API authorization testing for SaaS APIs
Agnite Scan replays real API requests with changed actor, token, tenant, and object context, then compares responses to detect broken access control, BOLA, and unauthorized data exposure.
Built for SaaS teams that need response-level evidence, not status-code assumptions.
Authorization Test Flow
Evidence flow
Baseline requests are replayed under changed actor, token, tenant, and object context. The response diff shows whether authorization changed the returned data.
Validate object-level access control in SaaS APIs before a customer sees the leak.
Agnite Scan is authorization-first API testing for SaaS applications. It replays real requests with mutated actor, token, tenant, and object context to verify access control at the response level.
That makes it useful for object-level access validation, broken access control testing, and cross-tenant exposure checks where 200 OK is not enough proof.
What it validates
Checks whether authenticated API requests can reach data outside the caller's scope.
How it works
Captures a valid request, then replays it with a different actor, token, tenant, or object context.
Diffs the mutated response against the baseline to confirm whether access changed.
What it detects
Flags 200 OK responses that still expose unauthorized fields or customer data.
First active capability: OWASP API1 Broken Object Level Authorization (CWE-639).
BOLA proof
Baseline Response
actor:user_19{"id": "ord_89412","tenant_id": "team_77","owner_user_id": "user_19","amount": 2400,"currency": "USD","status": "paid"}Mutated Response
actor:user_44{"id": "ord_89412","tenant_id": "team_91","owner_user_id": "user_44","amount": 2400,"currency": "USD","status": "paid","customer_email": "billing@other-tenant.io","billing_address": "111 3rd Ave, NY","last4": "4242"}401/403 coverage does not prove authorization correctness.
200 can still be a security failure
APIs can return valid transport responses while leaking unauthorized object data.
Authorization drifts at object level
Identifier and context mutations can bypass ownership boundaries without triggering 401/403.
Manual testing misses context permutations
Actor, token, tenant, and object combinations are too broad for manual validation alone.
A 4-step authorization scanning flow.
Replay the same request under changed access context, compare the response, and use the delta to decide whether authorization actually held.
Run valid requests with known actor, auth, and tenant context.
Vary object IDs, actor claims, tokens, and tenant boundary inputs.
Execute variants and diff response structure, fields, and authorization outcomes.
Return endpoint-level findings with leaked fields, risk level, and confidence.
Output model
4-step technical flow
Practical authorization checks for teams that ship APIs, manage tenants, and need reproducible evidence.
A user requests another user's invoice, project, or order by changing the object ID.
Confirm the API blocks object-level access instead of returning the record.
A request replayed under another tenant context returns records from the wrong customer.
Surface tenant boundary failures and silent cross-tenant leaks.
Backend changes alter ownership checks, claims, or tenant routing before deployment.
Catch new access-control regressions in staging with baseline vs mutated diffs.
The API returns 200 OK, but the response shape changes when the caller changes.
Use field-level evidence to detect unauthorized data exposure that status codes miss.
Built for authorization scanning, not generic API checks.
Detects unauthorized payload drift, not just status-code drift.
Generates request variants across IDs, roles, claims, and tenant scope.
Surfaces object access violations across tenant boundaries and actor shifts.
Outputs reproducible endpoint findings with diffs, leaked fields, and confidence.
Traditional API security testing checks the surface. Agnite Scan checks whether access control still holds when the caller, tenant, or object changes.
For the failure mode behind silent exposure, read BOLA in APIs: Why Your API Returns 200 OK While Leaking Data and Broken Access Control in SaaS Platforms .
Authorization defects are often silent until customer data is exposed.
Dangerous authorization failures can return 200 and look healthy in monitoring.
Role, claim, token, and tenant changes can invalidate earlier access-control assumptions.
Teams cannot reliably test every actor-object permutation without automation.
BOLA, or Broken Object Level Authorization, is when an authenticated user can reach an object they do not own.
The API confirms the caller is logged in, but it does not verify ownership or tenant scope for the specific object.
That is why a valid 200 OK response can still be a security failure if it returns another user’s record, invoice, or project data.
3-step validation flow
Teams responsible for API authorization correctness and tenant isolation.
Validate tenant isolation as endpoints and customer data paths grow.
Catch object-level authorization regressions before release.
Automate high-signal authorization validation with technical evidence.
Continuously verify access control assumptions as context and roles evolve.
It is a tool that checks API behavior for security weaknesses such as broken access control, authorization failures, and data exposure.
A BOLA scanner tests whether authenticated users can access objects they do not own by mutating identifiers and comparing the response.
Yes. A 200 response only shows transport success, not authorization correctness. The API can still leak data.
Replay real requests, change actor or tenant context, mutate object identifiers, and compare the returned data against the baseline.
API security testing is broader. Authorization testing focuses on whether the API enforces access rules correctly at the object, tenant, and role level.
Yes. The core workflow is built to surface cross-tenant object access, BOLA, and unauthorized payload drift.
It is API-first and authorization-focused rather than a generic DAST crawler. It tests real API requests and response differences.
No. Scans run externally using API requests, authentication context, and test configuration.
Endpoint, baseline vs mutated response evidence, leaked fields, risk level, and confidence score.
Use the audit path for live validation, then connect the findings to stronger SaaS architecture.
Agnite Scan shows how request mutation and response diffing expose BOLA and cross-tenant leaks. Teams that need live request-level validation can start with a SaaS security audit and then connect the findings to the underlying product architecture.