{"dataType":"CVE_RECORD","dataVersion":"5.2","cveMetadata":{"cveId":"CVE-2026-4035","assignerOrgId":"c09c270a-b464-47c1-9133-acb35b22c19a","state":"PUBLISHED","assignerShortName":"@huntr_ai","dateReserved":"2026-03-12T02:17:42.523Z","datePublished":"2026-06-03T07:18:08.512Z","dateUpdated":"2026-06-30T12:09:23.099Z"},"containers":{"cna":{"title":"Environment Variable Resolution Vulnerability in mlflow/mlflow","providerMetadata":{"orgId":"c09c270a-b464-47c1-9133-acb35b22c19a","shortName":"@huntr_ai","dateUpdated":"2026-06-03T07:18:08.512Z"},"descriptions":[{"lang":"en","value":"A vulnerability in mlflow/mlflow versions prior to 3.11.0 allows for the resolution of environment variables in AI Gateway secrets, which can be exploited to exfiltrate sensitive server-side environment credentials to an attacker-controlled endpoint. This issue arises because the `api_key` field in gateway secrets can accept `$ENV_VAR` references, which are resolved against the MLflow server's environment during runtime. The resolved secrets are then sent in provider authentication headers to the configured upstream `api_base`. This vulnerability can be exploited by low-privileged authenticated users in basic-auth deployments or by unauthenticated users in default deployments without `basic-auth`. The impact includes potential leakage of sensitive credentials such as cloud artifact credentials (`AWS_ACCESS_KEY_ID`, `AWS_SECRET_ACCESS_KEY`), which could lead to artifact poisoning and cross-boundary code execution in downstream environments. The issue is fixed in version 3.11.0."}],"affected":[{"vendor":"mlflow","product":"mlflow/mlflow","versions":[{"version":"unspecified","lessThan":"3.11.0","status":"affected","versionType":"custom"}]}],"references":[{"url":"https://huntr.com/bounties/f8e591a0-0f19-4910-b82e-16c9956f2233"},{"url":"https://github.com/mlflow/mlflow/commit/4a3f2f720cb4f058c9e0c5b883e0acc9ab64a7f3"}],"metrics":[{"cvssV3_0":{"version":"3.0","attackComplexity":"LOW","attackVector":"NETWORK","availabilityImpact":"LOW","confidentialityImpact":"HIGH","integrityImpact":"LOW","privilegesRequired":"LOW","scope":"CHANGED","userInteraction":"NONE","vectorString":"CVSS:3.0/AV:N/AC:L/PR:L/UI:N/S:C/C:H/I:L/A:L","baseScore":9.1,"baseSeverity":"CRITICAL"}}],"problemTypes":[{"descriptions":[{"type":"CWE","lang":"en","description":"CWE-201 Insertion of Sensitive Information Into Sent Data","cweId":"CWE-201"}]}],"source":{"advisory":"f8e591a0-0f19-4910-b82e-16c9956f2233","discovery":"EXTERNAL"}},"adp":[{"references":[{"url":"https://huntr.com/bounties/f8e591a0-0f19-4910-b82e-16c9956f2233","tags":["exploit"]}],"metrics":[{"other":{"type":"ssvc","content":{"timestamp":"2026-06-03T13:10:20.303201Z","id":"CVE-2026-4035","options":[{"Exploitation":"poc"},{"Automatable":"no"},{"Technical Impact":"partial"}],"role":"CISA Coordinator","version":"2.0.3"}}}],"title":"CISA ADP Vulnrichment","providerMetadata":{"orgId":"134c704f-9b21-4f2e-91b3-4a467353bcc0","shortName":"CISA-ADP","dateUpdated":"2026-06-03T13:10:24.407Z"}},{"affected":[{"cpes":["cpe:/a:redhat:openshift_ai"],"defaultStatus":"affected","product":"Red Hat OpenShift AI (RHOAI)","vendor":"Red Hat"}],"datePublic":"2026-06-03T07:18:08.512Z","descriptions":[{"lang":"en","value":"A flaw was found in MLflow. This vulnerability allows an attacker to exfiltrate sensitive server-side environment credentials. It occurs because the AI Gateway secrets can resolve environment variables, which are then sent to an attacker-controlled endpoint. This could lead to unauthorized access to cloud resources and potentially enable cross-boundary code execution."}],"metrics":[{"other":{"content":{"namespace":"https://access.redhat.com/security/updates/classification/","value":"Important"},"type":"Red Hat severity rating"}},{"cvssV3_1":{"attackComplexity":"LOW","attackVector":"NETWORK","availabilityImpact":"NONE","baseScore":7.7,"baseSeverity":"HIGH","confidentialityImpact":"HIGH","integrityImpact":"NONE","privilegesRequired":"LOW","scope":"CHANGED","userInteraction":"NONE","vectorString":"CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:C/C:H/I:N/A:N","version":"3.1"},"format":"CVSS"}],"problemTypes":[{"descriptions":[{"cweId":"CWE-201","description":"Insertion of Sensitive Information Into Sent Data","lang":"en","type":"CWE"}]}],"references":[{"tags":["vdb-entry","x_refsource_REDHAT"],"url":"https://access.redhat.com/security/cve/CVE-2026-4035"},{"name":"RHBZ#2484318","tags":["issue-tracking","x_refsource_REDHAT"],"url":"https://bugzilla.redhat.com/show_bug.cgi?id=2484318"},{"tags":["x_sadp-csaf-vex"],"url":"https://security.access.redhat.com/data/csaf/v2/vex/2026/cve-2026-4035.json"}],"timeline":[{"lang":"en","time":"2026-06-03T09:00:55.993Z","value":"Reported to Red Hat."},{"lang":"en","time":"2026-06-03T07:18:08.512Z","value":"Made public."}],"title":"python-mlflow: MLflow: Sensitive credential exfiltration via environment variable resolution in AI Gateway secrets","workarounds":[{"lang":"en","value":"To mitigate this issue, restrict network access to the MLflow server to trusted clients only. Additionally, ensure that authentication mechanisms, such as basic-auth, are properly configured and enabled for MLflow deployments to prevent unauthenticated or low-privileged access to the AI Gateway. Consult MLflow documentation for specific configuration steps related to network access control and authentication. A restart or reload of the MLflow service may be required for changes to take effect."}],"x_adpType":"supplier","x_generator":{"engine":"sadp-cli 1.0.0"},"providerMetadata":{"orgId":"0b0ca135-0b70-47e7-9f44-1890c2a1c46c","shortName":"redhat-SADP","dateUpdated":"2026-06-30T12:09:23.099Z"}}]}}