CVE-2023-4033
📋 TL;DR
This CVE describes an OS command injection vulnerability in MLflow versions prior to 2.6.0. Attackers can execute arbitrary operating system commands on the server by injecting malicious input into vulnerable parameters. Organizations running MLflow for machine learning workflow management are affected.
💻 Affected Systems
- MLflow
📦 What is this software?
Mlflow by Lfprojects
⚠️ Risk & Real-World Impact
Worst Case
Full server compromise allowing attackers to execute arbitrary commands, access sensitive data, install malware, or pivot to other systems in the network.
Likely Case
Unauthorized command execution leading to data exfiltration, service disruption, or privilege escalation within the MLflow environment.
If Mitigated
Limited impact with proper input validation and command sanitization in place, potentially only affecting isolated components.
🎯 Exploit Status
The vulnerability requires some level of access to MLflow functionality but exploitation is straightforward once access is obtained.
🛠️ Fix & Mitigation
✅ Official Fix
Patch Version: 2.6.0 and later
Vendor Advisory: https://github.com/mlflow/mlflow/commit/6dde93758d42455cb90ef324407919ed67668b9b
Restart Required: Yes
Instructions:
1. Backup your MLflow data and configurations. 2. Update MLflow using pip: 'pip install --upgrade mlflow>=2.6.0'. 3. Restart all MLflow services. 4. Verify the update with 'mlflow --version'.
🔧 Temporary Workarounds
Input Validation and Sanitization
allImplement strict input validation and sanitization for all user inputs that interact with system commands.
# Implement input validation in your MLflow deployment code
# Example: Validate and sanitize repository URLs and paths
Network Segmentation
linuxRestrict network access to MLflow instances to only trusted users and systems.
# Configure firewall rules to limit access
# Example: iptables -A INPUT -p tcp --dport 5000 -s trusted_ip -j ACCEPT
🧯 If You Can't Patch
- Implement strict network access controls to limit who can access MLflow instances
- Deploy web application firewall (WAF) rules to detect and block command injection attempts
🔍 How to Verify
Check if Vulnerable:
Check MLflow version with 'mlflow --version' or 'pip show mlflow'. If version is below 2.6.0, the system is vulnerable.Check Version:
mlflow --versionVerify Fix Applied:
After updating, run 'mlflow --version' to confirm version is 2.6.0 or higher. Test repository functionality to ensure it works without errors.📡 Detection & Monitoring
Log Indicators:
- Unusual command execution patterns in system logs
- MLflow logs showing unexpected repository operations
- Error messages containing shell metacharacters
Network Indicators:
- Unusual outbound connections from MLflow server
- Traffic patterns suggesting data exfiltration
SIEM Query:
source="mlflow.logs" AND ("os.system" OR "subprocess" OR "shell=True") AND NOT user="trusted_user"