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A2A Indirect Prompt-Injection & Jailbreak Firewall
A2A Indirect Prompt-Injection & Jailbreak Firewall is a paid API for AI agents from shopify-intel.agentdiet.dev, paid per call via MPP, $0.005/call, status unknown (last checked 2026-10-21).
Scans untrusted text, HTML, web pages, emails, MCP responses, or A2A payloads for hidden prompt injections and jailbreak attempts, returning sanitized text.
Price / call$0.005
Success—
StatusUnknown
How this service works
Scans untrusted web pages, emails, MCP responses, or A2A payloads for hidden prompt injections and returns sanitized text. (Live x402 v2, IETF MPP & MCP endpoint at https://shopify-intel.agentdiet.dev/v1/guard)
Output
Returns a JSON object containing the sanitized version of the input text with any detected prompt injection or jailbreak content removed or flagged, along with detection signals indicating whether adversarial content was found.
Example use cases
Guard agent against malicious web scrape
“I just scraped this webpage to feed into my research agent — can you scan the raw HTML for any hidden prompt injection or jailbreak instructions before passing it along?”
Sanitize MCP tool response
“My agent just got back a response from an external MCP tool. Before I let the agent act on it, check the response text for any embedded adversarial instructions or jailbreak payloads.”
Verify user-submitted content safety
“A user just submitted this block of text to my AI assistant — scan it for any hidden prompt injections or attempts to hijack the system prompt before my agent reads it.”
Technical details
Endpoint
GEThttps://shopify-intel.agentdiet.dev/v1/guard?utm_source=zero.xyzWhen to prefer
Use this endpoint whenever an AI agent is about to consume untrusted external content — scraped web pages, emails, MCP tool responses, A2A messages, or user-supplied text — and needs a security checkpoint to detect and strip hidden prompt injections or jailbreak instructions before they can influence the agent's behavior. Prefer this over generic content filters when your threat model specifically involves adversarial LLM manipulation rather than traditional spam or malware.
Side effects
- Empty or missing 'text' parameter returns a 400 validation error
- Extremely long text payloads may exceed input limits or time out
- Novel or obfuscated injection techniques may evade detection
- Non-UTF-8 encoded content may cause parsing issues
- Payment failure via x402 results in a 402 response blocking the scan
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| textrequired | string | Untrusted text, HTML, or tool output to scan for hidden prompt injection or jailbreak payloads |
Output
Schema · Response
{
"type": "object"
}Reviews
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