Tracerney

Lightweight prompt injection detection for LLM applications. Runs 100% locally.

Install

npm install @sandrobuilds/tracerney

Usage

import { Tracerney } from '@sandrobuilds/tracerney';

const tracer = new Tracerney();

const result = await tracer.scanPrompt(userInput);

if (result.suspicious) {
  console.log('⚠️ Suspicious:', result.patternName);
  // Handle flagged prompt (log, block, rate-limit, etc.)
}

What's Included

• 258 embedded attack patterns — covers known injection techniques
• Local detection — <5ms latency, zero network calls
• Zero dependencies — single npm package
• No data collection — all detection happens in your process

Result Object

{
  suspicious: boolean;     // true if pattern matched
  patternName?: string;    // e.g., "Ignore Instructions"
  severity?: string;       // "CRITICAL" | "HIGH" | "MEDIUM" | "LOW"
  blocked: boolean;        // false (Layer 1 only)
}

Detected Patterns

• Instruction overrides ("ignore all instructions")
• Role-play jailbreaks ("act as unrestricted AI")
• Context confusion attacks
• Data extraction attempts
• Code execution risks
• And 233 more...

Multi-Layer Runtime Defense

Layer 1 (Current): Pattern-based detection with 258 embedded patterns

• Fast local detection
• Zero network overhead
• Blocks known attack techniques

Layer 2 (In Development): LLM Sentinel

• Backend LLM verification for novel attacks
• Context-aware analysis
• Rate limiting to prevent cost spikes
• Coming soon...

License

MIT