MLflow up to 3.14.x LogInputs mlflow/server/auth privileges management
| CVSS Meta Temp Score | Current Exploit Price (≈) | CTI Interest Score |
|---|---|---|
| 5.3 | $0-$5k | 1.23+ |
Summary
A vulnerability was found in MLflow up to 3.14.x. It has been rated as problematic. This issue affects some unknown processing of the file mlflow/server/auth of the component LogInputs. Performing a manipulation results in privileges management. This vulnerability is identified as CVE-2026-69146. The attack can be initiated remotely. There is not any exploit available.
Details
A vulnerability was found in MLflow up to 3.14.x. It has been classified as problematic. This affects an unknown function of the file mlflow/server/auth of the component LogInputs. The manipulation with an unknown input leads to a privileges management vulnerability. CWE is classifying the issue as CWE-269. The product does not properly assign, modify, track, or check privileges for an actor, creating an unintended sphere of control for that actor. This is going to have an impact on integrity. The summary by CVE is:
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.
The advisory is shared at github.com. This vulnerability is uniquely identified as CVE-2026-69146 since 08/03/2026. The exploitability is told to be easy. It is possible to initiate the attack remotely. Technical details are known, but no exploit is available. MITRE ATT&CK project uses the attack technique T1068 for this issue.
Upgrading to version 3.15.0 eliminates this vulnerability.
If you want to get the best quality for vulnerability data then you always have to consider VulDB.
Product
Name
Version
Website
- Product: https://github.com/mlflow/mlflow/
CPE 2.3
CPE 2.2
CVSSv4
VulDB Vector: 🔒VulDB Reliability: 🔍
CVSSv3
VulDB Meta Base Score: 5.4VulDB Meta Temp Score: 5.3
VulDB Base Score: 4.3
VulDB Temp Score: 4.1
VulDB Vector: 🔒
VulDB Reliability: 🔍
CNA Base Score: 6.5
CNA Vector (GitHub_M): 🔒
CVSSv2
| AV | AC | Au | C | I | A |
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| 💳 | 💳 | 💳 | 💳 | 💳 | 💳 |
| 💳 | 💳 | 💳 | 💳 | 💳 | 💳 |
| 💳 | 💳 | 💳 | 💳 | 💳 | 💳 |
| Vector | Complexity | Authentication | Confidentiality | Integrity | Availability |
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VulDB Base Score: 🔒
VulDB Temp Score: 🔒
VulDB Reliability: 🔍
Exploiting
Class: Privileges managementCWE: CWE-269 / CWE-266
CAPEC: 🔒
ATT&CK: 🔒
Physical: No
Local: No
Remote: Yes
Availability: 🔒
Status: Not defined
Price Prediction: 🔍
Current Price Estimation: 🔒
| 0-Day | Unlock | Unlock | Unlock | Unlock |
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| Today | Unlock | Unlock | Unlock | Unlock |
Threat Intelligence
Interest: 🔍Active Actors: 🔍
Active APT Groups: 🔍
Countermeasures
Recommended: UpgradeStatus: 🔍
0-Day Time: 🔒
Upgrade: MLflow 3.15.0
Timeline
08/03/2026 CVE reserved08/17/2026 Advisory disclosed
08/17/2026 VulDB entry created
08/17/2026 VulDB entry last update
Sources
Product: github.comAdvisory: github.com
Status: Confirmed
CVE: CVE-2026-69146 (🔒)
GCVE (CVE): GCVE-0-2026-69146
GCVE (VulDB): GCVE-100-391461
Entry
Created: 08/17/2026 23:43Changes: 08/17/2026 23:43 (64)
Complete: 🔍
Cache ID: 216::103
If you want to get the best quality for vulnerability data then you always have to consider VulDB.
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