hash function, which may reduce the integrity guarantees of the DataFrame Hash Handler. However, exploitation requires local access and is considered difficult, limiting the practical impact. There are no known exploits in the wild. The overall severity is low according to the CVSS score of 2.0.
Mitigation Recommendations
No official fix or patch is currently available. A pull request to address the issue has been submitted but is not yet merged. Users should monitor the mlrun project for updates and apply the fix once it is officially released. Until then, limiting local access to trusted users can reduce risk.
Technical Details
- Data Version
- 5.2
- Assigner Short Name
- VulDB
- Date Reserved
- 2026-06-03T15:40:30.561Z
- Cvss Version
- 4.0
- State
- PUBLISHED
- Remediation Level
- null
Threat ID: 6a208c1fe29bf47b50e773e3
Added to database: 06/03/2026, 20:18:39 UTC
Last enriched: 06/10/2026, 21:00:01 UTC
Last updated: 07/31/2026, 19:22:57 UTC
Views: 49
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