autohandai/analyzing-cobalt-strike-malleable-profiles
analyzing-cobalt-strike-malleable-profiles/SKILL.md
Parses Cobalt Strike malleable C2 profiles using pyMalleableC2 to extract beacon configuration, HTTP communication patterns, and sleep/jitter settings. Combines with JARM TLS fingerprinting to detect C2 servers on the network. Use when investigating suspected Cobalt Strike infrastructure or building detection signatures for C2 traffic.
$ install --global
skillsauthnpx skillsauth add autohandai/community-skills analyzing-cobalt-strike-malleable-profilesInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
Security Scan Results
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
3
Scanners Passed
9
Scanners in report
Clean
TrivyContainer and dependency vulnerability scanner
95%
Clean
SemgrepStatic code analysis for vulnerabilities
95%
Clean
mcp-scan (Snyk)Model Context Protocol security validation
95%
Skipped
Snyk (dep)Open source security scanning
50%
Skipped
Socket.devSupply chain security analysis
50%
Skipped
VirusTotalMulti-engine malware detection
50%
Skipped
CrowdStrikeAdvanced threat intelligence
50%
Skipped
OSV-ScannerOpen Source Vulnerability database check
50%
Skipped
OWASP Dep-Check
50%
Last scanned: Jul 1, 2026, 3:50 AM16.7s3 files scanned
SKILL.md
- name:
- analyzing-cobalt-strike-malleable-profiles
- description:
- >
- domain:
- cybersecurity
- subdomain:
- security-operations
- tags:
- [analyzing, cobalt, strike, malleable]
- version:
- 1.0
- author:
- mahipal
- license:
- Apache-2.0
Analyzing Cobalt Strike Malleable Profiles
Instructions
Parse malleable C2 profiles to extract IOCs and detection opportunities using the pyMalleableC2 library. Combine with JARM fingerprinting to identify C2 servers.
from malleablec2 import Profile
# Parse a malleable profile from file
profile = Profile.from_file("amazon.profile")
# Extract global options (sleep, jitter, user-agent)
print(profile.ast.pretty())
# Access HTTP-GET block URIs and headers for network signatures
# Access HTTP-POST block for data exfiltration patterns
# Generate JARM fingerprints for known C2 infrastructure
Key analysis steps:
- Parse the malleable profile to extract HTTP-GET/POST URI patterns
- Extract User-Agent strings and custom headers for IDS signatures
- Identify sleep time and jitter for beaconing detection thresholds
- Scan suspect IPs with JARM to match known C2 fingerprint hashes
- Cross-reference extracted IOCs with network traffic logs
Examples
# Parse profile and extract detection indicators
from malleablec2 import Profile
p = Profile.from_file("cobaltstrike.profile")
print(p) # Reconstructed source
# JARM scan a suspect C2 server
import subprocess
result = subprocess.run(
["python3", "jarm.py", "suspect-server.com"],
capture_output=True, text=True
)
print(result.stdout)
# Compare fingerprint against known CS JARM hashes
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