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OT AI-Uplift Exposure Assessor
x402
OT AI-Uplift Exposure Assessor is a paid API for AI agents from ot-intel-api.onrender.com, paid per call via x402, $0.2/call, status unknown (last checked 2026-09-14).
Assesses how much a general-purpose AI agent lowers the barrier for an attacker to reach a vendor's OT/ICS-adjacent footprint, returning a tiered exposure verdict grounded in ICS threat intelligence.
Price / call$0.2
Success—
StatusUnknown
How this service works
Assesses how much a general-purpose AI agent (not a specialized ICS tool) lowers the barrier for an attacker to reach a vendor's OT-adjacent footprint. Grounded in Dragos's May 2026 water-utility precedent, not governance thresholds. Distinct from /ot/ai-exposure (vendor's own AI copilot). Input: vendor (required); product, internet_facing, auth_type, segmented (all optional; unknown caps tier at informational). DeepSeek-synthesized, ICD-203 language.
Output
Returns a tiered AI uplift exposure verdict (e.g. informational, low, moderate, high, critical) indicating how much a general-purpose AI agent lowers the attack barrier for the specified OT vendor's footprint, with ICS threat context grounded in Dragos's May 2026 water-utility precedent and ICD-203 language. If optional parameters are omitted, the tier is capped at 'informational'.
Example use cases
Example prompt
“What's the AI uplift exposure risk for Schneider Electric — the OT environment is internet-facing, uses single-factor auth, and is not segmented from the IT network?”
Technical details
Endpoint
GEThttps://ot-intel-api.onrender.com/ot/ai-upliftWhen to prefer
Use this endpoint when you need to understand specifically how general-purpose AI agent capabilities (not specialized ICS tools or the vendor's own AI copilot) change the attacker's ability to reach an OT/ICS vendor's footprint. Prefer this over /ot/ai-exposure (which assesses the vendor's own AI copilot risk) and over generic OT risk endpoints when the threat question is AI-mediated attack uplift. Best suited for OT security analysts, red teamers, and cyber risk teams evaluating AI-era threat posture for specific ICS vendors.
Side effects
- Missing required 'vendor' parameter returns 400 or informational-only result
- Unknown or misspelled vendor name may return a generic or uncalibrated assessment
- All optional parameters left as unknown caps the exposure tier deterministically at 'informational', limiting usefulness
- Ambiguous or unsupported auth_type values may default to 'unknown' behavior
- Service hosted on render.com free tier may experience cold-start latency or downtime
- DeepSeek synthesis may produce inconsistent results for niche or obscure vendors
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
Output
Schema · Response
{
"type": "json",
"example": {
"tlp": "TLP:CLEAR",
"vendor": "Schneider Electric",
"product": "Modicon",
"summary": "Modicon PLC line has documented CVEs with public exploit context and no MFA on the management interface; no direct AI-assisted-targeting precedent yet found in the corpus for this vendor.",
"confidence": "moderate",
"recommendations": [
"Enforce MFA on all remote engineering access",
"Monitor for password-spray patterns against gateway interfaces"
],
"ai_exposure_tier": "moderate",
"known_precedents": [],
"compensating_controls": [
"Restrict engineering workstation access via allowlisting",
"Segment Modicon management VLAN from general IT"
],
"deployment_context_used": {
"auth_type": "single-factor",
"internet_facing": "true",
"segmented_from_it": "false"
}
}
}Tags
x402
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