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A2A Indirect Prompt-Injection & Jailbreak Firewall
A2A Indirect Prompt-Injection & Jailbreak Firewall is a paid API for AI agents from preflight.agentdiet.dev, paid per call via MPP, $0.005/call, status unknown (last checked 2026-10-21).
Scans untrusted text, web pages, emails, MCP responses, or A2A payloads for hidden prompt injections 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://preflight.agentdiet.dev/v1/injection-guard)
Output
Returns a structured object indicating whether prompt injection or jailbreak content was detected in the input, along with sanitized text safe for downstream agent consumption. Likely includes a detection flag, risk classification, and cleaned version of the input.
Example use cases
Sanitize scraped web content before agent ingestion
“I'm about to feed this scraped article into my AI pipeline — can you first scan it for any hidden prompt injections or jailbreak instructions embedded in the HTML and return me only the clean, safe text?”
Guard agent inbox from malicious email payloads
“My AI assistant is reading incoming emails automatically. Before it processes this email body, please check it for indirect prompt injection attacks or hidden jailbreak commands and sanitize it.”
Validate MCP tool response before chaining
“My orchestration agent just got back a response from an external MCP tool. Can you run the injection-guard scan on this payload to make sure there are no hidden instructions trying to hijack my agent before I pass it downstream?”
Technical details
Endpoint
GEThttps://preflight.agentdiet.dev/v1/injection-guard?utm_source=zero.xyzWhen to prefer
Choose this endpoint when your agent needs to safely consume content from untrusted external sources — web scrapes, emails, third-party API or MCP tool responses, or A2A payloads — before feeding them into an LLM context window. It is specifically designed for the agentic security use case of indirect prompt injection and jailbreak detection, making it ideal for multi-agent pipelines, autonomous browsing agents, and orchestrators that must process untrusted data at runtime.
Side effects
- Empty or missing 'text' parameter returns a validation error
- Extremely long payloads may be truncated or rejected
- Network timeout on large HTML documents
- False negatives on novel or obfuscated injection patterns
- Non-UTF-8 encoded content may cause parsing errors
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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