CVE-2026-10766: mlrun DataFrame Hash Collisions Can Cause Vulnerability

LOW
Advisory Identifier: GHSA-phx2-3w66-h4pw
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CVSS 3.6
CWE-327
Published
Advisory Summary

CVE-2026-10766 is a LOW (CVSS 3.6) dataframe hash collisions can cause vulnerability (CWE-327: Use of a Broken or Risky Cryptographic Algorithm) affecting mlrun libraries in the PyPI ecosystem. The issue involves dataframe hash collisions can cause dataset artifact path conflicts and silent data corruption. Remediation is available in the latest vendor maintenance releases.

CVE-2026-10766 at a Glance

CVE Identifier CVE-2026-10766
GHSA Identifier GHSA-phx2-3w66-h4pw
Severity LOW
CVSS v3.1 Base Score 3.6
CWE Classification CWE-327: Use of a Broken or Risky Cryptographic Algorithm
Affected Product mlrun
Package Ecosystem PyPI
Published Date
Last Updated

Security Impact

CVSS: 3.6

The security impact metrics below are parsed directly from the CVSS v3.1 vector string (CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:L/A:L).

Attack Vector Local (AV:L)
Attack Complexity High (AC:H)
Privileges Required Low (PR:L)
User Interaction None (UI:N)
Scope Unchanged (S:U)
Confidentiality None (C:N)
Integrity Low (I:L)
Availability Low (A:L)

How to Fix CVE-2026-10766

To remediate this vulnerability, upgrade all affected mlrun dependencies to a patched release. Both direct and transitive dependencies should be checked, as frameworks or security libraries may pull in vulnerable versions transitively.

mlrun fixed: Latest secure release 
pip install mlrun>=Latest secure release
Verify Direct and Transitive Dependencies

Run the following command in your project directory to verify that all resolved dependencies use the patched release: 

pip show mlrun

How to Check if You Are Affected

To determine whether your Python environment is affected by CVE-2026-10766, inspect your installed packages using pip:

pip show mlrun

Analyze the terminal output to locate any version of mlrun in your dependency tree. If any resolved version matches the vulnerable ranges listed in the table below (for example, versions earlier than the patched release), your application is affected.

Note: The pip show mlrun command checks currently installed packages in your active Python environment.

Technical Details

Vulnerability Mechanism & Technical Analysis

This vulnerability is classified under CWE-327: Use of a Broken or Risky Cryptographic Algorithm, where the product uses a broken or risky cryptographic algorithm or protocol. In mlrun, software state validation or input boundaries are circumvented during processing. Review the official source advisory statement below for specific affected components, classes, and reproduction details.

Source Advisory Statement

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.

CVE-2026-10766 Affected mlrun Versions

1 component(s)
Product / Package Ecosystem Affected Versions Fixed Version
mlrun
pypi/mlrun
PyPI
≤ 1.12.0rc3

References

NVD — CVE-2026-10766 NVD
https://nvd.nist.gov/vuln/detail/CVE-2026-10766
mlrun Source Repository REPOSITORY
https://github.com/mlrun/mlrun/issues/9691
mlrun Source Repository REPOSITORY
https://github.com/mlrun/mlrun/pull/9692
mlrun Source Repository REPOSITORY
https://github.com/mlrun/mlrun
vuldb.com/cve/cve-2026-10766 WEB
https://vuldb.com/cve/CVE-2026-10766
vuldb.com/submit/831419 WEB
https://vuldb.com/submit/831419
vuldb.com/vuln/368136 WEB
https://vuldb.com/vuln/368136
vuldb.com/vuln/368136/cti WEB
https://vuldb.com/vuln/368136/cti

Frequently Asked Questions

What is CVE-2026-10766?
CVE-2026-10766 is a security vulnerability in mlrun involving DataFrame hash collisions can cause dataset artifact path conflicts and silent data corruption under CWE-327: Use of a Broken or Risky Cryptographic Algorithm.
Which mlrun versions are affected?
Affected versions include releases prior to current release patches across affected packages: mlrun.
What version fixes CVE-2026-10766?
Upgrading to current release patches (or the latest patched release for your respective branch) resolves the vulnerability.
Is mlrun affected?
Yes, mlrun is affected in releases prior to Latest secure release. Upgrade your dependency to Latest secure release or later.
What is the CVSS score of CVE-2026-10766?
CVE-2026-10766 has a CVSS v3.1 base score of 3.6 (LOW) with vector string CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:L/A:L.
What CWE is associated with CVE-2026-10766?
CVE-2026-10766 is classified under CWE-327: Use of a Broken or Risky Cryptographic Algorithm (The product uses a broken or risky cryptographic algorithm or protocol.).
How can I check PyPI dependencies for CVE-2026-10766?
Run the dependency tree command: 'pip show mlrun'. This command lists direct and transitive dependencies in your build configuration so you can verify if a vulnerable version is resolved.
Machine-readable OSV JSON OSV v1.5 Schema
Normalized schema output
View Raw JSON 
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  "schema_version" : "1.4.0",
  "id" : "GHSA-phx2-3w66-h4pw",
  "modified" : "2026-07-14T18:49:45Z",
  "published" : "2026-06-03T21:30:31Z",
  "aliases" : [ "CVE-2026-10766" ],
  "summary" : "mlrun: DataFrame hash collisions can cause dataset artifact path conflicts and silent data corruption",
  "details" : "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.",
  "severity" : [ {
    "type" : "CVSS_V3",
    "score" : "CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:L/A:L"
  }, {
    "type" : "CVSS_V4",
    "score" : "CVSS:4.0/AV:L/AC:H/AT:N/PR:L/UI:N/VC:N/VI:L/VA:L/SC:N/SI:N/SA:N/E:P"
  } ],
  "affected" : [ {
    "package" : {
      "ecosystem" : "PyPI",
      "name" : "mlrun"
    },
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      "type" : "ECOSYSTEM",
      "events" : [ {
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      }, {
        "last_affected" : "1.12.0rc3"
      } ]
    } ]
  } ],
  "references" : [ {
    "type" : "ADVISORY",
    "url" : "https://nvd.nist.gov/vuln/detail/CVE-2026-10766"
  }, {
    "type" : "WEB",
    "url" : "https://github.com/mlrun/mlrun/issues/9691"
  }, {
    "type" : "WEB",
    "url" : "https://github.com/mlrun/mlrun/pull/9692"
  }, {
    "type" : "PACKAGE",
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  }, {
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  }, {
    "type" : "WEB",
    "url" : "https://vuldb.com/submit/831419"
  }, {
    "type" : "WEB",
    "url" : "https://vuldb.com/vuln/368136"
  }, {
    "type" : "WEB",
    "url" : "https://vuldb.com/vuln/368136/cti"
  } ],
  "database_specific" : {
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    "severity" : "LOW",
    "github_reviewed" : true,
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    "nvd_published_at" : "2026-06-03T20:16:18Z"
  }
}