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Sven Rath developed an MCP server that enables Large Language Models (LLMs) like Claude to perform automatic static malware analysis, generating detailed reports in Markdown. The tool integrates:
– YARA (pattern-based malware detection)
– yara-forge (YARA rule generator)
– detect-it-easy (file type identification)
– FLOSS (extracting obfuscated strings)
– capa (identifying malware capabilities)
– PE analysis (IAT, EAT, section headers)
PoC Code: GitHub Link
You Should Know: Key Commands & Tools
1. YARA Rule Generation & Scanning
Generate YARA rules with yara-forge yara-forge -s malware_sample.exe -o custom_rule.yar Scan malware with YARA yara -r custom_rule.yar suspicious_file.exe
2. FLOSS for String Extraction
Extract obfuscated strings from malware floss -q malware_sample.exe > extracted_strings.txt
3. CAPA for Malware Capability Analysis
Analyze malware capabilities capa malware_sample.exe -v > capa_report.txt
4. Detect-It-Easy (DIE) for File Analysis
Check file type and entropy diec -f malware_sample.exe
5. PE Analysis (IAT/EAT/Sections)
Using PE Tools (Linux) readpe -h malware_sample.exe Show PE headers readpe -i malware_sample.exe Inspect IAT readpe -e malware_sample.exe Extract EAT
6. Automating with Python (MCP Server Integration)
import subprocess
def run_floss(file_path):
result = subprocess.run(["floss", file_path], capture_output=True, text=True)
return result.stdout
malware_report = run_floss("malware.exe")
print(malware_report)
What Undercode Say
Automating malware analysis with LLMs enhances reverse engineering efficiency, especially when combined with tools like YARA, CAPA, and FLOSS. This approach:
– Reduces manual analysis time
– Improves detection accuracy
– Generates structured reports
Future enhancements could include dynamic analysis integration (Cuckoo Sandbox) and AI-powered anomaly detection.
Prediction
- AI-driven malware analysis will dominate threat intelligence.
- LLMs will automate 60% of reverse engineering tasks by 2026.
Expected Output:
Malware Analysis Report (Generated by LLM) YARA Matches - Rule: `Trojan_Generic_01` - Detection: `Matching signature found in .text section` FLOSS Extracted Strings - `"C:\Windows\System32\kernel32.dll"` - `"http://malicious-domain.com/payload.exe"` CAPA Findings - `CAPABILITY: Persistence via Registry Run Key` - `CAPABILITY: Network Communication (HTTP)` PE Structure - Sections: `.text (RX), .data (RW)` - IAT Imports: `CreateProcessA, RegSetValueEx`
Relevant URLs:
References:
Reported By: Sven Rath – Hackers Feeds
Extra Hub: Undercode MoN
Basic Verification: Pass ✅
