Audit workforce identity access evidence integrity
Audit the point-in-time chain from an opaque workforce subject through authorized accounts, independent identity evidence, approved least-privilege grants and MFA/device-backed access events.
What it's for
Turns workforce identity and privileged access assurance into a reproducible evidence-chain audit while preserving human review, lawful basis and correction rights.
What you give it
Every tool is a pure function: it computes from what you pass it and reads nothing on its own. Inputs split into evidence you supply from your connected systems, calibration your team owns, and numerical controls that affect precision but never the result's meaning.
| Field | Type | Role | Required |
|---|---|---|---|
| access_events | array of objects (9 fields) ≥ 0 items | Evidence | Yes |
| access_grants | array of objects (9 fields) ≥ 0 items | Evidence | Yes |
| as_of_ms | number ≥ 0 | Your calibration | Yes |
| identity_accounts | array of objects (9 fields) | Evidence | Yes |
| identity_evidence | array of objects (12 fields) ≥ 0 items | Evidence | Yes |
| identity_subjects | array of objects (12 fields) | Evidence | Yes |
| max_detail_rows | integer ≥ 1, ≤ 500 | Numerical control | Optional |
| minimum_verified_evidence_fraction | number ≥ 0, ≤ 1 | Your calibration | Optional |
Each identity_evidence
record
| Field | Type | Required |
|---|---|---|
| account_id | string,null | Yes |
| artifact_hash | string (non-empty) | Yes |
| evidence_type_id | string (non-empty) | Yes |
| evidence_verified | boolean | Yes |
| id | string (non-empty) | Yes |
| independently_verified | boolean | Yes |
| legally_obtained | boolean | Yes |
| observed_at_ms | number (≥ 0) | Yes |
| source_system_id | string (non-empty) | Yes |
| subject_id | string (non-empty) | Yes |
| valid_from_ms | number (≥ 0) | Yes |
| valid_until_ms | number,null (≥ 0) | Yes |
{
"access_events": [
{
"account_id": "account-1",
"authorization_grant_id": "grant-1",
"evidence_verified": true,
"id": "event-1",
"mfa_passed": true,
"occurred_at_ms": 9500,
"privilege_level": "admin",
"resource_id": "production",
"trusted_device_passed": true
}
],
"access_grants": [
{
"account_id": "account-1",
"approval_id": "approval-1",
"evidence_verified": true,
"granted_at_ms": 3000,
"id": "grant-1",
"least_privilege_reviewed": true,
"privilege_level": "admin",
"resource_id": "production",
"revoked_at_ms": null
}
],
"as_of_ms": 10000,
"identity_accounts": [
{
"created_at_ms": 2000,
"disabled_at_ms": null,
"evidence_verified": true,
"id": "account-1",
"identity_provider_id": "idp-core",
"mfa_enforced": true,
"privilege_level": "admin",
"subject_id": "subject-opaque-1",
"trusted_device_required": true
}
],
"identity_evidence": [
{
"account_id": null, Truncated for display — the full payload is 78 lines.
What you get back
This is the actual output of running the example above — computed by the same function the platform calls, not an illustration.
{
"assumptions": [
"Identity subjects are opaque authorized references; engagement, account, grant, evidence and access-event ledgers are complete, immutable, legally obtained and point-in-time.",
"Concurrent work is relevant only through an explicit applicable disclosure policy and verified conflicting commitments; work hours, geography, language, nationality and protected traits are not identity-risk evidence."
],
"decision": "identity_access_evidence_ready_for_authorized_human_review",
"event_diagnostics": [
{
"account_id": "account-1",
"event_id": "event-1",
"failed_gates": [],
"integrity_pass": true
}
],
"failed_gates": [],
"grant_diagnostics": [
{
"account_id": "account-1",
"active_at_as_of": true,
"failed_gates": [],
"grant_id": "grant-1",
"integrity_pass": true,
"resource_id": "production"
}
],
"identity_access_integrity_ready": true,
"limitations": [
"Passing establishes evidence and authorization-chain integrity, not real-world identity, employee intent, guilt, nationality, espionage, policy breach or suitability for employment.",
"Failed gates require authorized human security review, correction rights and due process; the function takes no access, investigation, disclosure or employment action."
