{"uid":"cap_J8_D0hk0cdm6FaDESf7DC","slug":"company-enrich-agentdiet-dev-a2a-indirect-prompt-injection-jailbreak-d05c27fc","name":"A2A Indirect Prompt-Injection & Jailbreak Firewall","description":"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://company-enrich.agentdiet.dev/v1/llm-jailbreak-defense)","url":"https://company-enrich.agentdiet.dev/v1/llm-jailbreak-defense?utm_source=zero.xyz","method":"GET","headers":{},"bodySchema":{"type":"object","required":["text"],"properties":{"text":{"type":"string","minLength":1,"description":"Untrusted text, HTML, or tool output to scan for hidden prompt injection or jailbreak payloads"}}},"responseSchema":{"type":"object"},"example":null,"exampleRequest":null,"tags":[],"displayCostAmount":"0.005","displayCostAsset":"USD","priceDynamic":false,"priceHint":null,"priceStatus":"priced","priceSource":"probe","requiresHandshake":false,"reviewCount":0,"rating":{"score":"0.00","successRate":"0.00","reviews":0,"stars":null,"state":"unrated"},"availabilityStatus":"unknown","priceObserved":null,"sessionDeposit":null,"pricing":{"kind":"static","summary":"$0.005/call","primary":{"kind":"static","protocol":"mpp","network":"tempo","amountUsd":"0.005","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"mpp","network":"tempo","amountUsd":"0.005","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_sVFLsUXXrYkEVNsDOHZOv","protocol":"mpp","methodType":"crypto","chain":"tempo","mode":"charge","costAmount":"0.005","costPer":"request","priority":0,"asset":"0x833589fcd6edb6e08f4c7c32d4f71b54bda02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":"company-enrich.agentdiet.dev","brandSlug":"company-enrich-agentdiet-dev-mpp","brandBaseUrl":"https://company-enrich.agentdiet.dev","brandDocsUrl":null,"whatItDoes":"Scans untrusted text, HTML, emails, MCP responses, or A2A payloads for hidden prompt injections and jailbreak attempts, returning sanitized output.","exampleAgentPrompt":"Before you process that scraped web page content, run it through the prompt-injection firewall to check for any hidden jailbreak instructions or adversarial text — here's the raw HTML: '<html>...ignore previous instructions and...</html>'","exampleUseCases":[{"title":"Secure web scraping pipeline for agents","prompt":"I'm building an agent that browses the web and I'm worried about prompt injection on malicious pages. Can you scan this scraped page content for any hidden instructions or jailbreak payloads before you summarize it for me?"},{"title":"Email inbox safety for AI assistants","prompt":"My AI assistant reads my emails and drafts replies. Before processing this email I just received, can you check it for any hidden prompt injection attacks that might try to hijack my assistant's behavior?"},{"title":"MCP tool response sanitization","prompt":"I got this response back from an external MCP tool and I want to make sure it's safe before I feed it into my agent's context. Can you scan it for any embedded jailbreak instructions or adversarial content?"}],"resultDescription":"Returns a structured object containing the scan result — whether prompt injection or jailbreak content was detected, and a sanitized version of the input text with malicious instructions removed or flagged, safe to pass downstream to an LLM or agent pipeline.","failureModes":["Empty or missing 'text' parameter returns a validation error","Extremely long inputs may be truncated or rejected","False negatives possible for novel or obfuscated injection techniques","False positives may flag legitimate instruction-style text as malicious","Service unavailability or timeout if the endpoint is unreachable"],"whenToPreferThis":"Choose this endpoint when your agent pipeline ingests untrusted external content — scraped web pages, user-submitted text, emails, tool outputs, or A2A/MCP payloads — and you need to screen for indirect prompt injection or jailbreak attempts before passing that content to an LLM. It is especially valuable in agentic workflows where external data is automatically inserted into prompts, making the attack surface large. Prefer this over generic content moderation tools when the specific threat model is adversarial manipulation of AI agent behavior rather than general toxicity or spam.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-21T07:25:45.732Z","isFirstParty":false,"canonicalSlug":"company-enrich-agentdiet-dev-a2a-indirect-prompt-injection-jailbreak-90291d00"}