android-pentesting-skill

name	Android-Pentesting-Skill
description	Comprehensive Android APK security audit with static analysis, dynamic instrumentation, source-to-sink tracing, IPC/component abuse analysis, and CVSS 4.0 reporting. Covers decompilation, manifest analysis, deep links and intent injection, secrets detection, crypto analysis, Frida/Objection integration, and APK repackaging. Use when user says "audit APK", "analyze android app", "mobile pentest", "APK security", "decompile APK", "android vulnerability assessment", "reverse engineer android", "modify APK", "intent injection", "deep link abuse", "bypass SSL pinning", "bypass root detection", or provides an APK for security review, decompiled Android sources, or decoded resources.
license	Apache-2.0
allowed-tools	Bash(apktool:*) Bash(jadx:*) Bash(aapt2:*) Bash(d8:*) Bash(frida:*) Bash(objection:*) Bash(adb:*) Bash(keytool:*) Bash(zipalign:*) Bash(apksigner:*) Bash(python3:*) Bash(apkid:*) Read Write Edit Glob Grep
metadata	{"author":"DragonJAR SAS","version":"1.7.0","category":"mobile-security","tags":["android","apk-audit","static-analysis","dynamic-analysis","frida","objection","security-pentest","cvss-scoring","reverse-engineering","ai-powered","ai-analysis"]}

Android APK Security Audit

Overview

Deterministic 6-phase static analysis + optional dynamic confirmation workflow. Remove noise early, keep the package scope tight. Only report vulnerabilities where source, propagation, and sink are understood or clearly marked as needing dynamic confirmation.

When to Use

• User provides an APK file for security review
• User asks to analyze decompiled Android source code
• User needs to modify or repackage an APK for testing
• User wants mobile security testing or vulnerability assessment
• User needs help testing exported components, deep links, or intent injection
• User mentions Android reverse engineering or malware analysis

Critical Rules

1. NEVER report bare grep hits without traced context
2. ALWAYS constrain searches to the app namespace (avoid library noise)
3. STOP and report immediately if decoding fails
4. ALWAYS use imperative language in findings
5. NEVER skip validation — if unsure, mark as "Needs Dynamic Confirmation"
6. ALWAYS provide concrete PoC (adb command, Frida hook, or malicious intent)
7. NEVER duplicate findings for the same root cause

Quality Note: Take your time to analyze thoroughly. Quality is more important than speed. Do not skip validation steps — a false positive is worse than a missed finding.

Execution Model

Tools to use: bash, write, edit, read, glob, grep for core workflow.

Toolchain Requirements

Before starting, verify these tools are installed:

• APKTool 3.0.2+ (apktool --version) — aapt2-only mode; requires Java 17+
• JADX 1.5.5+ (jadx --version)
• Android SDK Platform Tools 36.0.2 (adb, fastboot)
• Android SDK Build Tools 36.0.0 (apksigner, zipalign, aapt2, d8)
• Frida 17.x (frida --version) — ⚠️ Frida-server on device must match the frida core version (the frida Python package), NOT frida-tools
• Objection 1.12.5+ (objection --version)
• APKiD 3.1.0+ (apkid --version)

Run scripts/06-setup/preflight-check.sh (bash), scripts/06-setup/preflight-check.py (universal, JSON output), or scripts/06-setup/preflight-check.ps1 (PowerShell) to verify all tools. See references/environment-setup.md for installation instructions.

---

AI-Powered Analysis

This skill includes AI-powered analysis capabilities. The AI model running this skill has built-in code analysis - use it strategically to enhance findings.

When to Use AI

• Analyzing decompiled code for semantic vulnerabilities
• Tracing complex data flows (source-to-sink)
• Generating Proof-of-Concept exploits
• Filtering false positives from automated scans
• Understanding obfuscated code behavior
• Enhancing report quality and context

How to Use AI

1. Analyze specific code sections: Don't ask AI to find ALL vulnerabilities - target specific suspicious code
2. Provide context: Include the full function/class, not just snippets
3. Ask for CVSS scoring: Request severity assessment with CVSS 4.0
4. Verify findings: Always validate AI findings against code and Frida testing

AI Analysis Prompts

See references/ai-pentesting-guide.md for complete methodology and prompt templates.

Quick examples:

ANALYZE: Is this SQL injection exploitable?
Code: <vulnerable_query_with_user_input>
Context: <userId from Intent extra>

For each finding provide:
- CWE ID and CVSS 4.0 score
- Exploitation scenario
- Frida script to demonstrate (if applicable)

Reference: references/ai-pentesting-guide.md - Complete AI analysis methodology

Inventory: references/project-manifest.md is the ground-truth list of every packaged file and directory.

