oyi77/1ai-skills/analyzing-android-malware-with-apktool

Analyzing Android Malware with Apktool

Overview

Android malware distributed as APK files can be statically analyzed to extract permissions, activities, services, broadcast receivers, and suspicious API calls without executing the sample. This skill uses androguard for programmatic APK analysis, identifying dangerous permission combinations, obfuscated code patterns, dynamic code loading, reflection-based API calls, and network communication indicators.

When to Use

Trigger phrases:

• "analyzing android malware with apktool"
• "Perform static analysis of Android APK malware samples using apktool for decompi"

• When investigating security incidents that require analyzing android malware with apktool
• When building detection rules or threat hunting queries for this domain
• When SOC analysts need structured procedures for this analysis type
• When validating security monitoring coverage for related attack techniques

Prerequisites

• Python 3.9+ with androguard
• apktool (for resource decompilation)
• jadx (for Java source recovery, optional)
• Isolated analysis environment (VM or sandbox)
• Sample APK files for analysis

Steps

# Example: IOC detection
import re
IOC_PATTERNS = {
    "ip": r"\b(?:\d{1,3}\.){3}\d{1,3}\b",
    "domain": r"\b[a-z0-9-]+\.[a-z]{2,}\b",
    "hash_md5": r"\b[a-f0-9]{32}\b",
    "hash_sha256": r"\b[a-f0-9]{64}\b",
}
def extract_iocs(text: str) -> dict:
    return {k: re.findall(v, text) for k, v in IOC_PATTERNS.items()}

1. Parse APK with androguard to extract manifest metadata
2. Enumerate requested permissions and flag dangerous combinations
3. List activities, services, receivers, and providers from manifest
4. Scan for suspicious API calls (reflection, crypto, SMS, telephony)
5. Detect dynamic code loading patterns (DexClassLoader, Runtime.exec)
6. Extract hardcoded URLs, IPs, and C2 indicators from strings
7. Generate risk assessment report with MITRE ATT&CK mobile mappings

Expected Output

• JSON report with permission analysis, component listing, suspicious API calls, network indicators, and risk score
• Extracted strings and potential IOCs from the APK

When NOT to Use

• You need to perform the attack, not analyze it (use performing-* skills)
• Task is about detection, not analysis (use detecting-* skills)
• You need to implement controls (use implementing-* skills)
• Task is about threat hunting, not post-incident analysis (use hunting-* skills)
• You don't have access to the artifacts/logs to analyze
• Task requires real-time monitoring (use SOC tools)

Red Flags

• Performing actions without explicit written authorization from the asset owner
• Testing against production systems without a defined scope and rules of engagement
• Analyzing malware on a machine connected to the production network
• Failing to isolate the analysis environment from the internet
• Executing samples without proper containment (VM, sandbox)

Process

1. Reconnaissance — Gather target information, identify attack surface, enumerate services
2. Analysis/Exploitation — Execute the technique, analyze results, document findings
3. Reporting — Document IOCs, write findings, provide remediation recommendations

Verification

• All steps executed successfully against a test environment before production use
• Output documented with screenshots or logs demonstrating expected behavior
• Sample hash recorded and verified (MD5, SHA-1, SHA-256)
• Analysis environment confirmed isolated from production network
• Indicators of compromise (IOCs) extracted and documented

Anti-Rationalization Table