mlrun: DataFrame hash collisions can cause dataset artifact path conflicts and silent data corruption
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.
This issue can be reached with local access to the system, attack complexity is high, an attacker needs low-level privileges on the target. No user interaction is required. The scope is unchanged, so the impact stays within the vulnerable component. Rated impact: confidentiality none, integrity low, availability low.
The score comes from this vector: CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:L/A:L
CVE-2026-10766 is classified as CWE-327: Use of a Broken or Risky Cryptographic Algorithm. An algorithm with known weaknesses is used, so the protection it appears to give does not hold.
CVE-2026-10766 is recorded against 2 packages.
Published on 23 July 2026. No public exploit is currently recorded for this entry. Record sourced from NVD.
nvd.nist.gov (Advisory)
github.com (Web)
github.com (Web)
github.com (Package)
vuldb.com (Web)
vuldb.com (Web)
vuldb.com (Web)
vuldb.com (Web)
pypi.org (Package)
github.com (Advisory)
These advisories are the same class of weakness (CWE-327: Use of a Broken or Risky Cryptographic Algorithm) in other software:
Details
CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:L/A:L
Affected Packages
| Software | From version | Fixed in |
|---|---|---|
| mlrun | — | — |
| unknown | — | — |
References
Similar Threats
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ⓘ Data Notice: The information presented above has been compiled from publicly available internet sources. Boteraser aggregates this data solely for informational purposes and does not independently classify, evaluate, or endorse any findings about the vulnerabilities listed. The accuracy and completeness of this information is the sole responsibility of the original publishers. Boteraser and its operators accept no liability for any decisions made based on this data.
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