Ctf malware
CLEAVE: skills-based CTF agents for mechanics-first challenge triage and exploit orchestration.
npx -y skills add MateoBogo/CLEAVE --skill ctf-malwareAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
2 things to look at
- no licenseNo license file was found in the repository. Code published without one is not open source by default, so using it at work is a question for whoever answers licensing questions where you are.
- 4 stars4 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.
What its author says it does
Copied from the file, not written here
Malware & network analysis: obfuscated JS/PowerShell/VBA, PE/.NET analysis, PyInstaller/PyArmor, custom C2 protocols (RC4, AES, DNS), YARA rules, shellcode, memory-forensics IOCs, anti-sandbox/anti-VM bypass.
The file declares its own license as MIT. That is the author’s claim about this one file, and it is not the same thing as the license GitHub reports for the repository, which is listed with the other numbers below.
SKILL.md
3.6 KB, as published. Nobody here has run it
CTF Malware & Network Analysis
Quick reference for malware analysis CTF challenges. Each technique has a one-liner here; see supporting files for full details with code.
Additional Resources
- scripts-and-obfuscation.md - JavaScript deobfuscation, PowerShell analysis, eval/base64 decoding, junk code detection, hex payloads, Debian package analysis, dynamic analysis techniques (strace/ltrace, network monitoring, memory string extraction, automated sandbox execution), YARA rules for malware detection, shellcode analysis (Unicorn Engine, Capstone), memory forensics for malware (Volatility 3 malfind, process injection detection), anti-analysis techniques (VM detection, timing evasion, API hashing, process injection)
- c2-and-protocols.md - C2 traffic patterns, custom crypto protocols, RC4 WebSocket, DNS-based C2, network indicators, PCAP analysis, AES-CBC, encryption ID, Telegram bot recovery, Poison Ivy RAT Camellia decryption
- pe-and-dotnet.md - PE analysis (peframe, pe-sieve, pestudio), .NET analysis (dnSpy, AsmResolver), LimeRAT extraction, sandbox evasion, malware config extraction, PyInstaller+PyArmor
Pattern Recognition Index
Dispatch on byte/file signals, never the sample's reputation.
| Signal | Technique → file |
|---|---|
File starts with PK + contains package.json + .vsix extension | VSCode extension activation-event exfil → scripts-and-obfuscation.md |
High-entropy extension.js/index.js > 50 KB with child_process | JS obfuscator.io / JSFuck deobfuscation → scripts-and-obfuscation.md |
PowerShell -enc <b64> or IEX in parent process logs | PS script decode + reflection assembly → scripts-and-obfuscation.md |
| PCAP with custom TCP port, payload bytes distributed uniformly | Custom crypto / RC4 / AES session key recovery → c2-and-protocols.md |
PCAP with DNS TXT records carrying base32/64 blobs | DNS-based C2 exfil → c2-and-protocols.md |
| PCAP where specific User-Agent receives non-default responses | UA-gated C2 path-hex-XOR → (see ctf-forensics/network-advanced.md) |
PE32/PE64 with .text sections having packer signatures (UPX, VMProtect, Themida) | Unpacking + dump-after-decrypt → pe-and-dotnet.md |
| .NET assembly with obfuscated strings + reflection calls | dnSpy + de4dot + string decryption → pe-and-dotnet.md |
PyInstaller binary (MEIPASS, _MEIxxxx strings) | pyinstxtractor + pycdc → pe-and-dotnet.md |
Process-injection IoCs in memory dump (RWX allocations, NtUnmapViewOfSection) | Volatility malfind + process hollowing detection → scripts-and-obfuscation.md |
Anti-VM checks (cpuid hypervisor bit, RDTSC timing, specific drivers) | VM-detection bypass in analysis sandbox → scripts-and-obfuscation.md |
| WebSocket frame with visible RC4 key-setup or KSA signatures | RC4 WebSocket reversing → c2-and-protocols.md |
Recognize the artefact or protocol pattern. The sample's name is not a signal.
For inline snippets and quick-reference tables, see quickref.md. The Pattern Recognition Index above is the dispatch table — always consult it first.