FinTechTask Prompt

Security Prompt for CrowdStrike-CLEAR Endpoint Signal Mapping to Liveness

This **Arc** task prompt takes your active **endpoint security** logging routes and the **CrowdStrike-CLEAR** person-based verification model, then wires endpoint risk to identity assurance. Arc, the deepidv credential gateway, maps each **device posture** flag your endpoint logs raise to a corresponding trust action, returns a signal-mapping matrix that ties **high-risk device posture** to **client-edge liveness attestation**, a trigger-flow configuration that steps up to sub-150ms liveness only when posture warrants it, a friction budget that keeps trusted-device users on a silent path, and a routing spec for the endpoints that fail attestation. Built for security and identity engineers at fintechs unifying **CrowdStrike CLEAR endpoint** telemetry with real-time face liveness, so a compromised or high-risk device is re-verified at the person, not just quarantined, without slowing everyone else.

How to use this prompt

1
Open Arc in the deepidv dashboard and paste the full prompt, or run it in Claude, ChatGPT, or Gemini if you are drafting the signal mapping outside the platform.
2
Replace the INPUT section with your endpoint security logging routes, the device posture flags they raise, your current liveness attestation flow, and your friction and latency budgets.
3
Run the prompt and read the signal-mapping matrix first: it ties each high-risk posture flag to a step-up liveness action and leaves trusted devices on a silent path.
4
Hand the trigger-flow configuration to your identity engineer and route the mapping matrix to your security lead; start with any high-risk flag that currently has no step-up.
5
Re-run the prompt after each endpoint-policy change and after CrowdStrike updates the CLEAR model so the mapping stays aligned before your next security review.

The prompt

Arc, evaluate our active endpoint security logging routes against the CrowdStrike-CLEAR person-based verification model. Configure a trigger flow that maps high-risk device posture flags to our sub-150ms client-edge liveness attestation without introducing user friction.

ROLE
You are Arc, the deepidv credential gateway. You read a firm's endpoint security telemetry, map its device posture signals to identity-assurance actions, and configure the trigger flow that steps up to liveness attestation only when posture warrants it.

CONTEXT
The CrowdStrike-CLEAR person-based verification model pairs endpoint device posture with person-based identity verification, so an access decision weighs both the device and the human behind it. A blunt block on any high-risk device punishes legitimate users and still does not prove who is present. The stronger control maps a high-risk posture flag to a client-edge liveness attestation that re-verifies the person inside a sub-150ms budget, while trusted-device sessions stay on a silent, friction-free path.

INPUT, the user will paste:
- The endpoint security logging routes and the device posture flags they raise
- The CrowdStrike-CLEAR model references the firm is aligning to
- The current liveness attestation flow and where in the session it runs today
- The friction budget for trusted-device users and the tolerance for step-up
- The latency budget for liveness attestation, and any open trigger questions the security team is tracking

TASKS
1. Evaluate the endpoint logging routes and classify each device posture flag by the risk it represents.
2. Map each high-risk posture flag to a client-edge liveness attestation step-up, and map trusted posture to a silent path.
3. Configure a trigger flow that fires the step-up inside the sub-150ms budget without adding friction for trusted-device sessions.
4. Specify the routing for endpoints that fail attestation, and the evidence retained per stepped-up session.

OUTPUT FORMAT, return the following structured response:

1. SIGNAL-MAPPING MATRIX
- Each device posture flag, its risk class, and the identity action it maps to (silent, step-up liveness, or block)
- The CrowdStrike-CLEAR reference behind each high-risk mapping

2. TRIGGER-FLOW CONFIGURATION
- The condition that fires the client-edge liveness attestation, and its placement against the sub-150ms budget
- The silent path for trusted-device posture, with no added step

3. FRICTION BUDGET
- The share of sessions expected to stay step-free, and the posture flags that justify a step-up
- The guardrail that prevents a low-risk flag from triggering unnecessary re-verification

4. ROUTING SPEC
- The routing and quarantine action when an endpoint fails attestation, by risk class
- The evidence bundle retained per stepped-up or failed session for a security review

Be specific about which posture flags trigger a step-up and which stay silent. Where the endpoint input is insufficient to map a flag, flag it as an open question instead of guessing.

