Atlas / Skills / mukul975 / Analyzing Android Malware With Apktool

Analyzing Android Malware With ApktoolSAFE

skills/mukul975/analyzing-android-malware-with-apktool

817 structured cybersecurity skills for AI agents · Mapped to 6 frameworks: MITRE ATT&CK, NIST CSF 2.0, MITRE ATLAS, D3FEND, NIST AI RMF & MITRE F3 (Fight Fraud) · agentskills.io standard · Works with Claude Code, GitHub Copilot, Codex CLI, Cursor, Gemini CLI & 20+ platforms · 29 security domains ·

Verdict
SAFE
Grade
B
Trust score
89 /100
Version
1.0
Hosts
—
License
Apache-2.0
Stars
33,870
01

Overview

817 structured cybersecurity skills for AI agents · Mapped to 6 frameworks: MITRE ATT&CK, NIST CSF 2.0, MITRE ATLAS, D3FEND, NIST AI RMF & MITRE F3 (Fight Fraud) · agentskills.io standard · Works with Claude Code, GitHub Copilot, Codex CLI, Cursor, Gemini CLI & 20+ platforms · 29 security domains ·

Read from source at commit 6c59587be632OBSERVED · 2026-10-07
02

What it tells the agent

The instruction file, verbatim from the audited commit — this is the text the model reads, and the surface the audit's instruction layer examines. Quoted here so you can judge it without cloning anything.

---
name: analyzing-android-malware-with-apktool
description: Perform static analysis of Android APK malware using apktool for resource decompilation, jadx for Java source recovery, and androguard for manifest inspection, dangerous permission-combination detection, and identification of obfuscated code, dynamic code loading, and reflection-based API calls. Use to statically triage a suspicious APK without executing it or to build mobile malware detection rules.
domain: cybersecurity
subdomain: malware-analysis
tags:
- Android
- APK
- apktool
- jadx
- androguard
- mobile-malware
- static-analysis
- reverse-engineering
version: '1.0'
author: mahipal
license: Apache-2.0
nist_csf:
- DE.AE-02
- RS.AN-03
- ID.RA-01
- DE.CM-01
mitre_attack:
- T1406
- T1407
- T1626.001
- T1655.001
- T1521.001
---

# 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

- 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

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
03

Trust audit

SAFEgrade B · trust 89/100 Nothing in the source contradicts what it says it does. Grade A is reserved for packages that have also passed the behavioural sandbox.

LayerWhat it checksResult
L0Provenance & inventoryPASS
L1Static analysis of the codePASS
L2Instruction surface (what it tells the agent)PASS
L3Class-specific surfacePASS
L4Behavioural (sandbox)SKIPPED

What the source does

Filesystem
none-observed
Network
none-observed
Shell
none-observed
Dependencies
pinned
Secrets in source
none-found

Findings (0)

No findings outside the package's declared scope.

Gates applied: no_behavioural_pass.

Audited 2026-10-07 · audit v0.4.1 · source sha 6c59587be632full audit observations/trust-audit/skill/mukul975__analyzing-android-malware-with-apktool.json · Report an issue / request a re-scan
04

Audit history

Every audit this skill has had.

DateSourceVerdictGradeScoreChange
2026-10-076c59587be632SAFEB89first audit
05

Questions

What does the Analyzing Android Malware With Apktool skill do?

817 structured cybersecurity skills for AI agents · Mapped to 6 frameworks: MITRE ATT&CK, NIST CSF 2.0, MITRE ATLAS, D3FEND, NIST AI RMF & MITRE F3 (Fight Fraud) · agentskills.io standard · Works with Claude Code, GitHub Copilot, Codex CLI, Cursor, Gemini CLI & 20+ platforms · 29 security domains ·

Is Analyzing Android Malware With Apktool safe to install?

The audit found nothing in the source that contradicts what it says it does, and graded it B (89/100). Grade A is held back for packages that have also passed a sandboxed behavioural run, which is why a clean skill reads B.

What can Analyzing Android Malware With Apktool access on my machine?

The audit observed no filesystem, network or shell use at all in its source.

How current is this page?

The grade is for one exact copy of the source (6c59587be632), read on 2026-10-07. The repository is watched, and a new audit runs when it changes — this is the first audit.

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