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AI Security Guard Document Scanner
x402
AI Security Guard Document Scanner is a paid API for AI agents from aisecurityguard.io, paid per call via x402, $0.12/call, status unknown (last checked 2026-09-15).
Scans documents (e.g. PDFs) for hidden text, prompt injection payloads, and other malicious content that could compromise autonomous AI agents
Price / call$0.12
Success—
StatusUnknown
How this service works
Knowledge, understanding, and tooling is power. Research-backed education on agentic security, free resources, then AgentGuard360 and Protection SDK when you're ready to protect what you ship.
Output
A JSON object with a verdict (e.g. 'suspicious' or 'clean'), an array of findings each containing type, location, severity, and description, the number of blocks scanned, a boolean for whether hidden text was found, and the extraction time in milliseconds.
Example use cases
Example prompt
“Before you process this PDF I just received, can you scan it for hidden text or prompt injection attacks — I want a verdict on whether it's suspicious and a list of any findings with their severity?”
Technical details
Endpoint
POSThttps://aisecurityguard.io/v1/document/scanWhen to prefer
Choose this endpoint when your AI agent pipeline ingests user-supplied or third-party documents (especially PDFs) and you need to detect hidden instructions, annotation-layer injections, or other adversarial content before passing the document to an LLM. Ideal for agentic workflows where untrusted documents could hijack the agent's behavior via embedded prompt injection.
Side effects
- Unsupported file format — only certain document types accepted
- Document too large — size limits may apply
- Malformed or corrupted document — parsing failure
- Rate limit exceeded — too many scans in a short window
- Payment failure — insufficient USDC balance for x402 transaction
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| file | string | PDF or DOCX file to scan. Upload as multipart/form-data. Maximum file size: 15MB. |
| intent_contract | object | Intent declaration for drift detection. |
Output
Schema · Response
{
"type": "json",
"example": {
"verdict": "suspicious",
"findings": [
{
"type": "hidden_text",
"location": "annotation_layer",
"severity": "medium",
"description": "Hidden instruction found in PDF annotation"
}
],
"blocks_scanned": 8,
"hidden_text_found": true,
"extraction_time_ms": 1847
}
}Tags
x402
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