Vulnerability in mlflow (CVE-2026-10803)
Summary
Vulnerability in mlflow (CVE-2026-10803). Risk of unauthorized operations or information disclosure. Mitigation: upgrade to 3.10.1 or later.
Original description
The description as published by the source.
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.
Source: GitHub Security Advisories (Global) NVD GitHub Advisory
Auto-generated summary
Assembled by SecPulse from the source data (CVSS, CWE, affected versions) using templates — no AI involved. Check the original description and references below for exact details.
A vulnerability tracked as CVE-2026-10803 has been found in mlflow.
Risk of unauthorized operations or information disclosure. CVSS score: 3.6/10.
What to do: upgrade mlflow to 3.10.1 or later.
If unsure, ask your IT team or search "mlflow CVE-2026-10803" on the vendor's site.
CVE-2026-10803 (mlflow) — CWE-327 / CVSS v3 3.6
Attack vector: local / no user interaction
Patched: 3.10.1 — apply immediately
Plan: 1) Audit SBOM/dependencies, 2) Stage→prod upgrade, 3) Add WAF/proxy monitoring on affected endpoints, 4) Hunt IOCs in logs.
Refs: see the GHSA / vendor advisory / patched release linked on this page.
A vulnerability (CWE-327) exists in mlflow.
Check the vendor advisory for the affected versions of mlflow.
Severity: Low (CVSS 3.6/10). Risk of unauthorized operations or information disclosure.
Update to 3.10.1.
Until the patch is applied: disable the affected feature, apply WAF rules, or restrict access via network ACLs.
Search webserver/proxy logs for unusual request patterns matching this CVE's known IOCs. Run grep -r 'mlflow' . against your dependency files (package-lock.json, requirements.txt, go.sum) to find affected services.
Response actions
Concrete steps and command examples for SOC/SRE teams to execute in order
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1Identify exposure identify
grep -r 'mlflow' . | grep -v node_modulesリポジトリと本番環境の依存ファイル (package-lock.json / requirements.txt / go.sum / Gemfile.lock 等) で
mlflowを grep し、稼働しているサービス・バージョンを把握する。 -
2Apply patch patch
Upgrade mlflow to 3.10.1ステージング環境で 3.10.1 に上げて回帰テスト → 本番反映。回帰テストはアプリの主要ハッピーパスを含めること。
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3Post-deployment verification verify
Confirm patched version is live in productionパッチ適用後、ステージングで PoC または同等の悪用パターンを再現して脆弱性が閉じたことを確認。本番ではアクセスログ・WAF でアラート再発が無いか継続監視。
Affected packages
References
- advisory vuldb.com
- advisory vuldb.com
- advisory vuldb.com
- advisory github.com
- package github.com
- report github.com
- report github.com
- report vuldb.com
- web nvd.nist.gov
- web github.com
- web github.com