CVE-2026-10803: MLflow: Deterministic sampling in dataset digest enables predictable collisions
A flaw has been found in MLflow up to 3.10.0. This issue affects the function mlflow.data.digestutils of the file mlflow/data/digestutils.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.
Published Jun 4, 2026 · Updated Jul 15, 2026
Affected packages
mlflow
- Ecosystem
- PyPI
- Affected
- < 3.10.1
- Fixed in
- 3.10.1
- Check
pip show mlflow
Advisory details
From the GitHub Advisory Database (CC BY 4.0).
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.
References
- https://nvd.nist.gov/vuln/detail/CVE-2026-10803
- https://github.com/mlflow/mlflow/issues/22419
- https://github.com/mlflow/mlflow/pull/22420
- https://github.com/mlflow/mlflow
- https://vuldb.com/cve/CVE-2026-10803
- https://vuldb.com/submit/831462
- https://vuldb.com/vuln/368252
- https://vuldb.com/vuln/368252/cti
- https://github.com/pypa/advisory-database/tree/main/vulns/mlflow/PYSEC-2026-195.yaml
- https://github.com/advisories/GHSA-5qmp-p3c4-72qj
How this page is made: the data panel comes from the GitHub Advisory Database, CISA’s KEV catalog, the NVD and FIRST EPSS, and updates twice a day. No analysis has been written for this entry yet. Methodology
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