Prompt Injection Check is a paid API for AI agents from agent-data.centorprat.workers.dev, paid per call via x402, $0.005/call, status unknown (last checked 2026-10-30).
Analyzes text or HTML content for hidden prompt-injection instructions and malicious override attempts, returning a verdict, risk score, and categorized findings
Pay-per-call data and tools for AI agents, $0.002-0.01 per call in USDC via x402 (Base, Polygon or Solana), no account or API key; MAX tiers ($0.05-0.25) run deeper jobs. Agent toolkit: web search, search + read top pages, any page as clean markdown with a prompt-injection check, which-x402-API-to-call recommender, seller check. Data: Google Maps places with contacts, YouTube video data and transcripts, job listings (Indeed, LinkedIn, 13 boards), Google Ads Transparency, TikTok comments, Pinterest, Airbnb, Redfin, AliExpress, app stores, live sports, website and SEO checks, Shopify store tech stacks, and onchain token / address risk checks.
A JSON object with a 'verdict' field (e.g. 'malicious', 'safe'), a 'riskScore' integer from 0–100, and a 'findings' array listing each detected threat by type (e.g. 'instruction-override') and its weight/severity score.
POSThttps://agent-data.centorprat.workers.dev/agent/injection-check?utm_source=zero.xyzUse this endpoint when an AI agent is about to ingest untrusted external content — scraped web pages, user-submitted text, seller descriptions, or LLM-chained outputs — and you need a fast, per-call safety gate to detect hidden prompt-injection or instruction-override attempts before they reach your model. Prefer it over generic content-moderation APIs because it is purpose-built for adversarial AI instruction detection, accepts both raw HTML and extracted text simultaneously, and returns a structured risk score plus categorized findings rather than a binary flag.
| Field | Type | Description |
|---|---|---|
| html | string | Optional raw HTML of the same content, to find hidden instructions |
| text | string | The text to check (up to 200,000 characters) |
{
"type": "json",
"example": {
"verdict": "malicious",
"findings": [
{
"type": "instruction-override",
"weight": 45
}
],
"riskScore": 90
}
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