ctf-malware

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Malware and network analysis techniques for CTF challenges. Use when analyzing obfuscated scripts, malicious packages, custom protocols, or C2 traffic.

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NPX Install

npx skill4agent add ljagiello/ctf-skills ctf-malware

SKILL.md Content

CTF Malware & Network Analysis

Obfuscated Scripts

  • Replace
    eval
    /
    bash
    with
    echo
    to print underlying code
  • Extract base64/hex blobs and analyze with
    file
  • Common deobfuscation chain: base64 decode → gzip decode → reverse → base64 decode

Debian Package Analysis

bash
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

bash
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

javascript
// 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

powershell
# Common obfuscation
-enc / -EncodedCommand  # Base64 encoded
IEX / Invoke-Expression # Eval equivalent
[System.Text.Encoding]::Unicode.GetString([System.Convert]::FromBase64String($encoded))

PE Analysis

bash
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

bash
# 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:
python
# 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:
  1. Find network functions (TcpClient, DnsClient, etc.)
  2. Identify encoding/encryption wrappers
  3. Look for command dispatch (switch on opcode)
AsmResolver for programmatic analysis:
csharp
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:
python
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:
  1. Find password generation function
  2. Identify rotation trigger (time-based, message count)
  3. Sync your decryptor with the rotation
python
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:
bash
# 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 k
    or
    0x61707865
  • 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):
  1. Open .NET binary in dnSpy
  2. Find configuration class with Base64 encoded string
  3. Identify decryption method (typically AES-256-ECB with derived key)
  4. Key derivation: MD5 of hardcoded string → first 15 + full 16 bytes + null = 32-byte key
  5. Decrypt: Base64 decode → AES-ECB decrypt → reveals C2 IP/domain
python
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 → 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:
python
# 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:
  1. Identify C2 port from malware source (not standard 443)
  2. Remap port with
    tcprewrite
    so Wireshark decodes TLS
  3. Add RSA key for TLS decryption → reveals WebSocket frames
  4. Find RC4 key hardcoded in malware binary
  5. 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

bash
# 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