Reverse Engineering Android Malware with JADX

When to Use

• A suspicious Android APK has been reported as malicious or flagged by mobile threat detection
• Analyzing Android banking trojans, spyware, SMS stealers, or adware samples
• Determining what data an app collects, where it sends it, and what permissions it abuses
• Extracting C2 server addresses, encryption keys, and configuration data from Android malware
• Understanding overlay attack mechanisms used by banking trojans

Do not use for analyzing obfuscated native (.so) libraries within APKs; use Ghidra or IDA for native ARM binary analysis.

Prerequisites

• JADX 1.5+ installed (download from https://github.com/skylot/jadx/releases)
• Android SDK with aapt2 and adb tools for APK inspection
• apktool for full APK disassembly including smali code and resources
• Python 3.8+ with androguard library for automated APK analysis
• Frida for dynamic instrumentation (optional, for runtime analysis)
• Isolated Android emulator (Genymotion or Android Studio AVD) without Google services

Workflow

Step 1: Extract APK Metadata and Permissions

Examine the APK structure and AndroidManifest.xml:

# Get APK basic info
aapt2 dump badging malware.apk

# Extract AndroidManifest.xml
apktool d malware.apk -o apk_extracted/ -f

# Analyze permissions with androguard
python3 << 'PYEOF'
from androguard.core.apk import APK

apk = APK("malware.apk")

print(f"Package:    {apk.get_package()}")
print(f"App Name:   {apk.get_app_name()}")
print(f"Version:    {apk.get_androidversion_name()}")
print(f"Min SDK:    {apk.get_min_sdk_version()}")
print(f"Target SDK: {apk.get_target_sdk_version()}")

# Dangerous permissions
dangerous_perms = {
    "android.permission.READ_SMS": "SMS theft",
    "android.permission.RECEIVE_SMS": "SMS interception",
    "android.permission.SEND_SMS": "Premium SMS fraud",
    "android.permission.READ_CONTACTS": "Contact harvesting",
    "android.permission.READ_CALL_LOG": "Call log theft",
    "android.permission.RECORD_AUDIO": "Audio surveillance",
    "android.permission.CAMERA": "Camera surveillance",
    "android.permission.ACCESS_FINE_LOCATION": "Location tracking",
    "android.permission.READ_PHONE_STATE": "Device fingerprinting",
    "android.permission.SYSTEM_ALERT_WINDOW": "Overlay attacks",
    "android.permission.BIND_ACCESSIBILITY_SERVICE": "Full device control",
    "android.permission.REQUEST_INSTALL_PACKAGES": "Sideloading apps",
    "android.permission.BIND_DEVICE_ADMIN": "Device admin abuse",
}

print("\nDangerous Permissions:")
for perm in apk.get_permissions():
    if perm in dangerous_perms:
        print(f"  [!] {perm}")
        print(f"      Risk: {dangerous_perms[perm]}")
    elif "android.permission" in perm:
        print(f"  [*] {perm}")

# Components
print("\nActivities:")
for act in apk.get_activities():
    print(f"  {act}")

print("\nServices:")
for svc in apk.get_services():
    print(f"  {svc}")

print("\nReceivers:")
for rcv in apk.get_receivers():
    print(f"  {rcv}")
PYEOF

Step 2: Decompile with JADX

Open the APK in JADX for Java/Kotlin source analysis:

# Open in JADX GUI
jadx-gui malware.apk

# Command-line decompilation for scripted analysis
jadx -d jadx_output/ malware.apk --show-bad-code

# Decompile with all options
jadx -d jadx_output/ malware.apk \
  --deobf \
  --deobf-min 3 \
  --deobf-max 64 \
  --show-bad-code \
  --threads-count 4

# The output directory structure:
# jadx_output/
#   sources/           <- Decompiled Java source code
#     com/malware/app/
#       MainActivity.java
#       C2Service.java
#       SMSReceiver.java
#   resources/         <- Decoded resources (layouts, strings, assets)
#     AndroidManifest.xml
#     res/
#     assets/

Step 3: Identify Malicious Functionality

Search for suspicious code patterns in decompiled sources:

# Search for network communication
grep -rn "HttpURLConnection\|OkHttpClient\|Retrofit\|Volley\|URL(" jadx_output/sources/

# Search for SMS operations
grep -rn "SmsManager\|getDefault().sendTextMessage\|SMS_RECEIVED" jadx_output/sources/

# Search for overlay attack code
grep -rn "SYSTEM_ALERT_WINDOW\|TYPE_APPLICATION_OVERLAY\|WindowManager.LayoutParams" jadx_output/sources/

# Search for accessibility service abuse
grep -rn "AccessibilityService\|onAccessibilityEvent\|performAction" jadx_output/sources/

