Code execution via attacker-controlled loader module
Published Sep 8, 2026 · Updated Sep 8, 2026
Code execution in MLflow 0.0.1 and later allows remote authenticated users to run arbitrary code via a crafted PyFunc model artifact. mlflow.pyfunc.load_model() adds the artifact's configured code directory to sys.path and imports its attacker-selected loader_module without a trust check. Exploitation requires control of an artifact that a user or job later loads, and code runs with the loading process's privileges.
Summary
What happened
Code execution in MLflow 0.0.1 and later allows remote authenticated users to run arbitrary code via a crafted PyFunc model artifact. mlflow.pyfunc.load_model() adds the artifact's configured code directory to sys.path and imports its attacker-selected loader_module without a trust check. Exploitation requires control of an artifact that a user or job later loads, and code runs with the loading process's privileges.
The record
- CVE
- CVE-2026-79721
- Published
- Sep 8, 2026
- Updated
- Sep 8, 2026
- Vendor
- MLflow Project
- Product
- MLflow
- Classifications
- CWE-829, T1204.002
- Attack vector
- network
- Privileges
- authenticated
Timeline
How it unfolded
- Sep 8, 2026CVE publishedPublication date reported by the CVE source.
- Sep 8, 2026Record updatedLatest update available in the CVE record.
Exploitability
Present is not the same as exploitable
Compare your product and version with the public record. A matching version still requires validation against your environment.
Is a vulnerable build present?
Compare these published version ranges with your installed build and any vendor patches.
- Affected versionversion=0.0.1 <=*
What conditions does exploitation require?
What is affected?
Published CVSS scores
CVSS describes severity. EPSS estimates exploitation probability.
Attacks
What attackers are doing with it
Daily unique IPs observed by Shadowserver honeypots for known exploited vulnerabilities (KEVs). Missing observations do not establish an absence of attacks.
Weakness, pattern, technique
Public exploit references
- Crafted PyFunc loader-module proof of conceptproof of concept · demonstrated
Labels summarize the accepted research assessment. They do not indicate a test against your environment.
Technologies
Your stack
See the directory against your own environment.
Your stack
Check the software in your environment
Book a demo to see how Hinoki identifies affected software and validates exploitability in your environment.
Book a demo