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A2A Indirect Prompt-Injection & Jailbreak Firewall
A2A Indirect Prompt-Injection & Jailbreak Firewall is a paid API for AI agents from whale-momentum.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 injections and jailbreak attempts, returning sanitized content.
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://whale-momentum.agentdiet.dev/v1/llm-jailbreak-defense)
Output
Returns a JSON object containing the sanitized version of the input text with any detected prompt injection or jailbreak payloads removed or flagged, enabling safe downstream LLM processing.
Example use cases
Securing agent web browsing pipeline
“I'm building an agent that browses the web and summarizes pages — before passing any scraped HTML to the LLM, run it through the prompt-injection firewall and only give me the sanitized text.”
Filtering incoming A2A tool responses
“My agent just got a response from an untrusted third-party MCP tool. Can you scan that payload for hidden jailbreak instructions before we let it influence any further actions?”
Screening user-submitted email content
“We're processing customer emails with an AI agent — please run this email body through the jailbreak firewall to check for any embedded prompt injections before the agent acts on it.”
Technical details
Endpoint
GEThttps://whale-momentum.agentdiet.dev/v1/llm-jailbreak-defense?utm_source=zero.xyzWhen to prefer
Choose this endpoint when your AI agent pipeline ingests untrusted external content — scraped web pages, third-party API responses, user emails, or A2A/MCP tool outputs — and you need a dedicated firewall layer to strip hidden prompt injections before the content reaches your LLM. Prefer this over manual filtering or generic content moderation when the threat model is specifically adversarial prompt manipulation targeting LLM behavior.
Side effects
- Empty or missing 'text' parameter returns a validation error
- Extremely long payloads may time out or exceed processing limits
- Novel obfuscated injection techniques may evade detection
- Non-text binary input may produce unexpected results
- Service unavailability returns HTTP 402 or 5xx 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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