---

Audit Mode Selection

Select the smallest mode that satisfies the user request. See references/audit-modes.md for full feature flags and presets.

Mode	Default Use	Notes
quick	First-pass triage	Decode, manifest, focused static checks, coverage statement.
static	No device/emulator	Static analysis only; mark runtime-only issues Needs Dynamic Confirmation.
full	Standard APK audit	Static + dynamic + MASVS + optional executive risk score.
protected-app	Packing/RASP blocks analysis	Follow protected-app fallback and record coverage gaps.
osint	Public exposure enrichment	Passive, in-scope OSINT only.
reporting-only	Existing findings JSON	Deduplicate, triage, MASVS, risk score, report.

---

Phase 0 — Decode and Detect Framework

Decode APK

apktool d app.apk -o decoded/         # Decode resources + smali
jadx -d jadx_output app.apk           # Decompile to Java
apkid app.apk                         # Detect framework/packer

Framework Detection

Identify the app's architecture early to tailor analysis.

React Native: grep -r "com.facebook.react" decoded/AndroidManifest.xml · Check for libhermes.so and index.android.bundle in assets/

Flutter: grep -r "io.flutter" decoded/AndroidManifest.xml · Check for libflutter.so and assets/flutter_assets/

Cordova/Ionic: grep -r "org.apache.cordova" decoded/AndroidManifest.xml · Check assets/www/ for cordova.js

Xamarin: grep -r "mono\|com.xamarin" decoded/AndroidManifest.xml · Check for libmonodroid.so

Reference: references/hybrid-webview-frameworks.md for complete detection scripts, Frida detection hooks, and framework-specific security considerations.

Cross-Platform Analysis Scripts: Use scripts/01-cross-platform/cordova-analysis.sh, scripts/01-cross-platform/flutter-analysis.sh, scripts/01-cross-platform/react-native-analysis.sh, and scripts/01-cross-platform/unity-analysis.sh for framework-specific static analysis of Cordova/Ionic, Flutter, React Native, and Unity applications respectively. These scripts extract framework-specific metadata, identify native module usage, and highlight security considerations unique to each framework.

Obfuscation Detection

• ProGuard/R8: Class names like a.b.c, a$a, a$1
• DexGuard: Additional string encryption and native methods
• Custom obfuscation: Unusual patterns, mixed naming schemes

Reference: references/static-analysis-patterns.md for detailed detection patterns.

---

Phase 1 — Attack Surface Mapping

Analyze AndroidManifest.xml

cat decoded/AndroidManifest.xml
aapt2 dump badging app.apk

Exported Components

Exported components are attack surfaces:

Component	Exported If	Security Checks
Activities	android:exported="true"	Intent filters, permission requirements
Services	android:exported="true"	Intent filters, permission requirements
Receivers	android:exported="true"	Intent filters, permission requirements
Providers	android:exported="true"	Path permissions, read/write permissions

Deep Link Schemes

Extract and document all deep link schemes:

<intent-filter>
    <data android:scheme="scheme" android:host="host" />
</intent-filter>

Security-Relevant XML Resources

Check res/xml/ for: network_security_config.xml (TLS/cleartext), file provider paths, preferences.

Reference: references/android-manifest-checklist.md for complete 50+ manifest checks. IPC / intent abuse: see references/intent-injection.md and references/pendingintent-security.md.

---

Phase 2 — Targeted Triage

Scoped Grep Patterns

ALWAYS grep within the app namespace only. Use patterns from references/static-analysis-patterns.md:

Category	Example Patterns	What to Look For
WebView sinks	loadUrl\(, evaluateJavascript	Loading untrusted URLs
IPC sources	getIntent(), onNewIntent()	Unsanitized data entry
Intent relays	getParcelableExtra, getSerializableExtra, startActivity\(, sendBroadcast\(	Nested intent / confused deputy patterns
Hardcoded secrets	password\s*=, api[_-]?key	Credentials in code
Encoded literals	Base64\.decode, "\x[0-9a-f]"	Obfuscated strings
Weak crypto	DES/, MD5, "AES/ECB"	Insecure algorithms
Insecure storage	SharedPreferences, MODE_WORLD_READABLE	Unprotected data
Network/TLS	TrustManager, X509TrustManager	SSL validation bypass
Native bridges	System\.loadLibrary, JNI methods	Native code interfaces

Resource File Analysis

Check res/values/strings.xml for secrets:

grep -iE "(key|token|secret|password|api)" decoded/res/values/strings.xml

Reference: references/static-analysis-patterns.md for 100+ grep patterns organized by vulnerability type.

