scan_injection

ai.tunnelmind/data · Verify this server

Runs a curated signature corpus over a piece of untrusted text — content an agent is about to consume, a retrieved document, a tool result, an email body — and returns the matched injection patterns plus a bounded 0..1 risk score. This is a signal, never a policy decision: the caller decides what to do with a flagged input. Detected classes: instruction_override (ignore/override previous rules), role_reassignment (you are now DAN / developer mode), exfiltration (leak the system prompt or a secret to a URL), tool_smuggling (covertly invoke a tool, delete/destroy data), boundary_spoof (fake system/assistant turn delimiters). Input is normalized first to blunt cheap evasions (zero-width characters, smart quotes, whitespace padding). Use this tool when: - You are an agent about to feed retrieved or third-party text into a model and want to check it for embedded instructions first. - You are triaging why a tool description or web page looks suspicious. Do NOT use this tool when: - You want a trust verdict on a domain or entity — use `cross_lens_verify`. - You want to scan a whole MCP server's tools — use `scan_mcp`. Inputs: - `text` (body, required): the untrusted text to scan. Max 200,000 chars. Returns: - `flagged`: true if any signature matched. - `score`: bounded 0..1 risk score (saturating — one high-severity hit is already strongly flagged; many hits approach but never exceed 1). - `severity_max`: highest severity among matches (`high`/`medium`/`low`) or null. - `classes`: distinct injection classes matched. - `matches`: each matched signature `{ id, class, severity, excerpt }`. Cost: - Free. No API key required. Pure edge computation, no external calls. Latency: - Typical <20ms.