# CVE-2025-15381: mlflow (High 8.1) 🐍 🐍 PyPI Not in CISA KEV HIGH severity # CVE-2025-15381 — mlflow HIGH CVE-2025-15381 is a high-severity (CVSS 8.1) Information Exposure vulnerability in mlflow. The records list no fixed version yet; check the vendor advisory below and apply the mitigations in the meantime. MLFlow allows Tracing + Assessments Access Also known asPYSEC-2026-2657 Published Mar 27, 2026 Updated Sep 10, 2026 Affected 1 pkg Patched See advisory Exploits None indexed Exploitation data as of Nov 10, 2026 · OSV.dev, NVD, FIRST.org (EPSS) ## Exploitation Status ### No confirmed exploitation observed yet - A successful exploit gives an attacker total control of the affected component, not partial access. - CISA’s own triage has not observed active exploitation or public proof-of-concept code for this CVE as of its last assessment. Exploitation and automatability from CISA’s SSVC triage for CVE-2025-15381. ## EPSS Exploitation Probability [via FIRST.org ↗](https://www.first.org/epss/) 0.3%probability of exploitation in next 30 days Lower Risk0.00% Lower risk than most CVEs28th percentile — riskier than 28% of all scored CVEsHighest risk 0.00%0.28%0.56%0.84%0.0%0.3%May 26Sep 26Nov 26 Probability of exploitation in the next 30 days, from [FIRST.org EPSS](https://www.first.org/epss/). ## How urgent is this, really ## Where this sits among everything scored ## Real-World Exposure 1 pkg affected 🐍`mlflow` Real-time download stats are indexed for npm and PyPI packages. This vulnerability affects PyPI packages — download data is not available via public APIs for these ecosystems. ## Description In the latest version of mlflow/mlflow, when the `basic-auth` app is enabled, tracing and assessment endpoints are not protected by permission validators. This allows any authenticated user, including those with `NO_PERMISSIONS` on the experiment, to read trace information and create assessments for traces they should not have access to. This vulnerability impacts confidentiality by exposing trace metadata and integrity by allowing unauthorized creation of assessments. Deployments using `mlflow server --app-name=basic-auth` are affected. ## Affected Packages 1 total Ecosystem Package Vulnerable range Fix 🐍PyPI `mlflow` all versions No fix ## Affected Products 1 product · 1 configurations Application `mlflow`lfprojects all ## Detection & mitigation playbook Open-source dependency 1. ### Detect Scan your dependency tree (package-lock.json, pnpm-lock.yaml, requirements.txt, go.sum, etc.) for mlflow, including transitive dependencies — a direct dependency you never call can still pull in a vulnerable version. 2. ### Remediation status The records we use list no patched version of mlflow for CVE-2025-15381. Check the maintainer's advisory, and where your build allows, override or pin the dependency away from the vulnerable range. 3. ### Mitigate without a patch Assume what was exposed is already known: rotate any credential, token or key that the affected component could return, restrict the endpoint to callers that genuinely need it, and strip sensitive fields from responses and error output at the boundary rather than relying on the client not to read them. ## Frequently Asked Questions In the latest version of mlflow/mlflow, when the \`basic-auth\` app is enabled, tracing and assessment endpoints are not protected by permission validators. This allows any authenticated user, including those with \`NO\_PERMISSIONS\` on the experiment, to read trace information and create assessments for traces they should not have access to. This vulnerability impacts confidentiality by exposing trace metadata and integrity by allowing unauthorized creation of assessments. Deployments using \`mlflow server --app-name=basic-auth\` are affected. O3 Security · Impact-Aware SCA ### Is CVE-2025-15381 in your dependencies? Find it across PyPI, including transitive dependencies. [Scan my dependencies](/book-demo) [How O3 SCA works](/impact-aware-sca)