Phase 2.5 — Static Analysis Rules (Optional)

The semgrep-based static analysis module augments grep patterns with OWASP MASTG rules:

# Enable semgrep in auto-audit-static.sh
bash scripts/auto-audit-static.sh app.apk --semgrep

# Run semgrep scan standalone
python3 scripts/03-static-analysis/semgrep-scan.py decoded/ --output findings-semgrep.json

# Merge findings with existing findings
python3 scripts/03-static-analysis/merge-findings.py --input findings.json semgrep.json --output merged.json

# Update rules from upstream
bash scripts/03-static-analysis/update-rules.sh --fetch

Features:

• 70+ MASTG-aligned rules covering crypto, network, storage, authentication
• Non-blocking fallback (continues if semgrep is not available)
• Deduplication by CWE + title before merging
• Phase 2.5 runs after grep patterns, before data flow tracing

Reference: scripts/03-static-analysis/semgrep-scan.py --help for rule categories and update workflow.

---

Phase 3 — Data Flow Tracing

Source-to-Sink Methodology

Map data flow from untrusted sources to dangerous sinks:

Common Sources

Source	Method	Example
IPC (Activities)	getIntent()	Malicious intent data
IPC (Services)	onStartCommand()	Start extras
Deep Links	getIntent().getData()	URL parameters
WebView	JavascriptInterface	Untrusted JS calls
Network	HttpResponse	API responses
Storage	SharedPreferences	Stored user input
External	Environment.getExternalStorageDirectory()	File system data

Common Sinks

Sink	Method	Impact
Command Execution	Runtime.exec(), ProcessBuilder	RCE
WebView Load	loadUrl(), loadData()	XSS, Phishing
File Operations	FileWriter, FileOutputStream	Path traversal, LFI
IPC Broadcast	sendBroadcast()	Intent injection
Reflection	Class.forName(), getMethod()	Code execution
Native Calls	JNI	Native code execution
SQL	SQLiteDatabase.execSQL()	SQL injection

Decision Rules

Rule	Condition	Action
1	Direct flow source → sink	Report as Likely
2	Indirect flow via static analysis	Report as Likely if path clear
3	Dynamic/reflective call	Mark as Needs Dynamic Confirmation
4	Native boundary	Mark as Needs Dynamic Confirmation
5	Library code	Verify if app wraps securely
6	No sanitization	Escalate severity

Manual Checks Grep Misses

Check	Why grep misses	How to verify
Runtime permissions	requestPermissions() calls	Trace onRequestPermissionsResult
Custom permission protections	checkPermission()	Look for permission checks
Activity transitions & intent relays	startActivity() hides nested-intent forwarding and grant flags	Follow intent construction, Parcelable relays, and FLAG_GRANT_* usage
File provider paths	XML + code	Map paths to exposed content URIs
Content provider queries	query()	Trace URI construction

Reference: references/attack-patterns.md for modern attack vectors: intent injection, deep link abuse, WebView universal XSS, task hijacking, file provider path traversal, broadcast theft, component hijacking.

---

Phase 4 — Dynamic Analysis (Optional)

Use when static analysis hits a wall: obfuscation, reflection, native code, runtime protections.

Runtime Defense Analysis (RDA)

The Runtime Defense Analysis module provides Frida-based detection and bypass for anti-analysis mechanisms:

# Run static audit first; RDA is a separate Phase 4 module
bash scripts/auto-audit-static.sh app.apk --semgrep

# Or via frida-exploit-helper.py
python3 scripts/07-tools/frida-exploit-helper.py -p com.target.app --runtime-defense

# List available detectors
bash scripts/02-rasp/runtime-defense-analyzer.sh --list

# Run with active bypass mode (attempt to bypass detections)
bash scripts/02-rasp/runtime-defense-analyzer.sh app.apk com.target.app --active-mode --authorized-lab

Available detector catalog (18 entries: 14 executable detectors + 4 not-applicable backend/cloud entries):

• rootbeer — RootBeer library detection
• safetynet — SafetyNet attestation
• emulator — Emulator detection
• debug — Debugger detection
• frida-detect — Frida detection
• screenshot — Screenshot prevention detection
• screenrecorded — Screen recording detection
• talsec, approov, dexguard, appdome, doverunner, digitalai — commercial RASP/shielding detection
• contrast, imperva, dynatrace, accuknox — cataloged as not-applicable for direct Android APK detection

Output: findings-rda.json with detector results

Reference: scripts/02-rasp/README.md for detailed detector documentation.

