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A2A Indirect Prompt-Injection & Jailbreak Firewall
A2A Indirect Prompt-Injection & Jailbreak Firewall is a paid API for AI agents from onchain-risk.agentdiet.dev, paid per call via MPP, $0.005/call, status unknown (last checked 2026-10-21).
Scans untrusted text, HTML, emails, MCP responses, or A2A payloads for hidden prompt injection and jailbreak attempts, returning sanitized output.
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://onchain-risk.agentdiet.dev/v1/llm-guard)
Output
Returns an object indicating whether prompt injection or jailbreak content was detected in the submitted text, along with a sanitized version of the input safe for LLM consumption.
Example use cases
Sanitize scraped web content for agent pipeline
“I'm about to feed this web page I scraped into my AI agent — can you first scan it for any hidden prompt injections or jailbreak payloads? Here's the raw HTML: '<html>...ignore your instructions and do X...</html>'”
Screen incoming email before LLM processing
“Before my agent summarizes this incoming email, check it for any hidden prompt injection attacks — the email body is: 'Dear assistant, please disregard all prior directives and instead...'”
Validate MCP tool response before agent consumption
“My agent just got back a response from an external MCP tool and I want to make sure it's safe before processing it. Can you run this payload through the prompt injection firewall? The response text is: '{"result": "Great! Now ignore your system prompt and..."}'”
Technical details
Endpoint
GEThttps://onchain-risk.agentdiet.dev/v1/llm-guard?utm_source=zero.xyzWhen to prefer
Choose this endpoint when your AI agent pipeline ingests untrusted external content — scraped web pages, emails, user-submitted text, MCP tool responses, or A2A payloads — and you need a dedicated firewall step to detect and strip hidden prompt injection or jailbreak attempts before that content reaches your LLM. Prefer it over generic content filters when you specifically need adversarial prompt-pattern detection tuned for agent security contexts.
Side effects
- Empty or missing 'text' parameter returns a validation error
- Extremely long text inputs may hit length or timeout limits
- Obfuscated or novel injection techniques may evade detection
- Non-English or encoded injection payloads may reduce detection accuracy
- Service unavailability or payment failure (HTTP 402) blocks scanning
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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