CVE-2024-46946
📋 TL;DR
CVE-2024-46946 is a critical remote code execution vulnerability in LangChain Experimental's LLMSymbolicMathChain component. Attackers can execute arbitrary code through sympy.sympify's eval function when processing untrusted input. This affects any application using vulnerable versions of langchain_experimental with LLMSymbolicMathChain functionality.
💻 Affected Systems
- langchain_experimental (LangChain Experimental)
📦 What is this software?
⚠️ Risk & Real-World Impact
Worst Case
Complete system compromise allowing attackers to execute arbitrary commands, steal data, install malware, or pivot to other systems.
Likely Case
Remote code execution leading to data exfiltration, credential theft, or deployment of ransomware/cryptominers.
If Mitigated
Limited impact if input validation and sandboxing prevent malicious payloads from reaching sympy.sympify.
🎯 Exploit Status
Proof-of-concept available in GitHub gist. Exploitation requires sending malicious input to LLMSymbolicMathChain endpoints.
🛠️ Fix & Mitigation
✅ Official Fix
Patch Version: langchain_experimental >= 0.3.1
Vendor Advisory: https://github.com/langchain-ai/langchain/releases/tag/langchain-experimental%3D%3D0.3.0
Restart Required: No
Instructions:
1. Update langchain_experimental to version 0.3.1 or higher using pip: pip install --upgrade langchain_experimental>=0.3.1
2. Verify no breaking changes in your application.
3. Test LLMSymbolicMathChain functionality after update.
🔧 Temporary Workarounds
Disable LLMSymbolicMathChain
allTemporarily disable or remove LLMSymbolicMathChain functionality until patching is possible.
# Remove or comment out LLMSymbolicMathChain imports and usage in your code
Input Validation and Sanitization
allImplement strict input validation to reject any mathematical expressions containing dangerous functions or characters.
# Example Python input validation:
import re
def validate_math_input(input_str):
dangerous_patterns = [r'__.*__', r'eval', r'exec', r'import', r'open', r'os\\.', r'subprocess']
for pattern in dangerous_patterns:
if re.search(pattern, input_str):
return False
return True
🧯 If You Can't Patch
- Implement network segmentation to isolate systems using vulnerable LangChain components
- Deploy web application firewall (WAF) rules to block malicious mathematical expression patterns
🔍 How to Verify
Check if Vulnerable:
Check if langchain_experimental version is between 0.1.17 and 0.3.0 inclusive, and if LLMSymbolicMathChain is imported/used.Check Version:
pip show langchain_experimental | grep VersionVerify Fix Applied:
Verify langchain_experimental version is 0.3.1 or higher and test that malicious sympy.sympify payloads are rejected.📡 Detection & Monitoring
Log Indicators:
- Unusual mathematical expression patterns in LLMSymbolicMathChain logs
- Python eval/exec errors or warnings
- Unexpected process spawns from LangChain applications
Network Indicators:
- HTTP requests containing suspicious mathematical expressions with Python code
- Outbound connections from LangChain applications to unexpected destinations
SIEM Query:
source="application_logs" AND "LLMSymbolicMathChain" AND ("eval" OR "exec" OR "__import__")