Authorized RASP Bypass Validation

After RDA detection, use the DRY bypass runner instead of duplicating Frida logic per detector:

# List reusable bypass profiles
bash scripts/02-rasp/rasp-bypass-runner.sh --list-profiles

# Build a reviewed command from detector names
bash scripts/02-rasp/rasp-bypass-runner.sh \
  --package com.target.app \
  --detectors rootbeer,frida_detect,talsec \
  --print-command

# Execute only in an authorized lab
bash scripts/02-rasp/rasp-bypass-runner.sh \
  --package com.target.app \
  --from-rda findings-rda.json \
  --run --authorized-lab

The single source of truth is scripts/02-rasp/bypass-profiles.json; the runner reuses scripts under assets/frida-scripts/. Do not copy bypass logic into detector files. See references/rasp-bypass-workflow.md for coverage, limits, and reporting requirements.

Frida Integration

# Spawn app with hook
frida -U -f com.example.app -l script.js

# Attach to running process
frida -U com.example.app -l script.js

Using frida-exploit-helper.py

The frida-exploit-helper.py script provides a convenient wrapper for Frida operations with bundled scripts and common patterns.

When to use: Prefer frida-exploit-helper.py over direct Frida CLI for:

• Bundled Frida scripts (SSL pinning bypass, root detection bypass, etc.)
• Quick memory operations (read, write, find base address)
• Discovering available scripts
• Simplified Frida workflow

Examples with bundled scripts:

# SSL pinning bypass
python3 scripts/07-tools/frida-exploit-helper.py -p com.target.app --script ssl-pinning-bypass

# Root detection bypass
python3 scripts/07-tools/frida-exploit-helper.py -p com.target.app --script root-detection-bypass

# List all available bundled scripts
python3 scripts/07-tools/frida-exploit-helper.py --list-scripts

# Display app memory layout (find base addresses)
python3 scripts/07-tools/frida-exploit-helper.py -p com.target.app --layout

# Hook specific functions (malloc, free, etc.)
python3 scripts/07-tools/frida-exploit-helper.py -p com.target.app --hook malloc,free

# Read memory at address
python3 scripts/07-tools/frida-exploit-helper.py -p com.target.app --read 0x12345678 64

# Write to memory address
python3 scripts/07-tools/frida-exploit-helper.py -p com.target.app --write 0x12345678 deadbeef

Key flags:

• -p, --package — Target package name (required for most operations)
• --script — Use bundled script name (use --list-scripts to see options) or path to a .js file
• --spawn / -s — Spawn a new process for the target package
• --attach / -a — Attach to a running process
• --list-scripts — Display all available bundled Frida scripts
• --layout — Show memory layout and base addresses
• --hook — Comma-separated list of functions to hook
• --read ADDRESS SIZE — Read memory at address (hex) with size in bytes
• --write ADDRESS DATA — Write data to address (hex). Data can be hex or string
• --base <library> — Get base address of specified module (requires library name)

Reference: See scripts/07-tools/frida-exploit-helper.py --help for complete options and bundled script catalog.

Reference: bundled Frida scripts in assets/frida-scripts/. See references/frida-scripts-index.md for the canonical catalog. Focused runtime triage: use assets/frida-scripts/android-file-access-monitor.js for filesystem/storage visibility, assets/frida-scripts/jni-tracer.js for JNI/native boundary discovery, and assets/frida-scripts/ipc-abuse-helper.js for passive IPC logging plus intentional provider/deep-link validation.

Script Maturity Levels:

• STABLE (with known scope): Production-ready within documented coverage. ssl-pinning-bypass.js covers core Java TLS/TrustManager paths (see its header for exact list — not a full universal OkHttp/WebView solution). root-detection-bypass.js, biometric-bypass.js, network-interceptor.js, etc. have broad but not infinite coverage.
• BETA: Functional but incomplete — use with caution

JNI Trace (Native Library Tracing)

For advanced JNI and native library analysis, use jnitrace:

# Install jnitrace
pip install jnitrace

# Trace all JNI functions in a native library (spawn mode)
jnitrace -l libnative-lib.so -m spawn com.target.app

# Trace with attach mode (attach to already-running app)
jnitrace -l libnative-lib.so -m attach com.target.app

# Trace only JNI methods matching a regex (include filter)
jnitrace -l libnative-lib.so -m spawn com.target.app \
  -i ".*decrypt.*|.*sign.*"

# Exclude noisy JNI methods
jnitrace -l libnative-lib.so -m spawn com.target.app \
  -e "GetStringUTFChars|ReleaseStringUTFChars"

# Hide JNIEnv/JavaVM struct calls to reduce noise
jnitrace -l libnative-lib.so -m spawn com.target.app \
  --ignore-env --ignore-vm

# Output trace to JSON file for later analysis
jnitrace -l libnative-lib.so -m spawn com.target.app \
  -o trace-output.json

Programmatic usage (via npm package):

npm install jnitrace-engine

Use jnitrace when:

• Analyzing custom JNI bindings
• Understanding native library behavior
• Debugging native crashes
• Tracing crypto operations in native code

Note: jnitrace requires the app to be started with Frida spawn mode. For more details, see references/native-analysis.md and jni-tracer.js for an alternative Frida-based approach.

