Ctf-skills ctf-malware
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.
git clone https://github.com/ljagiello/ctf-skills
T=$(mktemp -d) && git clone --depth=1 https://github.com/ljagiello/ctf-skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/ctf-malware" ~/.claude/skills/ljagiello-ctf-skills-ctf-malware && rm -rf "$T"
ctf-malware/SKILL.mdCTF 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.cobaltstrike
Linux (apt):
apt install strace ltrace tshark binwalk binutils
macOS (Homebrew):
brew install wireshark binwalk binutils ghidra
Manual install:
- dnSpy — GitHub, .NET decompiler (Windows)
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
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_file
Obfuscated Scripts
- Replace
/eval
withbash
to print underlying code; extract base64/hex blobs and analyze withecho
. See scripts-and-obfuscation.md.file
JavaScript & PowerShell Deobfuscation
- JS: Replace
witheval
, decodeconsole.log
,unescape()
,atob()
.String.fromCharCode() - PowerShell: Decode
base64, replace-enc
with output. See scripts-and-obfuscation.md.IEX
Junk Code Detection
- NOP sleds, push/pop pairs, dead writes, unconditional jumps to next instruction. Filter to extract real
targets. See scripts-and-obfuscation.md.call
PCAP & Network Analysis
tshark -r file.pcap -Y "tcp.stream eq X" -T fields -e tcp.payload
Look 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
, add RSA key for TLS decryption, find RC4 key in binary. See c2-and-protocols.md.tcprewrite
Identifying Encryption Algorithms
- AES:
S-box; ChaCha20:0x637c777b
; TEA/XTEA:expand 32-byte k
; RC4: sequential S-box init. See c2-and-protocols.md.0x9E3779B9
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
to extract, PyArmor-Unpacker for protected code. See pe-and-dotnet.md.pyinstxtractor.py
Telegram Bot Evidence Recovery
- Use bot token from malware source to call
andgetUpdates
APIs. See c2-and-protocols.md.getFile
Debian Package Analysis
ar -x package.deb && tar -xf control.tar.xz # Check postinst scripts
See 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
vol3 windows.malfind detects injected code (PAGE_EXECUTE_READWRITE without mapped file). windows.pstree reveals suspicious parent-child relationships. YARA scan memory with yarascan.YaraScan. 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 -u