# Search for data exfiltration
grep -rn "getDeviceId\|getSubscriberId\|getSimSerialNumber\|getLine1Number" jadx_output/sources/

# Search for crypto operations (key storage, encryption)
grep -rn "SecretKeySpec\|Cipher.getInstance\|AES\|DES\|RSA" jadx_output/sources/

# Search for dynamic code loading
grep -rn "DexClassLoader\|PathClassLoader\|loadDex\|loadClass" jadx_output/sources/

# Search for obfuscated strings and decryption
grep -rn "Base64.decode\|decrypt\|decipher\|xor" jadx_output/sources/

Step 4: Analyze C2 Communication

Trace the network communication logic:

# Automated C2 extraction from decompiled code
import os
import re

jadx_dir = "jadx_output/sources"

# Patterns for C2 URLs and IPs
url_pattern = re.compile(r'https?://[^\s"\'<>]+')
ip_pattern = re.compile(r'"(\d{1,3}\.\d{1,3}\.\d{1,3}\.\d{1,3})"')
base64_pattern = re.compile(r'"([A-Za-z0-9+/]{20,}={0,2})"')

urls = set()
ips = set()
b64_strings = set()

for root, dirs, files in os.walk(jadx_dir):
    for fname in files:
        if fname.endswith('.java'):
            filepath = os.path.join(root, fname)
            with open(filepath, 'r', errors='ignore') as f:
                content = f.read()

            for match in url_pattern.finditer(content):
                urls.add(match.group())
            for match in ip_pattern.finditer(content):
                ips.add(match.group(1))
            for match in base64_pattern.finditer(content):
                b64_strings.add(match.group(1))

print("URLs found:")
for u in urls:
    print(f"  {u}")

print("\nIP addresses:")
for ip in ips:
    print(f"  {ip}")

# Decode Base64 strings
import base64
print("\nDecoded Base64 strings:")
for b64 in b64_strings:
    try:
        decoded = base64.b64decode(b64).decode('utf-8', errors='ignore')
        if any(c.isprintable() for c in decoded) and len(decoded) > 3:
            print(f"  {b64[:30]}... -> {decoded[:100]}")
    except:
        pass

Step 5: Examine Native Libraries

Check for native code that may contain additional malicious logic:

# List native libraries in the APK
unzip -l malware.apk | grep "\.so$"

# Extract native libraries
unzip malware.apk "lib/*" -d apk_native/

# Check native library properties
file apk_native/lib/armeabi-v7a/*.so
readelf -d apk_native/lib/armeabi-v7a/*.so | grep NEEDED

# Strings from native libraries
strings apk_native/lib/armeabi-v7a/libpayload.so | grep -iE "(http|url|key|encrypt|password)"

# For deep native analysis, import into Ghidra:
# File -> Import -> Select .so file -> Select ARM architecture

Step 6: Document Analysis and Extract IOCs

Compile a comprehensive Android malware analysis report:

Analysis documentation should include:
- APK metadata (package name, version, signing certificate)
- Permission analysis with risk assessment
- Component analysis (activities, services, receivers, providers)
- Decompiled code walkthrough of malicious functions
- C2 communication protocol and endpoints
- Data exfiltration methods and targeted data types
- Persistence mechanisms (device admin, accessibility service)
- Evasion techniques (emulator detection, root detection)
- Extracted IOCs (C2 URLs, domains, IPs, signing certificate hash)

Key Concepts

Term	Definition
APK (Android Package)	Android application package format containing compiled DEX bytecode, resources, manifest, and native libraries
DEX Bytecode	Dalvik Executable format containing compiled Java/Kotlin code; JADX converts this back to readable Java source
Overlay Attack	Banking trojan technique displaying a fake UI layer over a legitimate banking app to steal credentials using SYSTEM_ALERT_WINDOW permission
Accessibility Service Abuse	Malware registering as an accessibility service to capture screen content, perform actions, and prevent uninstallation
Smali	Human-readable representation of DEX bytecode; intermediate representation between bytecode and Java used by apktool
Dynamic Code Loading	Loading additional DEX code at runtime using DexClassLoader to hide malicious functionality from static analysis
Device Admin Abuse	Malware requesting device administrator privileges to prevent uninstallation and perform device wipe threats

Tools & Systems

• JADX: Open-source DEX to Java decompiler providing GUI and CLI for Android APK analysis with deobfuscation support
• apktool: Tool for reverse engineering Android APK files to smali code and decoded resources
• androguard: Python framework for automated Android APK analysis including permission, component, and code analysis
• Frida: Dynamic instrumentation toolkit for hooking Java methods and native functions at runtime on Android
• MobSF (Mobile Security Framework): Automated mobile application security testing framework for static and dynamic analysis

Common Scenarios

Scenario: Analyzing an Android Banking Trojan

Context: A banking trojan APK is distributed via SMS phishing targeting customers of a specific bank. The sample needs analysis to identify targeted banks, C2 infrastructure, and data theft mechanisms.