Objection Commands

# Modern syntax (preferred): objection -n <package> start
objection -n com.example.app start

# Legacy syntax (deprecated but still works): objection -g <package> explore
objection -g com.example.app explore

# Enumerate components
android hooking list activities
android hooking list services
android hooking list receivers

# Bypass protections
android sslpinning disable

# Enumerate Android Keystore entries
android keystore list

ADB Runtime Testing

# Test exported activity
adb shell am start -n com.example.app/.MainActivity -a android.intent.action.VIEW -d "scheme://host"

# Test exported receiver
adb shell am broadcast -a com.example.app.ACTION -e key "value"

# Monitor logs
adb logcat | grep com.example.app

SSL Pinning bypass: references/dynamic-analysis-setup.md + assets/frida-scripts/ssl-pinning-bypass.js Split APK / AAB runtime handling: references/dynamic-analysis-setup.md#9-split-apk--aab-runtime-handling for pm path, adb install-multiple, and bundletool workflows. RASP bypass: references/rasp-bypass.md + assets/frida-scripts/native-root-detection-probe.js for anti-debug, anti-frida, emulator detection, and native root-check escalation. Protected-app fallback: references/packer-modern-unpacking.md#protected-app-fallback-decision-tree for runtime extraction, spawn-mode instrumentation, embedded instrumentation fallback, and static-only coverage handling.

---

Phase 5 — Classification and Reporting

Compliance Score (Optional)

Generate a MASVS v2 compliance score alongside CVSS findings:

# Generate MASVS compliance score
python3 scripts/05-scoring/calculate-score.py findings.json --json-output > score.json

# Generate full report with MASVS score
python3 scripts/07-tools/generate-report.py --input findings.json --masvs --output report.html

# Use custom MASVS mapping
python3 scripts/07-tools/generate-report.py --input findings.json --masvs --masvs-mapping scripts/05-scoring/masvs-mapping.json --output report.html

Scoring methodology:

• 24 MASVS v2 controls assessed
• Weighted deduction based on severity (Critical×10, High×5, Medium×2, Low×1)
• Final score: 0–100 with letter grade (A/B/C/D/F)

Grade thresholds:

• A: 90–100 (Excellent)
• B: 75–89 (Good)
• C: 60–74 (Acceptable)
• D: 40–59 (Poor)
• F: 0–39 (Critical)

References: scripts/05-scoring/README.md and references/masvs-scoring-model.md for control definitions, mapping semantics, and not-tested handling.

Executive Risk Score (Optional)

When generating an executive report, include an aggregate risk score only after deduplication and confidence triage. Use references/risk-score-model.md to keep this separate from CVSS and MASVS:

• CVSS = severity of individual vulnerabilities
• MASVS = control coverage/compliance posture
• Executive risk score = aggregate operational exposure and coverage gaps

Do not deduct score for rejected false positives. Treat unresolved protected code, missing splits, or skipped dynamic validation as coverage gaps rather than confirmed vulnerabilities.

OSINT Enrichment (Optional)

If the engagement scope allows passive reconnaissance, enrich Phase 5 with references/osint-apk-recon.md:

1. Correlate package name, app label, first-party domains, endpoints, and redacted secret fingerprints.
2. Search passive public sources only unless active probing is explicitly authorized.
3. Classify domains as first-party, likely first-party, third-party SDK, or unknown before reporting.
4. Promote OSINT evidence only when it supports an in-scope app finding or public exposure claim.

Confidence Levels

Level	Definition	Example Evidence
Confirmed	Full source-to-sink trace validated	Direct call chain from IPC source to Runtime.exec() with no sanitization
Likely	Strong evidence, minor gaps	Static trace clear but reflection obscures final sink
Needs Dynamic Confirmation	Static analysis inconclusive	Obfuscated code or native boundary requiring runtime verification

Severity

Use CVSS 4.0. See references/cvss-scoring-guide.md for complete methodology and severity mapping.

