Strix•IDOR 测试

IDOR

Object-level authorization failures (BOLA/IDOR) lead to cross-account data exposure and unauthorized state changes across APIs, web, mobile, and microservices. Treat every object reference as untrusted until proven bound to the caller.

Attack Surface

Scope

• Horizontal access: access another subject's objects of the same type
• Vertical access: access privileged objects/actions (admin-only, staff-only)
• Cross-tenant access: break isolation boundaries in multi-tenant systems
• Cross-service access: token or context accepted by the wrong service

Reference Locations

• Paths, query params, JSON bodies, form-data, headers, cookies
• JWT claims, GraphQL arguments, WebSocket messages, gRPC messages

Identifier Forms

• Integers, UUID/ULID/CUID, Snowflake, slugs
• Composite keys (e.g., {orgId}:{userId})
• Opaque tokens, base64/hex-encoded blobs

Relationship References

• parentId, ownerId, accountId, tenantId, organization, teamId, projectId, subscriptionId

Expansion/Projection Knobs

• fields, include, expand, projection, with, select, populate
• Often bypass authorization in resolvers or serializers

High-Value Targets

• Exports/backups/reporting endpoints (CSV/PDF/ZIP)
• Messaging/mailbox/notifications, audit logs, activity feeds
• Billing: invoices, payment methods, transactions, credits
• Healthcare/education records, HR documents, PII/PHI/PCI
• Admin/staff tools, impersonation/session management
• File/object storage keys (S3/GCS signed URLs, share links)
• Background jobs: import/export job IDs, task results
• Multi-tenant resources: organizations, workspaces, projects

Reconnaissance

Parameter Analysis

• Pagination/cursors: page[offset], page[limit], cursor, nextPageToken (often reveal or accept cross-tenant/state)
• Directory/list endpoints as seeders: search/list/suggest/export often leak object IDs for secondary exploitation

Enumeration Techniques

• Alternate types: {"id":123} vs {"id":"123"}, arrays vs scalars, objects vs scalars
• Edge values: null/empty/0/-1/MAX_INT, scientific notation, overflows
• Duplicate keys/parameter pollution: id=1&id=2, JSON duplicate keys {"id":1,"id":2} (parser precedence)
• Case/aliasing: userId vs userid vs USER_ID; alt names like resourceId, targetId, account
• Path traversal-like in virtual file systems: /files/user_123/../../user_456/report.csv

UUID/Opaque ID Sources

• Logs, exports, JS bundles, analytics endpoints, emails, public activity
• Time-based IDs (UUIDv1, ULID) may be guessable within a window

Key Vulnerabilities

Horizontal & Vertical Access

• Swap object IDs between principals using the same token to probe horizontal access
• Repeat with lower-privilege tokens to probe vertical access
• Target partial updates (PATCH, JSON Patch/JSON Merge Patch) for silent unauthorized modifications

Bulk & Batch Operations

• Batch endpoints (bulk update/delete) often validate only the first element; include cross-tenant IDs mid-array
• CSV/JSON imports referencing foreign object IDs (ownerId, orgId) may bypass create-time checks

Secondary IDOR

• Use list/search endpoints, notifications, emails, webhooks, and client logs to collect valid IDs
• Fetch or mutate those objects directly
• Pagination/cursor manipulation to skip filters and pull other users' pages

Job/Task Objects

• Access job/task IDs from one user to retrieve results for another (export/{jobId}/download, reports/{taskId})
• Cancel/approve someone else's jobs by referencing their task IDs

File/Object Storage

• Direct object paths or weakly scoped signed URLs
• Attempt key prefix changes, content-disposition tricks, or stale signatures reused across tenants
• Replace share tokens with tokens from other tenants; try case/URL-encoding variations

GraphQL

• Enforce resolver-level checks: do not rely on a top-level gate
• Verify field and edge resolvers bind the resource to the caller on every hop
• Abuse batching/aliases to retrieve multiple users' nodes in one request
• Global node patterns (Relay): decode base64 IDs and swap raw IDs
• Overfetching via fragments on privileged types

graphqlCopy code
query IDOR {
  me { id }
  u1: user(id: "VXNlcjo0NTY=") { email billing { last4 } }
  u2: node(id: "VXNlcjo0NTc=") { ... on User { email } }
}

Microservices & Gateways

• Token confusion: token scoped for Service A accepted by Service B due to shared JWT verification but missing audience/claims checks
• Trust on headers: reverse proxies or API gateways injecting/trusting headers like X-User-Id, X-Organization-Id; try overriding or removing them
• Context loss: async consumers (queues, workers) re-process requests without re-checking authorization