Approach:

1. Extract APK metadata and identify requested permissions (SMS, accessibility, overlay, device admin)
2. Decompile with JADX and search for overlay activity classes that mimic banking app UIs
3. Identify the list of targeted banking apps by searching for package name lists in the code
4. Trace the SMS interception receiver to understand how 2FA codes are stolen
5. Follow the C2 communication code to extract server URLs and command protocol
6. Check for web injection configuration files in assets/ directory
7. Extract all IOCs and document the complete attack chain

Pitfalls:

• Not deobfuscating class and method names before analysis (use JADX --deobf flag)
• Missing dynamically loaded DEX files downloaded after installation
• Ignoring native .so libraries that may contain the actual C2 logic or encryption routines
• Overlooking assets/ directory which may contain encrypted configuration or web injects

Output Format

ANDROID MALWARE ANALYSIS REPORT
==================================
APK File:         update_bank.apk
Package:          com.android.systemupdate
SHA-256:          e3b0c44298fc1c149afbf4c8996fb924...
Version:          1.2.3
Min SDK:          21 (Android 5.0)
Signing Cert:     SHA-256: abc123... (self-signed)

CLASSIFICATION
Family:           Anubis Banking Trojan
Type:             Banking Trojan / SMS Stealer / Keylogger

DANGEROUS PERMISSIONS
[!] RECEIVE_SMS          - Intercepts incoming SMS (2FA theft)
[!] READ_SMS             - Reads SMS messages
[!] SEND_SMS             - Sends premium SMS
[!] SYSTEM_ALERT_WINDOW  - Overlay attacks on banking apps
[!] BIND_ACCESSIBILITY   - Full device control
[!] BIND_DEVICE_ADMIN    - Prevents uninstallation

MALICIOUS COMPONENTS
Service:    com.android.systemupdate.C2Service (C2 communication)
Receiver:   com.android.systemupdate.SmsReceiver (SMS interception)
Activity:   com.android.systemupdate.OverlayActivity (credential overlay)

TARGETED APPS (23 banking apps)
com.bank.example1, com.bank.example2, ...

C2 INFRASTRUCTURE
Primary:    hxxps://c2-server[.]com/api/bot
Fallback:   hxxps://backup-c2[.]net/api/bot
Protocol:   HTTPS POST with JSON body
Bot ID:     MD5(IMEI + Build.SERIAL)

EXTRACTED IOCs
Domains:    c2-server[.]com, backup-c2[.]net
IPs:        185.220.101[.]42
URLs:       hxxps://c2-server[.]com/api/bot
            hxxps://c2-server[.]com/api/injects
Cert Hash:  abc123def456...

Verification Criteria

Confirm successful execution by validating:

• [ ] All prerequisite tools and access requirements are satisfied
• [ ] Each workflow step completed without errors
• [ ] Output matches expected format and contains expected data
• [ ] No security warnings or misconfigurations detected
• [ ] Results are documented and evidence is preserved for audit

Compliance Framework Mapping

This skill supports compliance evidence collection across multiple frameworks:

• SOC 2: CC7.2 (Anomaly Detection), CC7.4 (Incident Response)
• ISO 27001: A.12.2 (Malware Protection), A.16.1 (Security Incident Management)
• NIST 800-53: SI-3 (Malicious Code Protection), IR-4 (Incident Handling)
• NIST CSF: DE.CM (Continuous Monitoring), RS.AN (Analysis)

Claw GRC Tip: When this skill is executed by a registered agent, compliance evidence is automatically captured and mapped to the relevant controls in your active frameworks.

Deploying This Skill with Claw GRC

Agent Execution

Register this skill with your Claw GRC agent for automated execution:

# Install via CLI
npx claw-grc skills add reverse-engineering-android-malware-with-jadx

# Or load dynamically via MCP
grc.load_skill("reverse-engineering-android-malware-with-jadx")

Audit Trail Integration

When executed through Claw GRC, every step of this skill generates tamper-evident audit records:

• SHA-256 chain hashing ensures no step can be modified after execution
• Evidence artifacts (configs, scan results, logs) are automatically attached to relevant controls
• Trust score impact — successful execution increases your agent's trust score

Continuous Compliance

Schedule this skill for recurring execution to maintain continuous compliance posture. Claw GRC monitors for drift and alerts when re-execution is needed.