Finding Template

## [ID] - [Title]

**Confidence**: [Confirmed/Likely/Needs Dynamic Confirmation]
**Severity**: [Critical/High/Medium/Low] (CVSS: [X.X])
**CWE**: [CWE-ID]
**OWASP**: [OWASP Category]

### Description
[1-2 sentences explaining what the vulnerability is]

### Affected Components
- **File**: `path/to/file.java`
- **Method**: `methodName()`
- **Component**: `[Activity/Service/Receiver/Provider]` (if applicable)

### Attack Scenario
1. Attacker [action, e.g., sends malicious intent with crafted data]
2. App [processing step, e.g., extracts parameter without validation]
3. Data propagates through [call chain]
4. Reaches sink [dangerous operation]
5. Results in [impact, e.g., arbitrary command execution]

### Proof of Concept
```bash
adb shell am start -n com.example.app/.MainActivity \
  -a android.intent.action.VIEW \
  -d 'exploit://host/path?payload=cmd%7Ccat%20/data/data/com.example.app/databases/db'

Or provide Frida hook script for dynamic verification.

Impact

• Confidentiality: [High/Medium/Low/None] — [explanation]
• Integrity: [High/Medium/Low/None] — [explanation]
• Availability: [High/Medium/Low/None] — [explanation]

Remediation

// Provide secure code example
Intent intent = getIntent();
if (intent != null && intent.getData() != null) {
    String input = intent.getData().getQueryParameter("path");
    if (isValidPath(input)) {
        loadUrl(input);
    } else {
        Log.w(TAG, "Invalid path detected");
    }
}
private boolean isValidPath(String path) {
    return path != null && !path.contains("..") &&
           path.matches("^/safe/\\w+\\.html$");
}

CVSS 4.0 Calculation

[Show vector string and score breakdown]

### Coverage Statement
End your report with:

Coverage Analysis:

• Static Analysis: Complete (all decompiled sources analyzed)
• Dynamic Analysis: [Complete/Partial/Not Performed] (reason if partial)
• Scope: [com.example.app.* namespace only]
• Framework: [React Native/Flutter/Native/Standard]
• Obfuscation: [ProGuard/R8/DexGuard/Custom/None]

Limitations:

• [List any limitations, e.g., "Native code analysis requires additional tools"]
• [Any components that could not be analyzed]
• [Any findings requiring additional verification]

Total Findings: X (Critical: Y, High: Z, Medium: A, Low: B)

> **Reference**: `references/reporting-templates.md` for executive summary format, remediation priority matrix, and presentation templates.

### Automated Report Generation

Use the `generate-report.py` script to generate professional HTML or Markdown reports from findings JSON:

```bash
# Generate HTML report
python3 scripts/07-tools/generate-report.py \
  --input findings.json \
  --output report.html \
  --app-name "My App" \
  --package-name "com.example.app"

# Generate Markdown report
python3 scripts/07-tools/generate-report.py \
  --input findings.json \
  --output report.md \
  --app-name "My App" \
  --package-name "com.example.app"

The script supports both JSON array format and JSONL (one finding per line) and automatically:

• Sorts findings by severity (Critical first)
• Calculates CVSS 4.0 severity scores
• Generates executive summary with risk rating
• Maps OWASP MASTG categories
• Provides formatted proof of concept and remediation sections

See scripts/test-findings.json for the expected JSON structure.

---

APK Modification Workflow

1. Decode

apktool d app.apk -o app-modified/

2. Modify — Smali Patching

Edit smali files in app-modified/smali/:

.method public checkSecurity()Z
    .locals 1
    # Original: iget-boolean v0, p0, Lcom/example/App;->securityEnabled:Z
    # Patched — always return true
    const/4 v0, 0x1
    return v0
.end method

Resource Modification

Edit XML or resource files in app-modified/res/:

<!-- Example: enable debug flag -->
<bool name="debug_mode">true</bool>

3. Rebuild

apktool b app-modified/ -o app-modified.apk

4. Sign

# Generate keystore (first time only)
keytool -genkeypair -v -keystore my-release-key.jks -alias androiddebugkey -keyalg RSA -keysize 2048 -validity 10000

# Align first
zipalign -v 4 app-modified.apk app-aligned.apk

# Sign (apksigner supports v1, v2, v3, v3.1 signatures)
# Verify keystore exists before signing
if [ ! -f "my-release-key.jks" ]; then
    echo "Error: Keystore not found. Create it with keytool first."
    exit 1
fi
# --ks-key-alias is required when the keystore contains multiple keys; recommended in all cases
apksigner sign \
  --ks my-release-key.jks \
  --ks-key-alias androiddebugkey \
  --ks-pass pass:myPassword \
  --key-pass pass:myPassword \
  --out app-signed.apk \
  app-aligned.apk

# Verify signature
apksigner verify --verbose app-signed.apk

5. Install and Verify

adb install -r app-signed.apk

Reference: references/dynamic-analysis-setup.md for advanced repackaging, signature verification bypass, and ADB debugging. See references/apk-modification-guide.md for smali editing edge cases and troubleshooting.

