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RelayShield Agent Bait Scan
x402
RelayShield Agent Bait Scan is a paid API for AI agents from api.relayshield.net, paid per call via x402, $0.5/call, status unknown (last checked 2026-10-27).
Scans a GitHub repository's agent instruction files for prompt injection and bait instructions that could manipulate AI agents
Price / call$0.5
Success—
StatusUnknown
How this service works
Identity security, threat monitoring and intelligence for the agentic AI era. TAP verifier for agentic commerce, MCP Proxy Firewall for AI agents, and threat intelligence APIs backed by 725K indicators across 129 monitored marketplaces.
Output
Returns a JSON object with an overall verdict (e.g. LOW, MEDIUM, HIGH) indicating the risk level of agent-bait or prompt injection found, plus a list of specific findings detailing any suspicious instructions discovered in the repository's agent instruction files.
Example use cases
Vetting a third-party MCP server before use
“I'm about to add the MCP server at github.com/somevendor/ai-toolkit to my agent setup — can you scan that repo for any hidden bait instructions or prompt injection attempts buried in its CLAUDE.md or MCP manifests?”
Auditing an open-source coding assistant plugin
“Someone recommended I install the Cursor rules from github.com/community/cursor-rules — can you check those .cursorrules files for any adversarial instructions that might hijack my AI agent?”
Supply-chain safety check for agent infrastructure
“We're evaluating github.com/acme-ai/agent-framework for our internal AI pipeline. Can you scan its README and AGENTS.md for any bait instructions or prompt injection attacks before we deploy it?”
Technical details
Endpoint
POSThttps://api.relayshield.net/v1/payg/agent-bait-scan?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need to vet the safety of a GitHub repository's AI agent configuration files — specifically README, AGENTS.md, CLAUDE.md, .cursorrules, and MCP manifests — before allowing an AI agent to consume or act on them. It is purpose-built for detecting prompt injection and bait instructions targeting agentic AI systems, making it the right choice over generic malware scanners or URL checkers when the threat vector is adversarial agent instructions embedded in repositories.
Side effects
- Repository not found or inaccessible — returns error if the GitHub URL is invalid or the repo is private
- No agent instruction files found in repository — scan completes but findings are empty
- Network timeout if repository is very large or GitHub rate limits apply
- Malformed repository identifier returns validation error
- False negatives possible for novel or obfuscated bait instruction patterns
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| repository | string | GitHub repository URL or owner/repo whose agent instruction files (README, AGENTS.md, CLAUDE.md, .cursorrules, MCP manifests and tool descriptions) to scan for bait instructions |
Output
Schema · Response
{
"type": "json",
"example": {
"ok": true,
"data": {
"verdict": "LOW",
"findings": []
}
}
}Tags
x402
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