Performing Android App Static Analysis With Mobsf

Performing Android App Static Analysis With Mobsf

Overview

Cybersecurity skill for performing android app static analysis with mobsf. Follows industry best practices and security standards.

When to Use

Trigger phrases:

• "performing android app static analysis with mobsf"
• "Conducting security assessment of Android APK or AAB files before production rel"
• "Integrating automated mobile security scanning into CI/CD pipelines"
• "Performing initial triage of Android applications during penetration testing eng"

Use this skill when:

• Conducting security assessment of Android APK or AAB files before production release
• Integrating automated mobile security scanning into CI/CD pipelines
• Performing initial triage of Android applications during penetration testing engagements
• Reviewing third-party Android applications for supply chain security risks

Do not use this skill as a replacement for manual code review or dynamic analysis -- MobSF static analysis catches pattern-based vulnerabilities but misses runtime logic flaws.

When NOT to Use

• When you lack proper authorization for testing
• For production systems without change management
• When the task requires legal or compliance expertise beyond technical scope

Prerequisites

• MobSF v4.x installed via Docker (docker pull opensecurity/mobile-security-framework-mobsf) or local setup
• Target Android APK, AAB, or source code ZIP
• Python 3.10+ for MobSF REST API integration
• JADX decompiler (bundled with MobSF) for Java/Kotlin source recovery
• Network access to MobSF web interface (default: http://localhost:8000)

Workflow

# 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. Plan Operations — Define objectives, scope, and success criteria for android app static analysis operations.
2. Prepare Environment — Set up tools, access, and data sources required for android app static analysis.
3. Execute Core Workflow — Use mobsf to perform android app static analysis operations following established procedures.
4. Validate Results — Verify that results meet quality standards and objectives.
5. Report Findings — Document results, observations, and recommendations.
6. Follow Up — Track remediation actions and verify fixes where applicable.

Tools

• mobsf — Primary tool for this skill
• Analysis Platform — Data processing and visualization
• Collaboration Tools — Team coordination and knowledge sharing

Process

1. Design — Define interface, identify patterns, plan implementation
2. Implement — Write code following existing conventions, add tests
3. Verify — Run tests, check integration, validate behavior

Verification

• All android app static analysis procedures executed completely and documented
• Findings validated against multiple data sources
• False positives identified and filtered
• Results documented with evidence and timestamps
• Recommendations provided with risk-based prioritization

Anti-Rationalization Table