---

Troubleshooting

APK Decoding Fails

apktool d -f app.apk -o decoded/         # Force mode (re-decodes even if output dir exists)
aapt2 dump badging app.apk                # Verify APK integrity
apkid app.apk                             # Detect packer/protector

Note: Apktool 3.0+ removed the -api/--api-level flag. The API level is now auto-detected from the APK. If packed → see references/packing-unpacking.md for unpacking techniques.

JADX Shows Bad Code

jadx --show-bad-code -v app.apk           # Show code even with errors
jadx --decompilation-mode fallback app.apk
jadx-gui app.apk                          # GUI for manual inspection

Frida Cannot Attach

adb shell ps -A | grep frida
adb shell getprop ro.product.cpu.abi
adb shell "su -c 'killall frida-server'"
adb shell "su -c '/data/local/tmp/frida-server -D &'"

Full setup: references/dynamic-analysis-setup.md

Obfuscated Code Unreadable

• Identify obfuscator: apkid app.apk
• Enable JADX deobfuscation: jadx --deobf app.apk
• See references/static-analysis-patterns.md → "Obfuscation Patterns"
• Switch to Phase 4 for runtime behavior

When to Escalate to Dynamic Analysis

Static analysis reaches limits when: obfuscation unclear, reflection, JNI boundaries, anti-debug/root detection, SSL pinning. → Proceed to Phase 4 using references/dynamic-analysis-setup.md.

---

Examples

Example 1: Quick Assessment

com.example.app.apk → Decode → Framework detect → Manifest audit → Secrets grep → CVSS report

Example 2: SSL Pinning Bypass

frida -U -f com.target.app -l ssl-pinning-bypass.js → See references/rasp-bypass.md if fails

Example 3: APK Repackaging

Decode → Modify → Rebuild → Sign → Install (see references/apk-modification-guide.md)

---

Agent Operating Contract

This contract defines what every audit must produce, when to advance, when to stop, and how to report findings.

Required Audit Artifacts

For every APK audit, produce these artifacts:

Artifact	Phase	Description
scope.json	-1	Package name, target scope, authorization confirmation
toolchain-report.json	0	Tool versions, availability, preflight results
app-profile.json	0	Framework, obfuscation, architecture
attack-surface.json	1	Exported components, deep links, permissions
findings.json	2-4	All findings in standard schema
evidence/	2-4	Screenshots, logs, PoC commands
coverage-matrix.json	5	MASVS control coverage status
final-report.html	5	Executive summary + technical findings

Stop Conditions — STOP AND REPORT IMMEDIATELY

Condition	Action
APK decode fails	Report DECODE_FAILURE with error log
Package name cannot be determined	Report SCOPE_UNCLEAR and stop
Target namespace cannot be isolated	Report SCOPE_TOO_BROAD
Dynamic testing requested but no Frida/device	Mark findings Needs Dynamic Confirmation
Encrypted/packed APK blocks analysis	Report PACKED_APK with partial coverage

Finding States

State	When to Use	CVSS Required
Confirmed	Full source-to-sink trace validated	Yes
Likely	Strong evidence, minor gaps in trace	Yes
Needs Dynamic Confirmation	Static inconclusive (obfuscation, reflection, JNI)	TBD
Informational	Best practice violation, low risk	Optional
Rejected	Previously reported, confirmed false positive	N/A

APK Type Handling

Type	Analysis Approach
Standard APK	Full 6-phase workflow
Split APK / AAB	Phase 0 → detect base vs dynamic features, pull/install full split set, analyze each split separately; see dynamic-analysis-setup.md#9-split-apk--aab-runtime-handling
Packed/Protected	Phase 0 → static baseline, runtime extraction/spawn-mode/embedded instrumentation fallback; if blocked → PACKED_APK report with coverage gap
React Native	Phase 0 → extract Hermes bytecode, use scripts/01-cross-platform/react-native-analysis.sh
Flutter	Phase 0 → Blutter analysis, native SSL hooks
Xamarin	Phase 0 → identify Mono runtime, analyze bundled assemblies
Obfuscated	Phase 2 → enhanced grep + Phase 4 dynamic if available

Evidence Standards

Every finding must have:

1. File + line reference (or Frida trace for dynamic)
2. Evidence snippet (relevant code/data)
3. Attack scenario (how attacker exploits)
4. CVSS 4.0 vector (Confirmed/Likely) or TBD (Needs Dynamic)

