ctf-malware
Skill5 starsChanged 8 months agoMITView on GitHub
Provides malware analysis and network traffic techniques for CTF challenges. Use when analyzing obfuscated scripts, malicious packages, custom crypto protocols, C2 traffic, PE/.NET binaries, RC4/AES encrypted communications, YARA rules, shellcode analysis, memory forensics for malware (Volatility malfind, process injection detection), anti-analysis techniques (VM/sandbox detection, timing evasion, API hashing, process injection, environment checks), or extracting malware configurations and indicators of compromise.
- Installs packages
4 other projects use a version of this, 2 of them edited.
Adopted by
Steady: 0 new projects took it in the last 4 weeks, none the 4 weeks before.thin data
Most recently taken up by
- TaiMaBenJi/taima-skillsedited, first seen Oct 11, 2026
- wgpsec/AboutSecuritytheir own version, first seen May 21, 2026
- MateoBogo/CLEAVEedited, first seen Apr 23, 2026
- ljagiello/ctf-skillsword for word, first seen Mar 28, 2026
Other versions4 projects use a version of this.
Word for word · 1
- ljagiello/ctf-skills★ 3.7k100% same
Edited · 2
- MateoBogo/CLEAVE★ 437% same
- TaiMaBenJi/taima-skills★ 199% same
Wrote their own version · 1
- wgpsec/AboutSecurity★ 1.8ksame name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository12 other files it gives its agents.
- AGENTS.mdAGENTS.md
- ctf-ai-mlSkill
- ctf-cryptoSkill
- ctf-forensicsSkill
- ctf-miscSkill
- ctf-osintSkill
- ctf-pwnSkill
- ctf-reverseSkill
- ctf-similar-searchSkill
- ctf-webSkill
- ctf-writeupSkill
- solve-challengeSkill
The file
We split this skill into the rules it gives an agent
8 rules. About 0 are common, 2 are distinctive, and 6 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈2
Distinctive · estimate
This author's own choices. Worth a look.
6
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 50
If the sample is really just a normal crackme, packed challenge binary, or custom VM with no malware behavior, switch to /ctf-reverse.
- Very specific: line 51
If the main job is network reconstruction, disk carving, or host artifact recovery, switch to /ctf-forensics.
- Very specific: line 52
If the challenge turns into public attribution or infrastructure tracing, switch to /ctf-osint.
- Very specific: line 97
Look for C2 on unusual ports.
- Distinctive: line 132
Use dnSpy/ILSpy for decompilation.
- Distinctive: line 136
Check .data section, PE/.NET resources, registry keys, encrypted config files.
- Very specific: line 156
Use bot token from malware source to call getUpdates and getFile APIs.
- Very specific: line 168
Write YARA rules to match byte patterns, strings, and regex against files or memory dumps.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
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.
Prerequisites
Python packages (all platforms):
pip install yara-python pefile capstone oletools unicorn pycryptodome \
volatility3 dissect.cobaltstrikeLinux (apt):
apt install strace ltrace tshark binwalk binutilsmacOS (Homebrew):
brew install wireshark binwalk binutils ghidraManual install:
- dnSpy — GitHub, .NET decompiler (Windows)
MCP servers (optional): IDA Pro MCP / Ghidra MCP (unpacking, config extraction), WinDbg MCP (svnscha/mcp-windbg) for dynamic analysis, JADX MCP for Android — see tools-mcp.md. Run malware only in an isolated, disposable VM.
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), trojanized plugin analysis with custom alphabet C2 decoding
- 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
- tools-mcp.md - MCP server integration for malware: IDA/Ghidra MCP for unpacking and config/decryptor extraction, WinDbg MCP for dynamic debugging (RWX region hunting, in-memory C2 strings, live
VirtualAlloc/CreateRemoteThreadbreakpoints,.writemempayload dumping to skip the packer), JADX MCP for Android malware — pseudocode-first, isolated-VM safety note
When to Pivot
- If the sample is really just a normal crackme, packed challenge binary, or custom VM with no malware behavior, switch to
/ctf-reverse. - If the main job is network reconstruction, disk carving, or host artifact recovery, switch to
/ctf-forensics. - If the challenge turns into public attribution or infrastructure tracing, switch to
/ctf-osint.
Quick Start Commands
# Static analysis
file suspicious_file
strings -n 8 suspicious_file | head -50
xxd suspicious_file | head -20
# PE analysis
python3 -c "import pefile; pe=pefile.PE('mal.exe'); print(pe.dump_info())" | head
peframe mal.exe
# Dynamic analysis (sandboxed!)
strace -f -s 200 ./suspicious 2>&1 | head -100
ltrace ./suspicious 2>&1 | head -50
# Network indicators
strings suspicious_file | grep -E '[0-9]{1,3}\.[0-9]{1,3}\.[0-9]{1,3}\.[0-9]{1,3}'
strings suspicious_file | grep -iE 'http|ftp|ws://'
# YARA scan
yara -r rules.yar suspicious_fileObfuscated Scripts
- Replace
eval/bashwithechoto print underlying code; extract base64/hex blobs and analyze withfile. See scripts-and-obfuscation.md.
