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AgentDiet Prompt Guard (Prompt Firewall)
x402
AgentDiet Prompt Guard (Prompt Firewall) is a paid API for AI agents from x402-audit-72343955726.us-central1.run.app, paid per call via x402, $0.005/call, status unknown (last checked 2026-10-18).
Screens and validates AI prompts for security threats, injection attacks, and policy violations before they reach downstream agents or LLMs.
Price / call$0.005
Success—
StatusUnknown
How this service works
15-App Autonomous Business-to-Agent (B2A) API Hub & MCP Suite. Supports Web Distillation, On-Chain Risk, DEX Token Intelligence, B2B Lead Enrichment, Domain OSINT, Email Verification, SEC Filings, GitHub Audits, Prompt Firewall, and native HTTP 402 (x402 Base USDC).
Output
Returns a JSON object with a guard verdict indicating whether the prompt is safe or flagged, the threat classification (e.g. injection, jailbreak, policy violation), confidence level, and optionally a sanitized or annotated version of the input prompt. The response status field confirms successful evaluation.
Example use cases
Chatbot injection shield
“I'm building a customer-facing chatbot — before each user message reaches GPT-4, screen it with the prompt guard to check for injection attacks or jailbreak attempts and block anything flaggy.”
Autonomous agent input validation
“My autonomous agent is receiving task instructions from external sources. Run each instruction through the prompt firewall before execution and flag anything that looks like a policy violation or adversarial manipulation.”
Red-team audit of collected prompts
“I've collected 50 user prompts from our beta and want to audit which ones contain potential prompt injection or unsafe content — can you run them through the AgentDiet prompt guard and give me the risk verdicts?”
Technical details
Endpoint
GEThttps://x402-audit-72343955726.us-central1.run.app/v1/prompt-guard?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a dedicated, payable-per-call AI prompt security layer that integrates with x402/USDC micropayment infrastructure. Prefer it over rolling your own content filter when you need fast, agent-native prompt validation without managing model inference yourself, especially in autonomous B2A pipelines where external untrusted input reaches your LLM.
Side effects
- Empty or missing prompt input returns validation error
- Prompt exceeding token/character length limits may be rejected or truncated
- Payment failure via x402/USDC results in HTTP 402 and no evaluation
- Network timeout on Google Cloud Run cold start
- Ambiguous or borderline prompts may produce false positives or low-confidence verdicts
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| input | object | |
| output | object |
Output
Schema · Response
{
"type": "json",
"example": {
"data": {
"mode": "markdown",
"title": "Example Documentation",
"content": "# Example Documentation\nClean agent-ready markdown..."
},
"status": "ok",
"roi_proof": {
"raw_tokens": 14200,
"tokens_saved": 13520,
"roi_multiplier": 67.6,
"distilled_tokens": 680,
"compression_ratio_pct": 95.2
}
}
}Tags
x402
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