Security Findings Prompts
Last updated: May 18, 2026
Overview
These prompts surface anomalies, drift, and over-provisioning — what's wrong with current access rather than what new policies to build. Use them when investigating risk, preparing for an audit, or scoping a cleanup project.
Most prompts use [brackets] for customizable inputs like app names, attribute names, or top-N counts. Start broad, then drill in with follow-ups like "narrow to active users only", "exclude suspended accounts", or "add a column showing last login".
High-Risk Identities
Label | Prompt | Expected Output | Value |
|---|---|---|---|
High-risk regular employees |
| A ranked table of high-risk FTEs with risk scores, key HR attributes, and trend notes. | Focus investigations on the riskiest population first. |
High-risk contractors |
| A ranked table of high-risk contractors with risk scores, HR attributes, and governance concerns. | Tighten controls on contractors, who often hold elevated access with weaker oversight. |
Identity & HR Mismatches
Label | Prompt | Expected Output | Value |
|---|---|---|---|
IdP identities without an HR record |
| A list of users in your IdP with no matching record in your HRIS. | Catch ghost accounts, missed offboardings, and orphaned identities before they become incidents. |
Check a specific person's deprovisioning |
| A list of remaining access for that person, or confirmation they're fully deprovisioned. | Verify offboarding completed correctly when a manager flags a concern. |
Compare two sources of truth |
| A reconciliation table of identities present in only one system. | Find discrepancies between IdP, HRIS, and other authoritative systems. |
App-Level Anomalies
Label | Prompt | Expected Output | Value |
|---|---|---|---|
HR-attribute trends per app |
| An attribute breakdown of the app's users with expected vs. unexpected commentary. | Confirm the right population uses the app; flag terminated users, wrong departments, or contractors with admin access. |
Application access analysis (deep audit) |
| Insights mapped to org context — which licenses/roles are over-provisioned, which are appropriately scoped, and where cost can be reclaimed. | Combine cost optimization and least-privilege in one pass on a high-value app. |
Apps missing activity data |
| A table of apps without usage data and the source they're integrated from. | Identify your blind spots before relying on usage signals for cleanup decisions. |
Time-Limited & Expiring Access
Label | Prompt | Expected Output | Value |
|---|---|---|---|
Find access with no expiry |
| A list of apps configured for time-limited access alongside the users who currently have indefinite access to them. | Spot temporary access that quietly became permanent. |
Time remaining on access grants |
| A list of users with the app and their expiry date, sorted by urgency. | Plan renewals, extensions, or proactive offboarding for time-limited access. |
Access requests by expiry status |
| A split table of expiring vs. indefinite access requests for the app. | Audit whether time-limited access policies are actually being enforced in requests. |
Over-Provisioning & Waste
Label | Prompt | Expected Output | Value |
|---|---|---|---|
Over-provisioning review (top N apps) |
| A ranked table of apps with an over-provisioning label, assigned user count, and reasoning per app. | Right-size assignments to cut license spend and reduce blast radius. |
Low-activity apps |
| A table of low-activity apps with assigned users, active %, and a remediation suggestion. | Reclaim spend and reduce standing-access risk on apps no one uses. |
Unused licenses by team |
| A per-department breakdown of license waste for the app. | Target license reclamation at the teams where it'll have the biggest impact. |
Compliance & SaaS Sprawl
Label | Prompt | Expected Output | Value |
|---|---|---|---|
Email domain risk |
| A table of email domains with population share, app/group access, and worker-type mapping. | Surface risky external/alias domains and where they hold sensitive access. |
AI services sprawl |
| A grouped summary of AI tools in use, with sanctioned vs. unsanctioned signal. | Get ahead of shadow AI before it becomes a data-handling or compliance issue. |
Compliance-tier check |
| A list of Tier 1 apps per your standard (once uploaded in Knowledge Hub), plus a yes/no compliance assessment for the named app. | Quickly audit specific apps against your internal access-management standard. |