Best use case
sharp-edges is best used when you need a repeatable AI agent workflow instead of a one-off prompt. It is especially useful for teams working in multi. sharp-edges
sharp-edges
Users should expect a more consistent workflow output, faster repeated execution, and less time spent rewriting prompts from scratch.
Practical example
Example input
Use the "sharp-edges" skill to help with this workflow task. Context: sharp-edges
Example output
A structured workflow result with clearer steps, more consistent formatting, and an output that is easier to reuse in the next run.
When to use this skill
- Use this skill when you want a reusable workflow rather than writing the same prompt again and again.
When not to use this skill
- Do not use this when you only need a one-off answer and do not need a reusable workflow.
- Do not use it if you cannot install or maintain the related files, repository context, or supporting tools.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/sharp-edges/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How sharp-edges Compares
| Feature / Agent | sharp-edges | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
sharp-edges
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
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SKILL.md Source
---
name: sharp-edges
description: "Identifies error-prone APIs, dangerous configurations, and footgun designs that enable security mistakes. Use when reviewing API designs, configuration schemas, cryptographic library ergonomics, or evaluating whether code follows 'secure by...
---
# Sharp Edges Analysis
Evaluates whether APIs, configurations, and interfaces are resistant to developer misuse. Identifies designs where the "easy path" leads to insecurity.
## When to Use
- Reviewing API or library design decisions
- Auditing configuration schemas for dangerous options
- Evaluating cryptographic API ergonomics
- Assessing authentication/authorization interfaces
- Reviewing any code that exposes security-relevant choices to developers
## When NOT to Use
- Implementation bugs (use standard code review)
- Business logic flaws (use domain-specific analysis)
- Performance optimization (different concern)
## Core Principle
**The pit of success**: Secure usage should be the path of least resistance. If developers must understand cryptography, read documentation carefully, or remember special rules to avoid vulnerabilities, the API has failed.
## Rationalizations to Reject
| Rationalization | Why It's Wrong | Required Action |
|-----------------|----------------|-----------------|
| "It's documented" | Developers don't read docs under deadline pressure | Make the secure choice the default or only option |
| "Advanced users need flexibility" | Flexibility creates footguns; most "advanced" usage is copy-paste | Provide safe high-level APIs; hide primitives |
| "It's the developer's responsibility" | Blame-shifting; you designed the footgun | Remove the footgun or make it impossible to misuse |
| "Nobody would actually do that" | Developers do everything imaginable under pressure | Assume maximum developer confusion |
| "It's just a configuration option" | Config is code; wrong configs ship to production | Validate configs; reject dangerous combinations |
| "We need backwards compatibility" | Insecure defaults can't be grandfather-claused | Deprecate loudly; force migration |
## Sharp Edge Categories
### 1. Algorithm/Mode Selection Footguns
APIs that let developers choose algorithms invite choosing wrong ones.
**The JWT Pattern** (canonical example):
- Header specifies algorithm: attacker can set `"alg": "none"` to bypass signatures
- Algorithm confusion: RSA public key used as HMAC secret when switching RS256→HS256
- Root cause: Letting untrusted input control security-critical decisions
**Detection patterns:**
- Function parameters like `algorithm`, `mode`, `cipher`, `hash_type`
- Enums/strings selecting cryptographic primitives
- Configuration options for security mechanisms
**Example - PHP password_hash allowing weak algorithms:**
```php
// DANGEROUS: allows crc32, md5, sha1
password_hash($password, PASSWORD_DEFAULT); // Good - no choice
hash($algorithm, $password); // BAD: accepts "crc32"
```
### 2. Dangerous Defaults
Defaults that are insecure, or zero/empty values that disable security.
**The OTP Lifetime Pattern:**
```python
# What happens when lifetime=0?
def verify_otp(code, lifetime=300): # 300 seconds default
if lifetime == 0:
return True # OOPS: 0 means "accept all"?
# Or does it mean "expired immediately"?
```
**Detection patterns:**
- Timeouts/lifetimes that accept 0 (infinite? immediate expiry?)
- Empty strings that bypass checks
- Null values that skip validation
- Boolean defaults that disable security features
- Negative values with undefined semantics
**Questions to ask:**
- What happens with `timeout=0`? `max_attempts=0`? `key=""`?
- Is the default the most secure option?
- Can any default value disable security entirely?
### 3. Primitive vs. Semantic APIs
APIs that expose raw bytes instead of meaningful types invite type confusion.
**The Libsodium vs. Halite Pattern:**
```php
// Libsodium (primitives): bytes are bytes
sodium_crypto_box($message, $nonce, $keypair);
// Easy to: swap nonce/keypair, reuse nonces, use wrong key type
// Halite (semantic): types enforce correct usage
Crypto::seal($message, new EncryptionPublicKey($key));
// Wrong key type = type error, not silent failure
```
**Detection patterns:**
- Functions taking `bytes`, `string`, `[]byte` for distinct security concepts
- Parameters that could be swapped without type errors
- Same type used for keys, nonces, ciphertexts, signatures
**The comparison footgun:**
```go
// Timing-safe comparison looks identical to unsafe
if hmac == expected { } // BAD: timing attack
if hmac.Equal(mac, expected) { } // Good: constant-time
// Same types, different security properties
```
### 4. Configuration Cliffs
One wrong setting creates catastrophic failure, with no warning.
