sharp-edges

Identifies error-prone APIs, dangerous configurations, and misuse-prone designs in security-critical code.

Updated Apr 3, 2026
One-click install
npx skills add https://github.com/Ayoub-ouederni/SENTINEL --skill sharp-edges-ayoub-ouederni
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: sharp-edges
Source: https://github.com/Ayoub-ouederni/SENTINEL/tree/main/.claude/skills/sharp-edges
Command: npx skills add https://github.com/Ayoub-ouederni/SENTINEL --skill sharp-edges-ayoub-ouederni

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve? APIs and configurations often make insecure usage the path of least resistance, letting developers accidentally introduce vulnerabilities like algorithm downgrade attacks, timing leaks, and authentication bypasses. This Skill systematically audits code for these footguns before they ship to production. ## Core Features & Use Cases - Footgun Detection: Identifies six categories of sharp edges including algorithm/mode selection, dangerous defaults, primitive vs. semantic APIs, configuration cliffs, silent failures, and stringly-typed security. - Multi-Language Reference Guides: Provides language-specific footgun patterns for C/C++, Go, Rust, Java, Kotlin, C#, PHP, JavaScript/TypeScript, Python, Ruby, and Swift. - Real-World Case Studies: Documents actual vulnerabilities in GMP, OpenSSL, pickle, YAML, and PHP strcmp to ground analysis in proven attack patterns. - Use Case: When reviewing a new authentication library, use this Skill to probe zero/empty/null edge cases, verify defaults are secure, and check whether developers can accidentally select weak algorithms like MD5 or disable signature verification. ## Quick Start Review the authentication and configuration code in this repository for sharp edges and misuse-prone API designs.

Frequently Asked Questions about sharp-edges

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I find security footguns in API design?

Map security-relevant APIs, then probe each developer choice point with zero, empty, null, and negative values. Check whether defaults are secure, whether algorithms can be downgraded, and whether errors fail silently instead of rejecting invalid input.

What is a sharp edge in API security design?

A sharp edge is a design where the easy or obvious usage path leads to insecurity, such as JWT libraries trusting the alg header or OTP verifiers accepting lifetime=0. Secure APIs make the safe choice the default or only option.

How do I detect dangerous configuration options?

Look for booleans that disable security controls, numeric parameters accepting zero or negative values without defined meaning, string configs accepting wildcards, and constructor parameters lacking validation against allowlists or bounds.

Does this analysis cover language-specific vulnerabilities?

Yes, reference guides cover footguns in C/C++, Go, Rust, Java, Kotlin, C#, PHP, JavaScript/TypeScript, Python, Ruby, and Swift. Each guide documents patterns like Go's silent integer overflow, PHP type juggling, and Java deserialization risks.

When should I not use sharp edges analysis?

Do not use it for implementation bugs, which need standard code review, or business logic flaws, which need domain-specific analysis. It targets design-level misuse resistance, not correctness of individual functions or performance optimization.