Multi-Tenant

• Probe tenant scoping through headers, subdomains, and path params (X-Tenant-ID, org slug)
• Try mixing org of token with resource from another org
• Test cross-tenant reports/analytics rollups and admin views which aggregate multiple tenants

WebSocket

• Authorization per-subscription: ensure channel/topic names cannot be guessed (user_{id}, org_{id})
• Subscribe/publish checks must run server-side, not only at handshake
• Try sending messages with target user IDs after subscribing to own channels

gRPC

• Direct protobuf fields (owner_id, tenant_id) often bypass HTTP-layer middleware
• Validate references via grpcurl with tokens from different principals

Integrations

• Webhooks/callbacks referencing foreign objects (e.g., invoice_id) processed without verifying ownership
• Third-party importers syncing data into wrong tenant due to missing tenant binding

Bypass Techniques

Parser & Transport

• Content-type switching: application/json ↔ application/x-www-form-urlencoded ↔ multipart/form-data
• Method tunneling: X-HTTP-Method-Override, _method=PATCH; or using GET on endpoints incorrectly accepting state changes
• JSON duplicate keys/array injection to bypass naive validators

Parameter Pollution

• Duplicate parameters in query/body to influence server-side precedence (id=123&id=456); try both orderings
• Mix case/alias param names so gateway and backend disagree (userId vs userid)

Cache & Gateway

• CDN/proxy key confusion: responses keyed without Authorization or tenant headers expose cached objects to other users
• Manipulate Vary and Accept headers
• Redirect chains and 304/206 behaviors can leak content across tenants

Race Windows

• Time-of-check vs time-of-use: change the referenced ID between validation and execution using parallel requests

Blind Channels

• Use differential responses (status, size, ETag, timing) to detect existence
• Error shape often differs for owned vs foreign objects
• HEAD/OPTIONS, conditional requests (If-None-Match/If-Modified-Since) can confirm existence without full content

Chaining Attacks

• IDOR + CSRF: force victims to trigger unauthorized changes on objects you discovered
• IDOR + Stored XSS: pivot into other users' sessions through data you gained access to
• IDOR + SSRF: exfiltrate internal IDs, then access their corresponding resources
• IDOR + Race: bypass spot checks with simultaneous requests

Testing Methodology

1. Build matrix - Subject × Object × Action matrix (who can do what to which resource)
2. Obtain principals - At least two: owner and non-owner (plus admin/staff if applicable)
3. Collect IDs - Capture at least one valid object ID per principal from list/search/export endpoints
4. Cross-channel testing - Exercise every action (R/W/D/Export) while swapping IDs, tokens, tenants
5. Transport variation - Test across web, mobile, API, GraphQL, WebSocket, gRPC
6. Consistency check - Same rule must hold regardless of transport, content-type, serialization, or gateway

Validation

1. Demonstrate access to an object not owned by the caller (content or metadata)
2. Show the same request fails with appropriately enforced authorization when corrected
3. Prove cross-channel consistency: same unauthorized access via at least two transports (e.g., REST and GraphQL)
4. Document tenant boundary violations (if applicable)
5. Provide reproducible steps and evidence (requests/responses for owner vs non-owner)

False Positives

• Public/anonymous resources by design
• Soft-privatized data where content is already public
• Idempotent metadata lookups that do not reveal sensitive content
• Correct row-level checks enforced across all channels

Impact

• Cross-account data exposure (PII/PHI/PCI)
• Unauthorized state changes (transfers, role changes, cancellations)
• Cross-tenant data leaks violating contractual and regulatory boundaries
• Regulatory risk (GDPR/HIPAA/PCI), fraud, reputational damage

Pro Tips

1. Always test list/search/export endpoints first; they are rich ID seeders
2. Build a reusable ID corpus from logs, notifications, emails, and client bundles
3. Toggle content-types and transports; authorization middleware often differs per stack
4. In GraphQL, validate at resolver boundaries; never trust parent auth to cover children
5. In multi-tenant apps, vary org headers, subdomains, and path params independently
6. Check batch/bulk operations and background job endpoints; they frequently skip per-item checks
7. Inspect gateways for header trust and cache key configuration
8. Treat UUIDs as untrusted; obtain them via OSINT/leaks and test binding
9. Use timing/size/ETag differentials for blind confirmation when content is masked
10. Prove impact with precise before/after diffs and role-separated evidence

Summary

Authorization must bind subject, action, and specific object on every request, regardless of identifier opacity or transport. If the binding is missing anywhere, the system is vulnerable.