detecting-mobile-malware-behavior
Detects and analyzes malicious behavior in mobile applications through behavioral analysis, permission abuse detection, network traffic monitoring, and…
Skill by mukul975
Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/mukul975-detecting-mobile-malware-behavior
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About
Use cases: data
Reviews
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Permissions
What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
- None found
- Runs as
- Python package
Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/detecting-mobile-malware-behavior
What's inside
- Skill name
detecting-mobile-malware-behavior- Description
- Detects and analyzes malicious behavior in mobile applications through behavioral analysis, permission abuse detection, network traffic monitoring, and dynamic instrumentation. Use when analyzing suspicious mobile applications for data exfiltration, command-and-control communication, credential stealing, SMS interception, or other malware indicators. Activates for requests involving mobile malware analysis, app behavior monitoring, trojan detection, or suspicious app investigation.
- License
- Apache-2.0
- Instructions
- 182 lines in SKILL.md · view on GitHub
Before installing
- Ships executable scripts
- Instructions call the network
Files (8)
- LICENSE
- SKILL.md
- template.md · assets/
- api-reference.md · references/
- standards.md · references/
- workflows.md · references/
- agent.py · scripts/
- process.py · scripts/
SKILL.md (first lines)
# Detecting Mobile Malware Behavior
## When to Use
Use this skill when:
- Analyzing suspicious mobile applications submitted by users or discovered during incident response
- Monitoring enterprise mobile fleet for malicious app indicators
- Performing malware triage on APK/IPA samples
- Investigating data exfiltration or unauthorized device access from mobile apps
**Do not use** this skill to create, enhance, or distribute malware. This skill is for defensive analysis only.
## Prerequisites
- Isolated analysis environment (dedicated device or emulator, not connected to production networks)
- MobSF for automated static+dynamic analysis
- Frida/Objection for runtime behavior monitoring
- Wireshark/tcpdump for network traffic capture
- Android emulator (AVD) or Genymotion for safe execution
- VirusTotal API key for hash lookups
## Workflow
### Step 1: Static Indicator Analysis
```bash
# Hash the sample
sha256sum suspicious.apk
# Check VirusTotal
curl -s "https://www.virustotal.com/api/v3/files/<SHA256>" \
-H "x-apikey: <VT_API_KEY>" | jq '.data.attributes.last_analysis_stats'
# Extract permissions from AndroidManifest.xml
aapt dump permissions suspicious.apk
# High-risk permission combinations:
# READ_SMS + INTERNET = SMS stealer
# RECEIVE_SMS + SEND_SMS = SMS interceptor/banker trojan
# ACCESSIBILITY_SERVICE + INTERNET = overlay attack capability
# CAMERA + RECORD_AUDIO + INTERNET = spyware
# DEVICE_ADMIN + INTERNET = ransomware capability
# READ_CONTACTS + INTERNET = contact exfiltration
```
### Step 2: MobSF Automated Malware Scan
```bash
# Upload to MobSF
curl -F "file=@suspicious.apk" http://localhost:8000/api/v1/upload \
-H "Authorization: <API_KEY>"
# Review malware indicators in report:
# - Hardcoded C2 server addresses
# - Dynamic code loading (DexClassLoader)
# - Reflection-based API calls (to evade static analysis)
# - Encrypted/obfuscated payloads
# - Root detection (malware often checks for root)
# - Anti-emulator checks (malware evades sandbox)
```
### Step 3: Network Behavior Monitoring
```bash
# Start packet capture on emulator
tcpdump -i any -w malware_traffic.pcap
# Or use mitmproxy for HTTP/HTTPS
mitmproxy --mode transparent
# Monitor for:
# - DNS lookups to suspicious/newly registered domains
# - Connections to known C2 infrastructure
# - Data exfiltration patterns (large POST requests)
# - Beaconing behavior (regular interval connections)
# - Non-standard ports and protocols
# - Domain Generation Algorithm (DGA) patterns
```
### Step 4: Runtime Behavior Monitoring with Frida
```javascript
// monitor_malware.js - Comprehensive behavior monitoring
Java.perform(function() {
// Monitor SMS access
var SmsManager = Java.use("android.telephony.SmsManager");
SmsManager.sendTextMessage.overload("java.lang.String", "java.lang.String",
"java.lang.String", "android.app.PendingIntent", "android.app.PendingIntent")
.implementation = function(dest, sc, text, sent, delivery) {
console.log("[SMS] Sending to: " + dest + " Text: " + text);
// Allow or block based on analysis needs
return this.sendTextMessage(dest, sc, text, sent, delivery);
};
// Monitor file operations
var FileOutputStream = Java.use("java.io.FileOutputStream");
FileOutputStream.$init.overload("java.lang.String").implementation = function(path) {
console.log("[FILE-WRITE] " + path);
return this.$init(path);
};
// Monitor network connections
var URL = Java.use("java.net.URL");
URL.openConnection.overload().implementation = function() {
console.log("[NET] " + this.toString());
return this.openConnection();
};
// Monitor dynamic code loading
var DexClassLoader = Java.use("dalvik.system.DexClassLoader");
DexClassLoader.$init.implementation = function(dexPath, optDir, libPath, parent) {
console.log("[DEX-LOAD] Loading: " + dexPath);
return this.$init(dexPath, optDir, libPath, parent);
};
// Monitor command execution
var Runtime = Java.use("java.lang.Runtime");
Runtime.exec.overload("java.lang.String").implementation = function(cmd) {
console.log("[EXEC] " + cmd);
return this.exec(cmd);From mukul975/Anthropic-Cybersecurity-Skills, Apache-2.0.
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Signals
- Stars
- 34,941
- Forks
- 4,256
- Open issues
- 24
- Last commit (this folder)
- Jun 20, 2026 (4 months ago)
- Last release
- Jun 22, 2026 (4 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- Apache-2.0
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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Cite this page
detecting-mobile-malware-behavior skill. Agent Mart. https://agentmart.dev/skills/mukul975-detecting-mobile-malware-behavior (last updated 2026-10-24)