Coverage Declaration

End every report with:

{
  "coverage": {
    "static_analysis": "complete | partial | not-performed",
    "dynamic_analysis": "complete | partial | not-performed",
    "framework": "react-native | flutter | cordova | xamarin | native",
    "obfuscation": "proguard | dexguard | custom | none",
    "native_code": "analyzed | not-analyzed | not-applicable",
    "rasp": "detected | not-detected | not-tested"
  },
  "total_findings": { "critical": 0, "high": 0, "medium": 0, "low": 0 }
}

---

References Index

Phase	Files	Phase	Files
0	environment-setup, opencode-tooling, static-analysis-patterns, hybrid-webview-frameworks, kotlin-patterns, kotlin-async-security, kotlin-compose-security, kotlin-multiplatform-security, malware-analysis, tool-installation	3	attack-patterns, intent-injection, pendingintent-security, firebase-security, deep-link-exploitation, real-world-android-vulnerabilities
1	android-manifest-checklist, android-version-security, android-14-15-security-changes, android-15-security-guide, android-16-security-guide, androidx-security-migration, secure-storage-migration	4	dynamic-analysis-setup, native-code-analysis, native-analysis, rasp-bypass, rasp-bypass-workflow, packing-unpacking, packer-modern-unpacking, react-native-hermes-analysis, frida-version-matching-guide, android-keystore2-testing, biometric-testing-comprehensive, frida-advanced-patterns, android-anti-frida-countermeasures
2	dependency-analysis, supply-chain-security	5	cvss-scoring-guide, cvss-calculator, reporting-templates, finding-template-cards, masvs-scoring-model, risk-score-model, osint-apk-recon, audit-modes, frida-scripts-index, cheat-sheet-commands,

Scripts:

• scripts/01-cross-platform/ — Framework-specific analysis (Cordova, Flutter, React Native, Unity)
• scripts/02-rasp/ — Runtime Defense Analysis (RDA)
• scripts/03-static-analysis/ — semgrep scan + merge-findings
• scripts/04-android-15-16/ — Android 15/16 specific APIs
• scripts/05-scoring/ — MASVS v2 compliance scoring
• scripts/06-setup/ — preflight-check + validation
• scripts/07-tools/ — Core tools (frida-exploit-helper, generate-report, correlate-findings, mobsf-api-scan, burp-findings-export, rop-helper)
• auto-audit-static.sh — Main orchestrator
• audit-android-components.sh — Component audit Exploitation: exploitation-guide, heap-exploitation, exploitation-decisions, android-binder-cve-2023-20938 RASP bypass: scripts/02-rasp/rasp-bypass-runner.sh uses scripts/02-rasp/bypass-profiles.json to compose reusable Frida bypass stacks. See references/rasp-bypass-workflow.md. Assets: Frida scripts in assets/frida-scripts/ (see references/frida-scripts-index.md); full file inventory is in references/project-manifest.md

Loading Strategy: Load reference files only when encountering the specific technical challenge they cover. Do NOT load all references at once.

---

Platform-Specific Notes

See references/environment-setup.md for detailed Windows (PowerShell), macOS, and Linux setup. On macOS, use rg (ripgrep) instead of grep -P — BSD grep does not support PCRE.

Known Implementation Gaps (as of remediation pass, April 2026)

The following gaps were identified and partially mitigated during a full code + claims audit:

• Semgrep integration (Phase 2.5): Previously completely non-functional (no --json flag was passed). Now fixed in semgrep-scan.py.
• Preflight in agent contexts: Interactive safety/scope prompts would hang or fail under --json / non-TTY. Now auto-skips with clear notes when run by agents/CI.
• Frida bypass coverage claims: Several "STABLE" / "30+ implementations" statements (especially ssl-pinning-bypass.js) were overstated vs. actual code. Script headers and key docs have been qualified; the script itself is now honest about scope.
• Shell error handling: Multiple blanket &>/dev/null and unquoted loops existed (especially in audit-android-components.sh). Critical decode path now uses run_logged helper with real log capture + timeouts. More work remains on other heavy-tool calls.
• DRY / shared library: scripts/lib/ (findings schema, normalizers, MASVS helpers) was mostly dead code due to import hacks. Partial wiring started; full centralization of the 5–6 duplicated load_findings implementations is still pending.
• Committed artifacts: Many __pycache__/ and *.pyc files were present. .gitignore has been expanded.

These are tracked in the remediation plan for this change. Always run the preflight + validators before trusting a full audit in a new environment.

The skill prioritizes honest, reproducible results over impressive-sounding claims. When in doubt, mark "Needs Dynamic Confirmation" and surface coverage gaps explicitly.