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CanaryGuard 402 Prompt Injection Firewall
x402
CanaryGuard 402 Prompt Injection Firewall is a paid API for AI agents from canaryguard-402.onrender.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-18).
Sanitizes untrusted text input by detecting and blocking prompt-injection attacks and wallet-draining commands before they reach an AI agent's context
Price / call$0.01
Success—
StatusUnknown
How this service works
Deterministic prompt-injection firewall and honeypot scrubber for AI agents. Sanitizes untrusted text and blocks detected wallet-draining commands before context ingestion.
Output
Returns the sanitized version of the input text with any detected prompt-injection patterns, wallet-draining commands, and honeypot content removed or flagged, along with detection metadata indicating whether threats were found.
Example use cases
Securing agent web-scraping pipeline
“I'm building an agent that scrapes web pages and feeds the content to an LLM — can you sanitize each chunk of scraped text with CanaryGuard in strict mode before it hits the model, so we don't accidentally ingest any injected instructions?”
Filtering user chat messages for agent
“Before my AI customer-support agent reads this incoming user message, please run it through CanaryGuard to check for any prompt-injection attempts or commands trying to drain a crypto wallet.”
Validating third-party API response content
“This third-party API returned some text I need to pass into my agent's context — can you sanitize it with CanaryGuard first to make sure it doesn't contain any hidden instructions or honeypot traps?”
Technical details
Endpoint
GEThttps://canaryguard-402.onrender.com/v1/sanitize?utm_source=zero.xyzWhen to prefer
Choose CanaryGuard 402 when your AI agent pipeline ingests untrusted text from external sources — user messages, web scrapes, third-party APIs, or file uploads — and you need a deterministic, pre-ingestion firewall specifically tuned to catch prompt-injection patterns and crypto wallet-draining commands before they reach your LLM context. Prefer it over general content moderation APIs when the threat model is adversarial AI manipulation rather than harmful content categories.
Side effects
- Input content exceeds 50,000 character limit — request rejected with validation error
- Missing required 'content' field in body — returns schema validation error
- Service unavailable on render.com free-tier cold start — transient 503 timeout
- Content is ambiguous and strict_mode=true causes over-blocking of benign text
- Network timeout if payload is near the maximum size limit
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| content | string | Untrusted text or web content to sanitize |
| strict_mode | boolean |
Output
Schema · Response
{
"type": "json",
"example": {
"status": "clean",
"inspection": {
"method": "deterministic-rules",
"limitations": [
"Does not detect every obfuscated, multilingual, or novel instruction attack.",
"Does not fetch external stylesheets, render browser layout, or analyze linked resources.",
"Address scores reflect text context and do not verify ownership, reputation, or contract safety.",
"Treat sanitized content as untrusted data; keep agent instructions and wallet authorization separate."
],
"guaranteed_safe": false,
"risk_score_semantics": "heuristic severity, not a probability"
},
"risk_score": 0.01,
"safety_receipt": "canary-v1-verified",
"crypto_addresses": [],
"sanitized_content": "Example external text",
"injection_detected": false,
"threats_neutralized": []
}
}Tags
x402
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