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@asyncinnovator/hallint

v0.1.8

Published

Detect security and quality issues in AI-generated code

Readme

@asyncinnovator/hallint

Static analysis library for AI-generated code. Detects security and quality issues that AI coding assistants commonly introduce.

npm License: MIT Node


Install

npm install @asyncinnovator/hallint

Usage

Scan files

import { scan } from '@asyncinnovator/hallint'

const result = await scan({
  files: ['./src/**/*.ts'],
  rules: 'recommended',
  minSeverity: 'high',
  ignore: ['**/node_modules/**', '**/dist/**'],
})

result.findings.forEach(f => {
  console.log(`[${f.severity}] ${f.ruleId} — ${f.filePath}:${f.line}`)
  console.log(`  ${f.message}`)
  console.log(`  fix: ${f.fix}`)
})

Scan a string in memory

Useful for editor integrations, build plugins, or tests:

import { scanSource } from '@asyncinnovator/hallint'

const findings = scanSource(
  `const apiKey = "sk-abc123defgh456789xyz"`,
  'virtual.ts'
)

findings.forEach(f => console.log(f.ruleId, f.message))

API

scan(config): Promise<ScanResult>

| Field | Type | Default | Description | |---|---|---|---| | files | string \| string[] | — | Paths, globs, or directories | | rules | 'recommended' \| 'all' \| Rule[] | 'recommended' | Rule set to run | | minSeverity | Severity | 'info' | Skip findings below this level | | ignore | string[] | [] | Glob patterns to exclude | | llm | LLMConfig | — | Optional LLM layer for explanations |

scanSource(source, filePath, config?): Finding[]

Scans a source string directly without touching the file system.

ScanResult

{
  findings:     Finding[]
  scannedFiles: string[]
  durationMs:   number
  summary:      Record<'critical' | 'high' | 'medium' | 'low' | 'info', number>
}

Finding

{
  ruleId:   string   // e.g. "hardcoded-secret"
  severity: string   // "critical" | "high" | "medium" | "low" | "info"
  message:  string
  fix?:     string
  filePath: string
  line:     number
  snippet?: string
}

Rules

| Rule | Severity | What it catches | |---|---|---| | hardcoded-secret | critical | API keys, tokens, and known token prefixes (ghp_, sk-, AKIA, xoxb-, and more) | | sql-injection | critical | User input interpolated into SQL queries | | unsafe-eval | critical | eval() or new Function() with dynamic input | | missing-auth-check | high | Route handlers with no auth middleware | | xss-innerHTML | high | Non-literal values assigned to .innerHTML | | permissive-cors | high | cors({ origin: '*' }) in route handlers | | async-no-catch | medium | async functions with no error handling | | http-not-https | medium | Hardcoded http:// URLs in fetch/axios calls |


Custom rules

import type { Rule } from '@asyncinnovator/hallint'

const noConsoleLog: Rule = {
  id: 'no-console-log',
  severity: 'low',
  languages: ['js', 'ts'],
  layer: 'regex',
  pattern: /\bconsole\.log\s*\(/,
  message: 'console.log left in production code',
  fix: 'Remove or replace with a structured logger.',
}

await scan({ files: './src', rules: [noConsoleLog] })

LLM layer (optional)

await scan({
  files: './src',
  llm: {
    provider: 'anthropic',   // 'openai' | 'anthropic' | 'ollama'
    model: 'claude-haiku-4-5',
    apiKey: process.env.ANTHROPIC_API_KEY,
  },
})

No API key required when using Ollama:

llm: { provider: 'ollama', model: 'llama3', baseUrl: 'http://localhost:11434' }

Links