CVE-2026-10803: MLflow Deterministic Sampling Vulnerability

LOW
Advisory Identifier: GHSA-5qmp-p3c4-72qj
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CVSS 3.6
CWE-327
Published
Advisory Summary

CVE-2026-10803 is a LOW (CVSS 3.6) deterministic sampling vulnerability (CWE-327: Use of a Broken or Risky Cryptographic Algorithm) affecting MLflow libraries in the PyPI ecosystem. The issue involves deterministic sampling in dataset digest enables predictable collisions. Remediation is available by upgrading affected packages to version 3.10.1.

CVE-2026-10803 at a Glance

CVE Identifier CVE-2026-10803
GHSA Identifier GHSA-5qmp-p3c4-72qj
Severity LOW
CVSS v3.1 Base Score 3.6
CWE Classification CWE-327: Use of a Broken or Risky Cryptographic Algorithm
Affected Product MLflow
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-2026-10803

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

mlflow fixed: 3.10.1 
pip install mlflow>=3.10.1
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 mlflow

How to Check if You Are Affected

To determine whether your Python environment is affected by CVE-2026-10803, inspect your installed packages using pip:

pip show mlflow

Analyze the terminal output to locate any version of MLflow in your dependency tree. If any resolved version matches the vulnerable ranges listed in the table below (for example, versions earlier than 3.10.1), your application is affected.

Note: The pip show mlflow 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 MLflow, 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 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.

CVE-2026-10803 Affected MLflow Versions

1 component(s)
Fixed Versions:
3.10.1
Product / Package Ecosystem Affected Versions Fixed Version
mlflow
pypi/mlflow
PyPI
< 3.10.1
3.10.1

References

NVD — CVE-2026-10803 NVD
https://nvd.nist.gov/vuln/detail/CVE-2026-10803
MLflow Source Repository REPOSITORY
https://github.com/mlflow/mlflow/issues/22419
MLflow Source Repository REPOSITORY
https://github.com/mlflow/mlflow/pull/22420
MLflow Source Repository REPOSITORY
https://github.com/mlflow/mlflow
MLflow Source Repository REPOSITORY
https://github.com/pypa/advisory-database/tree/main/vulns/mlflow/PYSEC-2026-195.yaml
vuldb.com/cve/cve-2026-10803 WEB
https://vuldb.com/cve/CVE-2026-10803
vuldb.com/submit/831462 WEB
https://vuldb.com/submit/831462
vuldb.com/vuln/368252 WEB
https://vuldb.com/vuln/368252
vuldb.com/vuln/368252/cti WEB
https://vuldb.com/vuln/368252/cti

Frequently Asked Questions

What is CVE-2026-10803?
CVE-2026-10803 is a security vulnerability in MLflow involving Deterministic sampling in dataset digest enables predictable collisions under CWE-327: Use of a Broken or Risky Cryptographic Algorithm.
Which MLflow versions are affected?
Affected versions include releases prior to 3.10.1 across affected packages: mlflow.
What version fixes CVE-2026-10803?
Upgrading to 3.10.1 (or the latest patched release for your respective branch) resolves the vulnerability.
Is mlflow affected?
Yes, mlflow is affected in releases prior to 3.10.1. Upgrade your dependency to 3.10.1 or later.
What is the CVSS score of CVE-2026-10803?
CVE-2026-10803 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-2026-10803?
CVE-2026-10803 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-2026-10803?
Run the dependency tree command: 'pip show mlflow'. 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 
{
  "schema_version" : "1.4.0",
  "id" : "GHSA-5qmp-p3c4-72qj",
  "modified" : "2026-07-15T17:51:25Z",
  "published" : "2026-06-04T12:30:26Z",
  "aliases" : [ "CVE-2026-10803" ],
  "summary" : "MLflow: Deterministic sampling in dataset digest enables predictable collisions",
  "details" : "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.",
  "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" : "mlflow"
    },
    "ranges" : [ {
      "type" : "ECOSYSTEM",
      "events" : [ {
        "introduced" : "0"
      }, {
        "fixed" : "3.10.1"
      } ]
    } ]
  } ],
  "references" : [ {
    "type" : "ADVISORY",
    "url" : "https://nvd.nist.gov/vuln/detail/CVE-2026-10803"
  }, {
    "type" : "WEB",
    "url" : "https://github.com/mlflow/mlflow/issues/22419"
  }, {
    "type" : "WEB",
    "url" : "https://github.com/mlflow/mlflow/pull/22420"
  }, {
    "type" : "PACKAGE",
    "url" : "https://github.com/mlflow/mlflow"
  }, {
    "type" : "WEB",
    "url" : "https://github.com/pypa/advisory-database/tree/main/vulns/mlflow/PYSEC-2026-195.yaml"
  }, {
    "type" : "WEB",
    "url" : "https://vuldb.com/cve/CVE-2026-10803"
  }, {
    "type" : "WEB",
    "url" : "https://vuldb.com/submit/831462"
  }, {
    "type" : "WEB",
    "url" : "https://vuldb.com/vuln/368252"
  }, {
    "type" : "WEB",
    "url" : "https://vuldb.com/vuln/368252/cti"
  } ],
  "database_specific" : {
    "cwe_ids" : [ "CWE-327" ],
    "severity" : "LOW",
    "github_reviewed" : true,
    "github_reviewed_at" : "2026-07-15T17:51:25Z",
    "nvd_published_at" : "2026-06-04T12:16:24Z"
  }
}