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Introduction:
Modern Android malware no longer hides solely in decompiled Java code; threat actors embed malicious logic in native libraries, dynamically loaded DEX files, and runtime-decrypted strings that evade static analysis. For penetration testers, this means checking OWASP MASVS checkboxes is insufficient – you must simulate real-world scenarios where a banking trojan like Cerberus or SharkBot shares the device and uses overlay attacks, keylogging, and SMS interception to compromise your app.
Learning Objectives:
- Detect and bypass obfuscated string decryption using dynamic instrumentation with Frida.
- Simulate and mitigate “type overlay” attacks that bypass traditional blocking mechanisms.
- Validate root detection against modern Magisk + Zygisk setups, not just legacy `su` file checks.
You Should Know
- Extracting the Unseen: JADX and Native Library Analysis
Static analysis with JADX reveals the Java layer, but advanced malware stores payloads in native `.so` libraries or encrypted strings that only decrypt at runtime. Start by pulling the APK apart, then inspect native code and runtime behaviors.
Step‑by‑step guide:
1. Decompile the APK with JADX:
`jadx -d output/ suspicious.apk`
- Navigate to `output/resources/lib/` – check for
armeabi-v7a/x86native libraries. - Use `readelf` (Linux) or `objdump` to inspect symbols:
`readelf -Ws libmalware.so | grep -i decrypt`
- Look for `System.loadLibrary()` calls in the Java code – they indicate native entry points.
- Identify dynamically loaded DEX files using `DexClassLoader` – extract and analyze them separately with JADX.
Why it matters: Static analysis alone misses runtime behavior. For Windows-based analysts, use `adb pull /data/app/
2. Dynamic Instrumentation with Frida: Hooking Decryption Routines
Frida allows you to hook native and Java functions in real time, dumping cleartext payloads and tracing C2 logic that static analysis cannot reach. This simulates what an active malware implant would do.
Step‑by‑step guide:
- Install Frida on your Linux/macOS/Windows machine and the Frida server on the rooted Android device:
`frida-server -D `
- Write a Frida script to hook a suspected decryption function (example for a Java method):
Java.perform(function() { var StringClass = Java.use('java.lang.String'); var MalwareClass = Java.use('com.malware.Decryptor'); MalwareClass.decrypt.implementation = function(encrypted) { console.log('[+] Encrypted: ' + encrypted); var plain = this.decrypt(encrypted); console.log('[+] Plaintext: ' + plain); return plain; }; });
3. Attach to the target app:
`frida -U -l decrypt_hook.js com.target.app`
- For native functions, hook using `Interceptor.attach()` on exported symbols.
Pro tip: When dealing with packed DEX files, use `Java.enumerateClassLoaders()` to find the correct loader before hooking.
- Defeating Overlay Attacks: Testing Your App Against Type Overlay
Traditional overlay attacks use `TYPE_APPLICATION_OVERLAY` (requires `SYSTEM_ALERT_WINDOW` permission). However, Mahmoud Bettouch points out that “type overlay” variants cannot be blocked by standard defenses. These use accessibility services or rogue input methods to draw over your app.
Step‑by‑step guide to test mitigation:
- Check if your app can be overlayed: On a rooted device, install an overlay simulator like “Overlay Tester” or use Frida to inject a fake overlay window.
2. Simulate a type overlay attack manually:
- Enable “Display over other apps” for a malicious test app.
- Launch your target app and trigger the overlay.
- Attempt to capture input using Android’s
InputMethodManager.
3. Mitigation commands (Linux/Android):
- Disable overlay permission for untrusted apps via ADB:
`adb shell pm revoke com.malicious.app android.permission.SYSTEM_ALERT_WINDOW`
- Implement touch event filtering in your app: override `onTouchEvent()` and check for window focus changes.
- Use the `android:filterTouchesWhenObscured=”true”` attribute in your app’s layout XML to discard touches when an overlay is present.
Pentester’s note: Always test with `setFilterTouchesWhenObscured(true)` enabled – many apps forget this.
4. Root Detection Evasion: Catching Magisk + Zygisk
Legacy root detection checks for `/system/bin/su` or Build.TAGS. Modern malware uses Magisk with Zygisk to hide root. As a tester, you must verify that your app’s root detection actually triggers on a properly hidden Magisk environment.
Step‑by‑step guide:
- Set up a test device with Magisk + Zygisk enabled and the “Shamiko” module for hiding.
- Run these Linux/Android detection commands inside your app’s context:
– Check for Magisk’s SELinux context: `ls -Z /data/adb/magisk/`
– Detect Zygisk injection: scan `/proc/self/maps` for `libzygisk.so`
– Use native code to call `fopen(“/sbin/.magisk”, “r”)`
3. Write a simple detection script (C snippet for NDK):
int check_magisk() {
FILE fp = fopen("/data/adb/magisk", "r");
if (fp != NULL) { fclose(fp); return 1; }
return 0;
}
4. Bypass for pentesting: Use Frida to hook `fopen` and `access` system calls, returning `-1` for Magisk paths.
Key takeaway: If your detection only checks `su` binary, it fails against Magisk. Include multiple heuristics like property checks (ro.debuggable, ro.build.tags).
