MLflow: MLflow AI Gateway permits SSRF through an unvalidated api_base
MLflow
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- Severity
- High, CVSS 7.1
- CVSS vector
- CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:L/A:N
- Record
- CVE-2026-71211
- Affects
- MLflow
- Known exploited
- Not listed in the CISA Known Exploited Vulnerabilities catalog
- Published
- Record first published by the source
- August 5, 2026
- Source last modified
- August 31, 2026
Description
MLflow's AI Gateway accepts an auth_config.api_base value when creating a gateway secret (mlflow/server/handlers.py, _create_gateway_secret) with no validation of scheme, host, or IP range; the value is stored verbatim. The gateway proxy endpoint (mlflow/server/gateway_api.py, raw_proxy) subsequently issues an HTTP request to that stored api_base plus a caller-supplied path and returns the full response body. MLflow's existing SSRF guard, _validate_webhook_url (which blocks non-global and metadata IPs), is never invoked anywhere in this gateway secret/proxy code path. The CreateGatewaySecret action additionally has no entry in the permission-validator map, so it requires only basic authentication rather than any specific scope, meaning any authenticated user — including read-only accounts — can create a secret pointing at an internal address and reach it via the proxy endpoint, potentially exposing cloud-instance IAM credentials via metadata services. This is related to CVE-2026-4035, which addresses a distinct mechanism in the same gateway-secret feature (server-side $ENV_VAR resolution inside the api_key field leaking credentials to the configured upstream); the finding here is an independent missing-validation gap in the api_base destination itself, unaffected by that fix.
Description quoted from the NVD record.
Who is affected
MLflow, made by LF Projects, is a platform for building, tracking and running machine learning and AI models. This flaw is in its AI Gateway, the part that connects MLflow to outside AI services. Any user who can sign in, even one with read-only access, can point the gateway at an address inside your network and read whatever comes back. That could expose private systems and, on cloud servers, the login credentials of the server itself. No specific affected versions are named for this flaw. This flaw is rated High.
What to do
- If someone in your organization installed or runs MLflow, that person should handle this. If an IT provider or vendor runs it for you, send them this advisory and ask when the update will be done.
- No fixed version is named for this flaw yet, so check the vendor advisory linked on this page for a fixed release and install it as soon as one is available.
- Tell the person responsible that this flaw is in the AI Gateway part of MLflow and can be used by any signed-in user, including read-only accounts.
Analysis written from the source record as of August 31, 2026 and reviewed before publishing.