CVE-2025-3466
📋 TL;DR
CVE-2025-3466 is a critical vulnerability in langgenius/dify versions 1.1.0 to 1.1.2 that allows attackers to execute arbitrary code with root permissions by exploiting unsanitized input in the code node. This occurs because attackers can override global JavaScript functions like parseInt before sandbox security restrictions are applied. Organizations using vulnerable dify.ai deployments are affected, potentially exposing secret keys, internal networks, and enabling lateral movement.
💻 Affected Systems
- langgenius/dify
📦 What is this software?
Dify by Langgenius
⚠️ Risk & Real-World Impact
Worst Case
Full system compromise with root access, exfiltration of all secret keys, complete control over the dify.ai instance, and lateral movement to other internal systems.
Likely Case
Unauthorized access to sensitive data, execution of arbitrary commands on the host system, and potential privilege escalation within the environment.
If Mitigated
Limited impact if proper network segmentation, least privilege principles, and input validation are implemented, though the vulnerability still presents significant risk.
🎯 Exploit Status
Exploitation requires access to the code node functionality, but the vulnerability is well-documented with public proof-of-concept available on huntr.com.
🛠️ Fix & Mitigation
✅ Official Fix
Patch Version: 1.1.3
Vendor Advisory: https://github.com/langgenius/dify/commit/1be0d26c1feb4bcbbdd2b4ae4eeb25874aadaddb
Restart Required: Yes
Instructions:
1. Backup your current dify.ai instance and data. 2. Update to version 1.1.3 or later using your deployment method (Docker, Kubernetes, etc.). 3. Restart the dify.ai service. 4. Verify the update was successful by checking the version.
🔧 Temporary Workarounds
Disable Code Node Functionality
allTemporarily disable or restrict access to the code node feature in dify.ai until patching can be completed.
# Modify dify.ai configuration to disable code execution features
# Check documentation for specific configuration options
Network Segmentation
linuxIsolate the dify.ai instance from sensitive internal networks and systems to limit lateral movement potential.
# Configure firewall rules to restrict dify.ai network access
# Example: iptables -A OUTPUT -d 10.0.0.0/8 -j DROP for internal networks
🧯 If You Can't Patch
- Implement strict network segmentation to isolate the vulnerable system from critical assets.
- Apply additional monitoring and alerting for suspicious code execution patterns in dify.ai logs.
🔍 How to Verify
Check if Vulnerable:
Check your dify.ai version. If it's between 1.1.0 and 1.1.2 inclusive, you are vulnerable.Check Version:
docker exec dify-container cat /app/version.txt || check dify.ai web interface version displayVerify Fix Applied:
After updating, verify the version is 1.1.3 or later and test that code node functionality works without allowing arbitrary code execution.📡 Detection & Monitoring
Log Indicators:
- Unusual code execution patterns in dify.ai logs
- Unexpected system command execution from dify.ai process
- Access to sensitive files or network resources by dify.ai
Network Indicators:
- Outbound connections from dify.ai to unexpected internal systems
- Unusual network traffic patterns from dify.ai instance
SIEM Query:
source="dify_logs" AND ("code_execution" OR "parseInt" OR "global_override")