JavaScript & PowerShell Deobfuscation
- JS: Replace
evalwithconsole.log, decodeunescape(),atob(),String.fromCharCode(). - PowerShell: Decode
-encbase64, replaceIEXwith output. See scripts-and-obfuscation.md.
Junk Code Detection
- NOP sleds, push/pop pairs, dead writes, unconditional jumps to next instruction. Filter to extract real
calltargets. See scripts-and-obfuscation.md.
PCAP & Network Analysis
tshark -r file.pcap -Y "tcp.stream eq X" -T fields -e tcp.payloadLook for C2 on unusual ports. Extract IPs/domains with strings | grep. See c2-and-protocols.md.
Custom Crypto Protocols
- Stream ciphers share keystream state for both directions; concatenate ALL payloads chronologically.
- ChaCha20 keystream extraction: send nullbytes (0 XOR anything = anything). See c2-and-protocols.md.
C2 Traffic Patterns
- Beaconing, DGA, DNS tunneling, HTTP(S) with custom headers, encoded payloads. See c2-and-protocols.md.
RC4-Encrypted WebSocket C2
- Remap port with
tcprewrite, add RSA key for TLS decryption, find RC4 key in binary. See c2-and-protocols.md.
Identifying Encryption Algorithms
- AES:
0x637c777bS-box; ChaCha20:expand 32-byte k; TEA/XTEA:0x9E3779B9; RC4: sequential S-box init. See c2-and-protocols.md.
AES-CBC in Malware
- Key = MD5/SHA256 of hardcoded string; IV = first 16 bytes of ciphertext. See c2-and-protocols.md.
PE Analysis
peframe malware.exe # Quick triage
pe-sieve # Runtime analysis
pestudio # Static analysis (Windows)See pe-and-dotnet.md.
.NET Malware Analysis
- Use dnSpy/ILSpy for decompilation; AsmResolver for programmatic analysis. LimeRAT C2: AES-256-ECB with MD5-derived key. See pe-and-dotnet.md.
Malware Configuration Extraction
- Check .data section, PE/.NET resources, registry keys, encrypted config files. See pe-and-dotnet.md.
Sandbox Evasion Checks
- VM detection, debugger detection, timing checks, environment checks, analysis tool detection. See pe-and-dotnet.md.
Anti-Analysis Techniques
VM detection (CPUID, MAC prefix, registry, disk size), timing evasion (sleep/RDTSC sandbox detection), API hashing (ROR13/DJB2/CRC32 + hashdb lookup), process injection (hollowing, APC, CreateRemoteThread), environment checks. See scripts-and-obfuscation.md.
Trojanized Plugin Analysis
Diff malicious plugin against official release to find injected code in try/except blocks. Custom alphabet rotation (C[(C.index(ch) - offset) % len(C)]) decodes C2 domain, XOR decodes endpoint path. See scripts-and-obfuscation.md.
PyInstaller + PyArmor Unpacking
pyinstxtractor.pyto extract, PyArmor-Unpacker for protected code. See pe-and-dotnet.md.
Telegram Bot Evidence Recovery
- Use bot token from malware source to call
getUpdatesandgetFileAPIs. See c2-and-protocols.md.
Debian Package Analysis
ar -x package.deb && tar -xf control.tar.xz # Check postinst scriptsSee scripts-and-obfuscation.md.
YARA Rules for Malware Detection
Write YARA rules to match byte patterns, strings, and regex against files or memory dumps. Detect XOR loops ({31 ?? 80 ?? ?? 4? 75}), base64 blobs, encoded PowerShell. Use yarac to compile for faster scanning. See scripts-and-obfuscation.md.
Shellcode Analysis
Disassemble with objdump -b binary -m i386:x86-64, emulate with Unicorn Engine (hook syscalls safely), or use Capstone for programmatic disassembly. Look for XOR decoder stubs. See scripts-and-obfuscation.md.
Memory Forensics for Malware
vol windows.malfind detects injected code (PAGE_EXECUTE_READWRITE without mapped file). windows.pstree reveals suspicious parent-child relationships. YARA scan memory with windows.vadyarascan.VadYaraScan. See scripts-and-obfuscation.md.
Network Indicators Quick Reference
strings malware | grep -E '[0-9]{1,3}\.[0-9]{1,3}\.[0-9]{1,3}\.[0-9]{1,3}'
tshark -r capture.pcap -Y "dns.qry.name" -T fields -e dns.qry.name | sort -uDoes it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