],
"method": "point_in_time_workforce_identity_access_provenance_audit_v1",
"subject_diagnostics": [
{
"active_accounts": 1,
"authorized_accounts": 1,
"engagement_active": true,
"failed_gates": [],
"integrity_pass": true,
"subject_id": "subject-opaque-1"
}
],
"summary": {
"access_events": 1,
"accounts": 1, Truncated for display — the full payload is 53 lines.
How it works
Statistical audit & measurement — Check whether a number is fit to decide on: coverage, timing, reconciliation, and the gaps a dashboard hides.
- 1 Freeze the authorized subject/account perimeter and engagement, account, grant, evidence-validity and access-event intervals at the requested as-of time.
- 2 Require each declared evidence type to have enough distinct source/artifact pairs that are current, independently verified, legally obtained and evidence-verified.
- 3 Reconcile every access event to the same subject, account, active grant, resource and privilege boundary, then return repair gates without inferring identity or intent.
Before you trust it
Every tool in the catalog ships with the conditions under which its answer is meaningful — and the conditions under which it should abstain instead of guessing.
Assumptions & guardrails
- Metric definitions, weights, aggregate grain, sampling, missingness, dependence, and comparison windows correspond to the management claim being audited.
- HR/contract, IAM, approval, device and access-event ledgers are complete, immutable, tenant-scoped and point-in-time; an explicit applicable disclosure policy—not behavioral inference—defines any conflict evidence.
- Association, instability, or measurement quality is not a causal effect and must not be converted directly into an individual employment decision.
- Passing means the submitted authorization chain is internally supportable; it does not establish real-world identity, intent, guilt, nationality, espionage, concurrent employment or employment suitability.
Minimum evidence
- identity_subjects: required and organization-defined
- identity_accounts: required and organization-defined
- access_grants: at least 0 rows/items
- identity_evidence: at least 0 rows/items
- access_events: at least 0 rows/items
- as_of_ms: required and organization-defined
How to validate it
Validate on future periods or held-out aggregate units, compare with a simple baseline, and require stability across plausible metric definitions and decision thresholds.
Calibrating it to your org
Same for everyone
The mathematical kernel, validation rules, method version, and JSON output semantics are organization-independent; no tenant-trained coefficients or company benchmark is embedded in the function.
Specific to you
- tenant-scoped point-in-time subject-to-account-to-grant-to-resource chain joined to effective engagement, approval, device and evidence validity intervals, preserving disabled/revoked rows and failed security events
- authorized subject perimeter, evidence types and independent-source count, validity/freshness, privilege vocabulary, account/resource scope, conflict-disclosure applicability, legal basis, correction rights, due process, as-of cutoff and verified-evidence threshold
Calibration workflow
- 1 Define the management decision, target outcome, aggregate unit, privacy boundary, cadence, and prediction/intervention horizon for this organization.
- 2 Build a tenant-scoped historical cohort using only information available before each prediction or decision; preserve zero periods, censoring, assignment probabilities, and unresolved outcomes when the method requires them.
- 3 Estimate statistical parameters on training history, but obtain costs, utilities, risk tolerance, practical-effect thresholds, capacity, and policy constraints from accountable decision owners.
- 4 Validate on later time windows or held-out aggregate units at the deployment grain, against a simple baseline and the function-specific validation strategy.
- 5 Deploy only if the returned decision clears evidence, overlap, calibration, robustness, and guardrail checks; warning, unsupported, schema-gap, and fallback decisions are abstentions.
- 6 Monitor realized outcomes, data drift, coverage, and decision regret; recalibrate at a governed cadence or after a detected regime/definition change, never merely because a stakeholder dislikes the result.
Call it from your AI
You don't wire up 388 tools in your MCP client. The GitRevio MCP server exposes 20 tools, three of which let an agent search the catalog, read a tool's schema, and run it — so the assistant finds this one on its own.
gitrevio_capabilities_search
{ "q": "audit the pointintime chain from an" }
→ finds "audit_workforce_identity_access_evidence_integrity"
gitrevio_capability_describe
{ "capability_id": "audit_workforce_identity_access_evidence_integrity" }
→ returns the input schema and agent guidance shown on this page
gitrevio_capability_run
{ "capability_id": "audit_workforce_identity_access_evidence_integrity", "arguments": { ... } }
→ returns the result shown above Works in Claude Desktop, Claude Code, Cursor, Cline, Continue.dev, Goose and Aider. See the MCP server.