ctf-malware
npx skills add https://github.com/ljagiello/ctf-skills --skill ctf-malware
Agent 安装分布
Skill 文档
CTF Malware & Network Analysis
Obfuscated Scripts
- Replace
eval/bashwithechoto print underlying code - Extract base64/hex blobs and analyze with
file - Common deobfuscation chain: base64 decode â gzip decode â reverse â base64 decode
Debian Package Analysis
ar -x package.deb # Unpack debian package
tar -xf control.tar.xz # Check control files
# Look for postinst scripts that execute payloads
Custom Crypto Protocols
- Stream ciphers may share keystream state for both directions
- Concatenate ALL payloads chronologically before decryption
- Look for hardcoded keys in
.rodata - ChaCha20 keystream extraction: Send large nullbytes payload (0 XOR anything = anything)
- Alternative: Pipe ciphertext from pcap directly into the binary
PCAP Analysis
tshark -r file.pcap -Y "tcp.stream eq X" -T fields -e tcp.payload
Look for C2 communication patterns on unusual ports (e.g., port 21 not for FTP).
Hex-Encoded Payloads
- Convert hex to bytes, try common transformations: subtract 1, XOR with key
JavaScript Deobfuscation
// Replace eval with console.log
eval = console.log;
// Then run the obfuscated code
// Common patterns
unescape() // URL decoding
String.fromCharCode() // Char codes
atob() // Base64
PowerShell Analysis
# Common obfuscation
-enc / -EncodedCommand # Base64 encoded
IEX / Invoke-Expression # Eval equivalent
[System.Text.Encoding]::Unicode.GetString([System.Convert]::FromBase64String($encoded))
PE Analysis
peframe malware.exe # Quick triage
pe-sieve # Runtime analysis
pestudio # Static analysis (Windows)
Sandbox Evasion Checks
Look for:
- VM detection (VMware, VirtualBox artifacts)
- Debugger detection (IsDebuggerPresent)
- Timing checks (sleep acceleration)
- Environment checks (username, computername)
- File/registry checks for analysis tools
Network Indicators
# Extract IPs/domains
strings malware | grep -E '[0-9]{1,3}\.[0-9]{1,3}\.[0-9]{1,3}\.[0-9]{1,3}'
strings malware | grep -E '[a-zA-Z0-9.-]+\.(com|net|org|io)'
# DNS queries
tshark -r capture.pcap -Y "dns.qry.name" -T fields -e dns.qry.name | sort -u
C2 Traffic Patterns
- Beaconing: regular intervals
- Domain generation algorithms (DGA)
- Encoded/encrypted payloads
- HTTP(S) with custom headers
- DNS tunneling
Junk Code Detection
Pattern: Obfuscation adds meaningless instructions around real code
Identification:
- NOP sleds, push/pop pairs that cancel
- Arithmetic that results in zero/identity
- Dead writes (register written but never read before next write)
- Unconditional jumps to next instruction
Filtering technique:
# Identify real calls by looking for patterns
# junk, junk, junk, CALL target, junk, junk
# Extract call targets, ignore surrounding noise
def extract_real_calls(disassembly):
calls = []
for instr in disassembly:
if instr.mnemonic == 'call' and not is_junk_target(instr.operand):
calls.append(instr)
return calls
.NET DNS-based C2
Pattern: Deobfuscated .NET malware with DNS C2
Analysis with dnSpy:
- Find network functions (TcpClient, DnsClient, etc.)
