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CC reverse-engineering-android-malware-with-jadx

Reverse engineers malicious Android APK files using the JADX decompiler to read Java/Kotlin source, inspect manifest permissions, receivers, services, and native libraries, and identify data theft, C2 communication, privilege escalation, or overlay-attack behavior. Use when analyzing a suspected Android banking trojan, spyware, SMS stealer, or other flagged APK, or when investigating mobile malware or Android threats generally.

mukul975/Anthropic-Cybersecurity-Skills Agent Skills author: mukul975 Apache-2.0 4 files · 1 script body ≈ 3 005 tokens Open the sourcegithub.com↗ analyzed 5 d ago

Reverse engineers malicious Android APK files using the JADX decompiler to read Java/Kotlin source, inspect manifest permissions, receivers, services, and…

As a process C 63/100 · Has gaps — weak spots: failures and branches, running it twice, progress reporting

ProcedureSoftware developmentSecuritytype and topics are labelled automatically from the skill text
Runs in: Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) OpenClaw Goose OpenCode
JSON
Technical rating
C
89/100
safety, quality, tests
Safety 60%
94
Quality 40%
82
Run on models
none yet
Process rating
C
63/100
Has gaps
Failures and branches w 10
0
Progress reporting w 2
0
Running it twice w 4
30
the three weakest of ten parameters · all ten

How to improve

    For the model run — optional
    • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
    • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

    Guard findings · 6

    ✓ No critical or high findings

    Medium and low: 6
    • low Risky intent intent-offensive-security references/api-reference.md:50
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      | urls | HTTP/HTTPS C2 server addresses |
    • low Risky intent intent-offensive-security SKILL.md:5
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      native libraries, and identify data theft, C2 communication, privilege escalation,
    • low Risky intent intent-offensive-security SKILL.md:42
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      - Extracting C2 server addresses, encryption keys, and configuration data from Android malware
    • low Risky intent intent-offensive-security SKILL.md:261
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      Compile a comprehensive Android malware analysis report:
    • low Risky intent intent-offensive-security SKILL.md:320
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      ANDROID MALWARE ANALYSIS REPORT
    • low Risky intent intent-offensive-security SKILL.md:331
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      Type:             Banking Trojan / SMS Stealer / Keylogger

    Files scanned: 4. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "domain"
    • note frontmatter-key unknown frontmatter key "subdomain"
    • note frontmatter-key unknown frontmatter key "nist_csf"
    • note frontmatter-key unknown frontmatter key "mitre_attack"

    Process rating: all ten parameters 63/100

    • 0Failures and branches. Linear process with no failure handling
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 1 mutating operations with no state check
    • 50When it triggers. No condition that starts the skill
    • 60Tools and files. Uses tools (python) that frontmatter does not declare
    • 60Result and completion. Output format stated, no completion criterion
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Steps. 27 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 3005 tokens

    Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

    Quality signals

    • +5Description has no quoted example phrases that should trigger the skill
    • -41 reference files, but SKILL.md never points to them: the model will not open them
    • -31 of 1 scripts are never mentioned in SKILL.md
    • +2Single-language instructions
    • +4Description says when NOT to use the skill
    • +3Description length 431: enough signal without eating the budget
    • +4Structure: 15 headings
    • +3Step-by-step instructions: 27 items
    • +3Output format is stated explicitly
    • +4Has examples (7 code blocks)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 82.