- CVSS
- HIGH · 7.7v3.1CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:C/C:H/I:N/A:N
- Published
- 2026-06-03
- Weakness
- CWE-201, CWE-201
- Source
- nvd.nist.gov/vuln/detail/CVE-2026-4035
Description
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.
References
- https://github.com/mlflow/mlflow/commit/4a3f2f720cb4f058c9e0c5b883e0acc9ab64a7f3
- https://huntr.com/bounties/f8e591a0-0f19-4910-b82e-16c9956f2233
- https://access.redhat.com/security/cve/CVE-2026-4035
- https://bugzilla.redhat.com/show_bug.cgi?id=2484318
- https://huntr.com/bounties/f8e591a0-0f19-4910-b82e-16c9956f2233
- https://security.access.redhat.com/data/csaf/v2/vex/2026/cve-2026-4035.json
How GTK Cyber trains on this
AI security training at GTK Cyber covers the LLM and ML-pipeline vulnerability classes that vulnerabilities like CVE-2026-4035 fall into. Our hands-on courses are taught by Charles Givre and other practitioners who break and defend production AI systems.