- Identify encoding/encryption wrappers
- Look for command dispatch (switch on opcode)
AsmResolver for programmatic analysis:
using AsmResolver.DotNet;
var module = ModuleDefinition.FromFile("malware.dll");
foreach (var type in module.GetAllTypes()) {
foreach (var method in type.Methods) {
// Analyze method body
}
}
AES-CBC in Malware
Common key derivation:
- MD5/SHA256 of hardcoded string
- Derived from timestamp or PID
- Password-based (PBKDF2)
Analysis approach:
from Crypto.Cipher import AES
from Crypto.Util.Padding import unpad
import hashlib
# Common pattern: key = MD5(password)
password = b"hardcoded_password"
key = hashlib.md5(password).digest()
# IV often first 16 bytes of ciphertext
iv = ciphertext[:16]
ct = ciphertext[16:]
cipher = AES.new(key, AES.MODE_CBC, iv)
plaintext = unpad(cipher.decrypt(ct), 16)
Password Rotation in C2
Pattern: C2 uses rotating passwords based on time/sequence
Analysis:
- Find password generation function
- Identify rotation trigger (time-based, message count)
- Sync your decryptor with the rotation
def get_current_password(timestamp):
# Password changes every hour
hour_bucket = timestamp // 3600
return hashlib.sha256(f"seed_{hour_bucket}".encode()).digest()
Malware Configuration Extraction
Common storage locations:
- .data section (hardcoded)
- Resources (PE resources, .NET resources)
- Registry keys written at install
- Encrypted config file dropped to disk
Extraction tools:
# PE resources
wrestool -x -t 10 malware.exe -o config.bin
# .NET resources
monodis --mresources malware.exe
# Strings in .rdata/.data
objdump -s -j .rdata malware.exe
Identifying Encryption Algorithms
By constants:
- AES:
0x637c777b,0x63636363(S-box) - ChaCha20:
expand 32-byte kor0x61707865 - RC4: Sequential S-box initialization
- TEA/XTEA:
0x9E3779B9(golden ratio)
By structure:
- Block cipher: Fixed-size blocks, padding
- Stream cipher: Byte-by-byte, no padding
- Hash: Mixing functions, rounds, constants
.NET Malware Analysis (C2 Extraction)
Tools: ILSpy, dnSpy, dotPeek
LimeRAT C2 extraction (Whisper Of The Pain):
- Open .NET binary in dnSpy
- Find configuration class with Base64 encoded string
- Identify decryption method (typically AES-256-ECB with derived key)
- Key derivation: MD5 of hardcoded string â first 15 + full 16 bytes + null = 32-byte key
- Decrypt: Base64 decode â AES-ECB decrypt â reveals C2 IP/domain
from Crypto.Cipher import AES
import hashlib, base64
key_source = '${8\',`d0}n,~@J;oZ"9a'
md5 = hashlib.md5(key_source.encode()).hexdigest()
# Key = md5[:30] + md5 + '\x00' (32 bytes total as hex â 16 bytes binary)
key = bytes.fromhex(md5[:30] + md5 + '00')[:32]
cipher = AES.new(key, AES.MODE_ECB)
plaintext = cipher.decrypt(base64.b64decode(encrypted_b64))
Telegram Bot API for Evidence Recovery
Pattern (Stomaker): Malware uses Telegram bot to exfiltrate stolen data.
Recover exfiltrated data via bot token:
# If you have the bot API token from malware source:
import requests
TOKEN = "bot_token_here"
# Get updates (message history)
r = requests.get(f"https://api.telegram.org/bot{TOKEN}/getUpdates")
# Download files sent to bot
file_id = "..."
r = requests.get(f"https://api.telegram.org/bot{TOKEN}/getFile?file_id={file_id}")
file_path = r.json()['result']['file_path']
requests.get(f"https://api.telegram.org/file/bot{TOKEN}/{file_path}")
RC4-Encrypted WebSocket C2 Traffic
Pattern (Tampered Seal): Malware uses WSS over non-standard port with RC4 encryption.
Decryption workflow:
- Identify C2 port from malware source (not standard 443)
- Remap port with
tcprewriteso Wireshark decodes TLS - Add RSA key for TLS decryption â reveals WebSocket frames
- Find RC4 key hardcoded in malware binary
- Decrypt each WebSocket payload with RC4 via CyberChef
Malware communication patterns:
- Registration message: hostname, OS, username, privileges
- Exfiltration: screenshots, keylog data, file contents
- Commands: reverse shell, file download, process list
PyInstaller + PyArmor Unpacking
# Step 1: Extract PyInstaller archive
python pyinstxtractor.py malware.exe
# Look for main .pyc file in extracted directory
# Step 2: If PyArmor-protected, use unpacker
# github.com/Svenskithesource/PyArmor-Unpacker
# Three methods available; choose based on PyArmor version
# Step 3: Clean up deobfuscated source
# Remove fake/dead-code functions (confusion code)
# Identify core encryption/exfiltration logic