Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add 26zl/cybersec-toolkit --skill conducting-mobile-app-penetration-testgit clone --depth 1 https://github.com/26zl/cybersec-toolkitWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/26zl/cybersec-toolkit/conducting-mobile-app-penetration-test)<a href="https://agentmods.dev/skills/26zl/cybersec-toolkit/conducting-mobile-app-penetration-test"><img src="https://agentmods.dev/badge/skills/26zl/cybersec-toolkit/conducting-mobile-app-penetration-test/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/26zl/cybersec-toolkit/conducting-mobile-app-penetration-test"><img src="https://agentmods.dev/badge/skills/26zl/cybersec-toolkit/conducting-mobile-app-penetration-test.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 5 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Privilege Escalation · line 118 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- high Privilege Escalation · line 129 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- high Prompt Injection · line 153 This pattern attempts to override system instructions or ignore safety constraints. Without LLM analysis, manual review is recommended.Fix: Remove or rewrite any text that instructs the agent to ignore prompts, override safety rules, or trust unverified content. Ensure skill content cannot be injected to alter agent behavior.
- medium Rogue Agent · line 85 Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.Fix: Remove any persistence mechanisms (cron jobs, startup scripts, state files). Skills should not maintain state across sessions without explicit user consent.
- medium Rogue Agent · line 119 Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.Fix: Remove any persistence mechanisms (cron jobs, startup scripts, state files). Skills should not maintain state across sessions without explicit user consent.
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00108 | $0.02696 |
| Opus 5 | $0.00054 | $0.01348 |
| Sonnet 5 | $0.00022 | $0.00539 |
| Haiku 4.5 | $0.00011 | $0.00270 |
Grade A, and why
conducting-mobile-app-penetration-test scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
1 near-identical copy found in the catalogue:
- conducting-mobile-app-penetration-test — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 227 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Conducting Mobile App Penetration Test
When to Use
- Testing mobile applications before release to identify security vulnerabilities and data protection issues
- Conducting compliance assessments against OWASP MASVS (Mobile Application Security Verification Standard) levels L1 and L2
- Evaluating the security of mobile banking, healthcare, or government applications handling sensitive data
- Testing mobile apps that interact with backend APIs to assess the end-to-end security of the mobile ecosystem
- Assessing mobile application resistance to reverse engineering, tampering, and runtime manipulation
Do not use against mobile applications without written authorization from the application owner, for distributing modified or repackaged applications, or for testing apps on the public app stores without a separate test build.
Prerequisites
- Target application IPA (iOS) and APK (Android) files or access to download from a private distribution channel
- Rooted Android device or emulator (Genymotion, Android Studio AVD) with Frida, Objection, and Magisk installed
- Jailbroken iOS device or Corellium virtual device with Frida, Objection, and SSL Kill Switch installed
- Static analysis tools: jadx (Android decompilation), Hopper/Ghidra (iOS binary analysis), MobSF (automated scanning)
- Burp Suite Professional configured as proxy for intercepting mobile app traffic with CA certificate installed on the test device
Legal Notice: This skill is for authorized security testing and educational purposes only. Unauthorized use against systems you do not own or have written permission to test is illegal and may violate computer fraud laws.
Workflow
Step 1: Static Analysis
Analyze the application binary without executing it:
Android Static Analysis:
- Decompile the APK:
jadx -d output/ target.apkto obtain Java/Kotlin source code - Review
AndroidManifest.xmlfor exported components (activities, services, receivers, content providers), permissions, and debuggable flag - Search for hardcoded secrets:
grep -rn "api_key\|password\|secret\|token\|aws_" output/ - Identify insecure data storage patterns: SharedPreferences with sensitive data, SQLite databases without encryption, files in external storage
- Check for WebView vulnerabilities:
setJavaScriptEnabled(true),addJavascriptInterface(), and loading untrusted content - Run MobSF automated scan:
python manage.py runserverand upload the APK for automated static analysis
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 8d ago First seen · 227 lines · 108 tokens per session scan A 88e772bdee5f
conducting-mobile-app-penetration-test is a skill published in the GitHub repository 26zl/cybersec-toolkit (54 stars, last pushed today), licensed MIT. It adds 108 tokens to every session and 2,696 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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