Test it in Claude or another LLM

This prompt is built for the Arc agent inside deepidv, where Arc ingests a firm's live endpoint posture signals and steps up to client-edge liveness attestation when posture warrants it. You can dry-run the same workflow in any general LLM first with synthetic endpoint and posture data to see the mapping-matrix shape before wiring it to real telemetry.

1
Paste the full prompt into Claude, ChatGPT, or Gemini, but replace the opening 'Arc,' with a role instruction such as 'Act as an identity and endpoint-security architect mapping device posture flags to client-edge liveness attestation.' Keep the four OUTPUT sections exactly as written.
2
Under the INPUT section, paste the synthetic sample block below so the model has endpoint logging routes, posture flags, and a liveness flow to map.
3
Add one framing line: 'This is synthetic test data. Where a posture-to-liveness mapping cannot be derived from the input, flag it as an open question instead of guessing.'
4
Check the output shape: a signal-mapping matrix tying posture flags to step-up actions, a trigger-flow configuration placed against the sub-150ms budget, a friction budget that keeps trusted devices silent, and a routing spec for failed attestation. If any section invents a posture flag the input omits, tighten the role line and re-run.
5
Once the output shape is right, run it live in the deepidv dashboard where Arc ingests your real endpoint posture and enforces the step-up liveness attestation.

Synthetic sample data to paste alongside the prompt

Fake test data, safe to share with any LLM. Swap in your own once the output looks right.

ENDPOINT SECURITY LOGGING ROUTES (synthetic, fake):
- Source: EDR agent on managed and BYOD devices, streaming to SIEM ref SIEM-TEST-01
- Device posture flags (fake): unmanaged device, EDR disabled, credential-theft heuristic, impossible-travel, jailbreak/root
VERIFICATION MODEL (fake): CrowdStrike-CLEAR person-based verification, ref CLEAR-TEST-2026-03
CURRENT LIVENESS FLOW (fake): passive face liveness at login only; no re-verify mid-session; no posture trigger
FRICTION BUDGET (fake): trusted-device sessions must stay step-free; step-up allowed only on high-risk posture
LATENCY BUDGET (fake): liveness attestation hard cap 150ms; session decision soft cap 400ms
OPEN ITEM (fake): whether impossible-travel alone should trigger step-up, fake ref TRIGGER-TEST-XX

Pairs with on deepidv

Sources & further reading

FAQ

What is the CrowdStrike-CLEAR person-based verification model?

It pairs CrowdStrike endpoint device posture with CLEAR person-based identity verification, so an access decision considers both the health of the device and assurance about the human behind it. Arc treats the endpoint posture as a signal that can trigger identity re-verification, mapping a high-risk device flag to a client-edge liveness attestation rather than a blunt block.

Why map device posture to liveness instead of just blocking a risky device?

A blunt block on any high-risk device posture punishes legitimate users on a flagged machine and still does not prove who is present. Stepping up to sub-150ms liveness attestation re-verifies the person at the exact moment posture rises, so a compromised or unmanaged device is cleared or stopped on identity evidence, not a coarse device rule that generates support tickets.

How does the trigger flow avoid adding user friction?

The friction budget keeps trusted-device sessions on a silent path with no extra step, and reserves the liveness attestation for the posture flags that actually warrant it. Because the attestation runs at the client edge inside a sub-150ms budget, even a stepped-up session clears in a single fluid check rather than a redirect or a wait.

Can I use this prompt outside the deepidv dashboard?

Yes. The structure works in Claude, ChatGPT, or Gemini as a signal-mapping framework and returns the mapping matrix, trigger-flow configuration, friction budget, and routing spec. Live posture ingestion and liveness attestation against your real endpoints only run inside the deepidv dashboard through Arc.

Run it with live verification data

These prompts work in any LLM. Inside the deepidv dashboard, Luna, Arbiter, and Arc run them against your real sessions, screening lists, and audit trails.

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