CVE-2026-69146
MLflow: LogInputs endpoint bypasses per-run UPDATE authorization in basic-auth
No known exploitation. EPSS puts it in the 30th percentile. No fix published yet.
What to do
No fixed build or workaround is published yet. Limit exposure and watch for a patch.
What it is
From the CVE record
MLflow is an open source AI engineering platform for agents, large language models, and machine learning models. From 3.13.0 until 3.15.0, LogInputs is absent from BEFORE_REQUEST_HANDLERS in the mlflow/server/auth package, allowing any authenticated user to call POST /api/2.0/mlflow/runs/log-inputs for another user's run_id and inject attacker-controlled DatasetInput records into the dataset_inputs lineage metadata without UPDATE permission. This issue is fixed in version 3.15.0.
In plain language
No plain-language summary for this CVE yet.
Exploitation
Where each signal puts this CVE on the scale from published to confirmed exploited.
- CISA KEV
Not in the catalog. CISA has not confirmed exploitation.
- Public exploits
No public exploit or proof of concept found in the sources we track.
- EPSS
0.4% chance of exploitation activity in the next 30 days, which ranks it in the 30th percentile of scored CVEs.
Exploit Prediction Scoring System, FIRST.org. A probability, not a confirmation.
Lifecycle
7 events over 34 days, from the signal feeds we watch.
- Record updated
- Record updated
- Publishedweakness classified, att&ck mapped, record updated
- OpenVAS check added
Affected products
Technical detail
CVSS 3.1 vector
Open in the CVSS calculatorCVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:H/A:N
Scored 6.5 by NVD.
How it is reached
- Attack Vector NetworkExploitable remotely over the network without any special conditions
- Attack Complexity LowNo special conditions — the attack can be reliably reproduced
- Privileges Required LowRequires basic user-level privileges
- User Interaction NoneNo user interaction needed — fully automated exploitation
Scope
- Scope UnchangedImpact is limited to the vulnerable component itself
Impact if exploited
- Confidentiality NoneNo confidentiality impact
- Integrity HighTotal loss of integrity — attacker can modify any data in the component
- Availability NoneNo availability impact
Weaknesses
ATT&CK techniques
Mapped from the weaknesses above (CWE to ATT&CK), not observed in attacks.
Sources
References in the record
- github.com/mlflow/mlflow/commit/5c34aec5669e2386b38b5ee0855cd61174e27693
- github.com/mlflow/mlflow/pull/24291
- github.com/mlflow/mlflow/releases/tag/v3.15.0
And 1 more reference. See all after sign-in
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