5. Service Abuse & Permission Hardening: Beyond MASVS
Banking trojans abuse powerful permissions: overlay drawing, accessibility services, and SMS read/send. As a defender, you must audit which permissions your app actually needs and test how malware could abuse them from a co‑resident app.
Step‑by‑step hardening guide:
- List all dangerous permissions currently granted to your app (Windows/Linux ADB):
`adb shell dumpsys package com.your.app | grep -A 50 “granted permissions”` - Review each against the principle of least privilege:
– Does it need RECEIVE_SMS? If not, remove from manifest.
– Can `BIND_ACCESSIBILITY_SERVICE` be replaced with NotificationListenerService?
3. Test abuse scenarios:
- Install a dummy malware app that requests overlay and accessibility.
- Attempt to capture keystrokes while your app is in the foreground.
- Implement runtime permission re‑verification every 30 seconds, not just at install time. Example code:
if (checkSelfPermission(Manifest.permission.SYSTEM_ALERT_WINDOW) != PackageManager.PERMISSION_GRANTED) { // Show warning and kill sensitive activities } - Windows-specific note: Use `adb shell pm list permissions -g -d` to see dangerous permission groups from a Windows terminal.
-
Simulating Banking Trojan Behavior: Keystroke Capture and SMS Interception
To truly assess resilience, mimic Cerberus or Anatsa: deploy a Frida script that captures keystrokes and intercepts SMS messages while your target app runs.
Step‑by‑step simulation:
1. Keylogging hook (Frida JavaScript):
Java.perform(function() {
var EditText = Java.use('android.widget.EditText');
EditText.setText.implementation = function(text) {
console.log('[bash] ' + text);
return this.setText(text);
};
});
2. SMS interception simulation: On a rooted device, use `adb shell content query –uri content://sms/` to read SMS database. Then create a Frida script that hooks SmsManager.sendTextMessage.
3. Mitigation: Encrypt sensitive inputs at the View level and avoid storing SMS data in plaintext. Use Android’s `setTransformationMethod` with a custom filter.
4. Test command – Linux: `adb logcat | grep -i “keylog”` to monitor your hooks.
Real‑world impact: Many banking apps still fail this test – they assume the OS protects input fields, but a trojan with accessibility can read anything.
7. Real-World Pentest Checklist for Android Apps
Combine all the above into a repeatable workflow that goes beyond compliance checklists.
Step‑by‑step checklist:
- [ ] Static + dynamic analysis: JADX for Java, Frida for runtime strings.
- [ ] Overlay resilience: Enable `filterTouchesWhenObscured` and test with a type overlay.
- [ ] Root detection validation: Run on Magisk + Zygisk with hiding enabled.
- [ ] Permission audit: Remove unnecessary dangerous permissions.
- [ ] Keylogging simulation: Frida hook on EditText and accessibility events.
- [ ] Native lib inspection: Use `readelf` and `objdump` for encrypted strings.
- [ ] C2 communication trace: Hook network APIs (OkHttp, HttpURLConnection) to spot beaconing even when encrypted.
Automation tip: Use `frida-tools` with a script that logs all decrypted strings and network calls for 10 minutes of UI interaction.
What Undercode Say
- Key Takeaway 1: Attackers are creative with native layers and runtime decryption; pentesters must adopt dynamic instrumentation (Frida) as a default tool, not an optional extra.
- Key Takeaway 2: Overlay attacks persist into 2026 because users blindly tap “Allow” and type overlays bypass traditional blocking – the only real defense is touch filtering and runtime permission re‑checks.
Analysis:
The post highlights a critical gap in most Android pentests: they treat the app in isolation, not as part of an infected device ecosystem. Dimitris Pallis’s workflow – JADX then Frida – reflects how real malware analysts operate. Mahmoud Bettouch’s comment about unblockable “type overlays” is a wake‑up call: even apps that set `filterTouchesWhenObscured` may be vulnerable to accessibility‑based overlays. The solution lies in defense‑in‑depth: combine touch filtering with continuous permission validation and input encryption. Furthermore, root detection must evolve to catch Magisk’s Zygisk, which hides processes and mounts. Pentesters who only check for `/system/bin/su` are missing the majority of modern rooted test devices. Ultimately, the post urges a mindset shift – from compliance to adversary simulation.
Prediction
- -1 Overlay attacks will become fully invisible as malware adopts Android’s `TYPE_ACCESSIBILITY_OVERLAY` and system‑level injection, making detection near impossible without kernel‑level monitoring.
- +1 Frida‑based continuous testing pipelines will integrate into DevSecOps, allowing apps to be automatically tested against runtime decryption and overlay hooks before release.
- -1 Legacy root detection will completely fail as Magisk moves to boot‑loader level hiding; apps will need hardware‑backed attestation (Play Integrity API) to remain secure.
- +1 Google will enforce runtime permission re‑verification for banking apps in the Play Store, driving down service abuse by 40% within 18 months.
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