**Detection patterns:**
- Boolean flags that disable security entirely
- String configs that aren't validated
- Combinations of settings that interact dangerously
- Environment variables that override security settings
- Constructor parameters with sensible defaults but no validation (callers can override with insecure values)
**Examples:**
```yaml
# One typo = disaster
verify_ssl: fasle # Typo silently accepted as truthy?
# Magic values
session_timeout: -1 # Does this mean "never expire"?
# Dangerous combinations accepted silently
auth_required: true
bypass_auth_for_health_checks: true
health_check_path: "/" # Oops
```
```php
// Sensible default doesn't protect against bad callers
public function __construct(
public string $hashAlgo = 'sha256', // Good default...
public int $otpLifetime = 120, // ...but accepts md5, 0, etc.
) {}
```
See config-patterns.md for detailed patterns.
### 5. Silent Failures
Errors that don't surface, or success that masks failure.
**Detection patterns:**
- Functions returning booleans instead of throwing on security failures
- Empty catch blocks around security operations
- Default values substituted on parse errors
- Verification functions that "succeed" on malformed input
**Examples:**
```python
# Silent bypass
def verify_signature(sig, data, key):
if not key:
return True # No key = skip verification?!
# Return value ignored
signature.verify(data, sig) # Throws on failure
crypto.verify(data, sig) # Returns False on failure
# Developer forgets to check return value
```
### 6. Stringly-Typed Security
Security-critical values as plain strings enable injection and confusion.
**Detection patterns:**
- SQL/commands built from string concatenation
- Permissions as comma-separated strings
- Roles/scopes as arbitrary strings instead of enums
- URLs constructed by joining strings
**The permission accumulation footgun:**
```python
permissions = "read,write"
permissions += ",admin" # Too easy to escalate
# vs. type-safe
permissions = {Permission.READ, Permission.WRITE}
permissions.add(Permission.ADMIN) # At least it's explicit
```
## Analysis Workflow
### Phase 1: Surface Identification
1. **Map security-relevant APIs**: authentication, authorization, cryptography, session management, input validation
2. **Identify developer choice points**: Where can developers select algorithms, configure timeouts, choose modes?
3. **Find configuration schemas**: Environment variables, config files, constructor parameters
### Phase 2: Edge Case Probing
For each choice point, ask:
- **Zero/empty/null**: What happens with `0`, `""`, `null`, `[]`?
- **Negative values**: What does `-1` mean? Infinite? Error?
- **Type confusion**: Can different security concepts be swapped?
- **Default values**: Is the default secure? Is it documented?
- **Error paths**: What happens on invalid input? Silent acceptance?
### Phase 3: Threat Modeling
Consider three adversaries:
1. **The Scoundrel**: Actively malicious developer or attacker controlling config
- Can they disable security via configuration?
- Can they downgrade algorithms?
- Can they inject malicious values?
2. **The Lazy Developer**: Copy-pastes examples, skips documentation
- Will the first example they find be secure?
- Is the path of least resistance secure?
- Do error messages guide toward secure usage?
3. **The Confused Developer**: Misunderstands the API
- Can they swap parameters without type errors?
- Can they use the wrong key/algorithm/mode by accident?
- Are failure modes obvious or silent?
### Phase 4: Validate Findings
For each identified sharp edge:
1. **Reproduce the misuse**: Write minimal code demonstrating the footgun
2. **Verify exploitability**: Does the misuse create a real vulnerability?
3. **Check documentation**: Is the danger documented? (Documentation doesn't excuse bad design, but affects severity)
4. **Test mitigations**: Can the API be used safely with reasonable effort?
If a finding seems questionable, return to Phase 2 and probe more edge cases.
## Severity Classification
| Severity | Criteria | Examples |
|----------|----------|----------|
| Critical | Default or obvious usage is insecure | `verify: false` default; empty password allowed |
| High | Easy misconfiguration breaks security | Algorithm parameter accepts "none" |
| Medium | Unusual but possible misconfiguration | Negative timeout has unexpected meaning |
| Low | Requires deliberate misuse | Obscure parameter combination |
## References
**By category:**
- **Cryptographic APIs**: See references/crypto-apis.md
- **Configuration Patterns**: See references/config-patterns.md
- **Authentication/Session**: See references/auth-patterns.md
- **Real-World Case Studies**: See references/case-studies.md (OpenSSL, GMP, etc.)
**By language** (general footguns, not crypto-specific):
| Language | Guide |
|----------|-------|
| C/C++ | references/lang-c.md |
| Go | references/lang-go.md |
| Rust | references/lang-rust.md |
| Swift | references/lang-swift.md |
| Java | references/lang-java.md |
| Kotlin | references/lang-kotlin.md |
| C# | references/lang-csharp.md |
| PHP | references/lang-php.md |
| JavaScript/TypeScript | references/lang-javascript.md |
| Python | references/lang-python.md |
| Ruby | references/lang-ruby.md |
See also references/language-specific.md for a combined quick reference.
## Quality Checklist
Before concluding analysis:
- [ ] Probed all zero/empty/null edge cases
- [ ] Verified defaults are secure
- [ ] Checked for algorithm/mode selection footguns
- [ ] Tested type confusion between security concepts
- [ ] Considered all three adversary types
- [ ] Verified error paths don't bypass security
- [ ] Checked configuration validation
- [ ] Constructor params validated (not just defaulted) - see config-patterns.md
## Limitations
- Use this skill only when the task clearly matches the scope described above.
- Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
- Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.Related Skills
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