{"dataType": "CVE_RECORD", "dataVersion": "5.2", "cveMetadata": {"cveId": "CVE-2025-14287", "assignerOrgId": "c09c270a-b464-47c1-9133-acb35b22c19a", "state": "PUBLISHED", "assignerShortName": "@huntr_ai", "dateReserved": "2025-12-08T19:06:12.739Z", "datePublished": "2026-03-15T09:27:36.706Z", "dateUpdated": "2026-03-15T09:27:36.706Z"}, "containers": {"cna": {"title": "Command Injection in mlflow/mlflow", "providerMetadata": {"orgId": "c09c270a-b464-47c1-9133-acb35b22c19a", "shortName": "@huntr_ai", "dateUpdated": "2026-03-15T09:27:36.706Z"}, "descriptions": [{"lang": "en", "value": "A command injection vulnerability exists in mlflow/mlflow versions before v3.7.0, specifically in the `mlflow/sagemaker/__init__.py` file at lines 161-167. The vulnerability arises from the direct interpolation of user-supplied container image names into shell commands without proper sanitization, which are then executed using `os.system()`. This allows attackers to execute arbitrary commands by supplying malicious input through the `--container` parameter of the CLI. The issue affects environments where MLflow is used, including development setups, CI/CD pipelines, and cloud deployments."}], "affected": [{"vendor": "mlflow", "product": "mlflow/mlflow", "versions": [{"version": "unspecified", "status": "affected", "versionType": "custom", "lessThanOrEqual": "latest"}]}], "references": [{"url": "https://huntr.com/bounties/229cd526-41aa-4819-b6f0-e2d0371c89e3"}], "metrics": [{"cvssV3_0": {"version": "3.0", "attackComplexity": "HIGH", "attackVector": "NETWORK", "availabilityImpact": "HIGH", "confidentialityImpact": "HIGH", "integrityImpact": "HIGH", "privilegesRequired": "NONE", "scope": "UNCHANGED", "userInteraction": "REQUIRED", "vectorString": "CVSS:3.0/AV:N/AC:H/PR:N/UI:R/S:U/C:H/I:H/A:H", "baseScore": 7.5, "baseSeverity": "HIGH"}}], "problemTypes": [{"descriptions": [{"type": "CWE", "lang": "en", "description": "CWE-94 Improper Control of Generation of Code", "cweId": "CWE-94"}]}], "source": {"advisory": "229cd526-41aa-4819-b6f0-e2d0371c89e3", "discovery": "EXTERNAL"}}}}

{}

{"cveTags": [], "descriptions": [{"lang": "en", "value": "A command injection vulnerability exists in mlflow/mlflow versions before v3.7.0, specifically in the `mlflow/sagemaker/__init__.py` file at lines 161-167. The vulnerability arises from the direct interpolation of user-supplied container image names into shell commands without proper sanitization, which are then executed using `os.system()`. This allows attackers to execute arbitrary commands by supplying malicious input through the `--container` parameter of the CLI. The issue affects environments where MLflow is used, including development setups, CI/CD pipelines, and cloud deployments."}], "id": "CVE-2025-14287", "lastModified": "2026-03-16T14:53:46.157", "metrics": {"cvssMetricV30": [{"cvssData": {"attackComplexity": "HIGH", "attackVector": "NETWORK", "availabilityImpact": "HIGH", "baseScore": 7.5, "baseSeverity": "HIGH", "confidentialityImpact": "HIGH", "integrityImpact": "HIGH", "privilegesRequired": "NONE", "scope": "UNCHANGED", "userInteraction": "REQUIRED", "vectorString": "CVSS:3.0/AV:N/AC:H/PR:N/UI:R/S:U/C:H/I:H/A:H", "version": "3.0"}, "exploitabilityScore": 1.6, "impactScore": 5.9, "source": "security@huntr.dev", "type": "Secondary"}]}, "published": "2026-03-16T14:17:55.610", "references": [{"source": "security@huntr.dev", "url": "https://huntr.com/bounties/229cd526-41aa-4819-b6f0-e2d0371c89e3"}], "sourceIdentifier": "security@huntr.dev", "vulnStatus": "Awaiting Analysis", "weaknesses": [{"description": [{"lang": "en", "value": "CWE-94"}], "source": "security@huntr.dev", "type": "Primary"}]}

{}

{"affected": [{"configurations": [{"platform": null, "status": "affected", "versions": {"scheme": "generic", "value": "[0,*]"}}], "enrichment": {"confidence": 100.0, "confidence_source": "manual", "scores": [{"score": 100.0, "source": "manual"}]}, "original": {"product": "mlflow/mlflow", "source": "cna", "vendor": "mlflow"}, "product": "mlflow", "vendor": "mlflow"}], "created": "2026-03-16T09:21:56.318157+00:00", "updated": "2026-03-16T09:21:56.318247+00:00", "vendors": ["mlflow", "mlflow$PRODUCT$mlflow"]}