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 allsmog/vuln-scout --skill dangerous-functionsgit clone --depth 1 https://github.com/allsmog/vuln-scoutWrote 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/allsmog/vuln-scout/dangerous-functions)<a href="https://agentmods.dev/skills/allsmog/vuln-scout/dangerous-functions"><img src="https://agentmods.dev/badge/skills/allsmog/vuln-scout/dangerous-functions/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/allsmog/vuln-scout/dangerous-functions"><img src="https://agentmods.dev/badge/skills/allsmog/vuln-scout/dangerous-functions.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00071 | $0.01185 |
| Opus 5 | $0.00036 | $0.00593 |
| Sonnet 5 | $0.00014 | $0.00237 |
| Haiku 4.5 | $0.00007 | $0.00119 |
Grade A, and why
Dangerous Functions 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 12d 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.
How it starts
The opening of the file, as written. The whole thing — 131 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Dangerous Functions Reference
Purpose
Provide comprehensive knowledge of security-sensitive functions (sinks) across programming languages for whitebox penetration testing. These functions are common targets during code review because improper use leads to critical vulnerabilities.
When to Use
Activate this skill during:
- Code review phase of whitebox security review
- Searching for potential vulnerability entry points
- Building grep patterns for sink identification
- Understanding language-specific security risks
Core Concepts
Sources vs Sinks
Sources: Entry points where user input enters the application
- HTTP parameters, headers, cookies
- File uploads, database reads
- Environment variables, command-line arguments
Sinks: Functions where malicious input causes damage
- Command execution, SQL queries
- File operations, deserialization
- Code evaluation, template rendering
Risk Categories
| Category | Impact | Common Languages |
|---|---|---|
| Command Injection | Remote Code Execution | All |
| Code Injection | Remote Code Execution | PHP, Python, JS |
| SQL Injection | Data breach | All with databases |
| Deserialization | Remote Code Execution | Java, PHP, Python, .NET |
| File Operations | LFI/RFI/Arbitrary Write | All |
| SSRF | Internal network access | All |
| Template Injection | Remote Code Execution | Python, Java, JS |
| Reentrancy | Fund theft | Solidity |
| Flash Loan Attacks | Price/state manipulation | Solidity |
| Access Control | Privilege escalation | Solidity |
Methodology
Step 1: Identify Application Language
Determine the primary language(s) used:
- Check file extensions (.php, .java, .py, .js, .cs, .go, .rb)
- Review package managers (composer.json, pom.xml, requirements.txt, package.json)
- Check framework indicators
Step 2: Load Language-Specific Reference
Consult the appropriate reference file for comprehensive sink lists:
references/php-sinks.mdfor PHP applicationsreferences/java-sinks.mdfor Java applicationsreferences/python-sinks.mdfor Python applicationsreferences/javascript-sinks.mdfor Node.js/JavaScriptreferences/dotnet-sinks.mdfor .NET/C# applicationsreferences/go-ruby-sinks.mdfor Go and Rubyreferences/rust-sinks.mdfor Rust applicationsreferences/kotlin-sinks.mdfor Kotlin/Android applications (preview -- not in supported language list)references/swift-sinks.mdfor Swift/iOS applications (preview -- not in supported language list)references/solidity-sinks.mdfor Solidity smart contracts
What ships with it
12 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.
- disable-functions-bypass.md 8.2 KB
- references/dotnet-sinks.md 5.0 KB
- references/go-ruby-sinks.md 7.9 KB
- references/java-sinks.md 4.0 KB
- references/javascript-sinks.md 7.6 KB
- references/kotlin-sinks.md 6.0 KB
- references/nginx-sinks.md 5.7 KB
- references/php-sinks.md 3.0 KB
- references/python-sinks.md 4.4 KB
- references/rust-sinks.md 8.4 KB
- references/solidity-sinks.md 13 KB
- references/swift-sinks.md 5.0 KB
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.
- 12d ago First seen · 131 lines · 71 tokens per session scan A 719da616b911
Dangerous Functions is a skill published in the GitHub repository allsmog/vuln-scout (24 stars, last pushed 3mo ago), licensed MIT. It adds 71 tokens to every session and 1,185 once invoked, about $0.0004 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 2026-08-30.
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