vulnerability / NVI-00008992 / Revision 2
MLflow vulnerable to arbitrary file read on unauthenticated servers via prompt model version source
GitHub lists this reviewed advisory for mlflow. Published version ranges and source prerequisites are shown below; this is not an inspection of a visitor’s application.
This report has not inspected your inventory, configuration, deployed build, reachability or evidence. A catalog listing and a severity score do not establish exposure or compromise.
01 / Meaning
Why it matters
Published affected context helps an owner decide what evidence to gather. This report has not examined your application.
7.5 high
GitHub source severity; exploitability and local consequence require separate evidence.
As of · GitHub Advisory Database
0.559%
FIRST EPSS model v2026.06.15; exploitation probability over 30 days, percentile 0.4658. Missing scores are unknown.
As of · FIRST EPSS
02 / Applicability
The affected context
Affected versions, configuration prerequisites and known exclusions are public. Confirm each one against the deployed service.
mlflow
source listed>= 3.10.0, < 3.17.0
### Summary On MLflow tracking servers running without authentication, which is the default for mlflow server, a remote attacker can read arbitrary files from the server’s filesystem by creating a model version tagged as a prompt whose source is a schemeless local path. The fix for CVE-2026-2614 in 3.10.0 added a prompt-specific branch to the `CreateModelVersion` handler that rejects `file://` URIs and absolute paths but runs path validation only when the source carries a URL scheme. A schemeless value such as `../../etc`, a plain relative name, `.`, a percent-encoded path, or a Windows drive-letter path is therefore stored unchanged as the model version’s artifact location, and the `model-versions/get-artifact endpoint` later serves files from it with the privileges of the server process. The tag check also keyed on the presence of the `mlflow.prompt.is_prompt` tag rather than its value, so a false value still selected the weaker branch. Servers using `--app-name basic-auth` are also affected: any authenticated user can create a registered model, so a low-privilege account can use this to read the authentication database, including the admin password hash. Affected: MLflow 3.10
03 / Response
What to do next
- investigate
Identify the exact component and deployed version, examine the linked publisher’s conditions, and retain evidence of any mitigation.
Confirm current vendor support, compatibility and deployment evidence. This report has not tested a fix in your system. FIRST EPSS
A fixed release is not deployment evidence.
Check current vendor support and compatibility. After making a change, verify the deployed build and relevant runtime conditions. Keep the evidence, owner and time. An updated lockfile alone does not prove what is running.
04 / Limits
What this report cannot establish
- Customer inventory, deployment, reachability and exploitation have not been inspected.
05 / Provenance
Sources you can inspect
Each assertion retains its source. Mirrored records may repeat one underlying publisher; additional links are not independent corroboration.
- GHSA-m65p-9j7q-6w33 ↗
GitHub Advisory Database · vendor advisory
Observed . GitHub Advisory Database; CC-BY-4.0. Each advisory links its original attribution. Null normalizes fields.
- CVE-2026-116690 ↗
FIRST EPSS · official catalog
Observed . FIRST EPSS; probability of exploitation in the next 30 days, not local compromise. Dataset date/model retained; FIRST services terms apply.
Public revision history
Only published revisions appear here. Routine fetches do not create a material-change event.
- Revision 2 ·
Dated EPSS estimate updated; this is not a new disclosure or proof of exploitation.
- Revision 1 ·
First indexed by Null; source disclosure date is shown separately.