Supabase security testing

Supabase Security Testing

penkit51 AI — professional penetration testing skill pack. Authorized testing only.

Deep Exploitation Guide

Supabase

Security testing for Supabase applications. Focus on mis-scoped Row Level Security (RLS), unsafe RPCs, leaked service_role keys, lax Storage policies, and Edge Functions trusting headers without binding to issuer/audience/tenant.

Attack Surface

Data Access

• PostgREST: table CRUD, filters, embeddings, RPC (remote functions)
• GraphQL: pg_graphql over Postgres schema with RLS interaction
• Realtime: replication subscriptions, broadcast/presence channels

Storage

• Buckets, objects, signed URLs, public/private policies

Authentication

• Auth (GoTrue): JWTs, cookie/session, magic links, OAuth flows

Server-Side

• Edge Functions (Deno): server-side code calling Supabase with secrets

Architecture

Endpoints

• REST: https://<ref>.supabase.co/rest/v1/<table>
• RPC: https://<ref>.supabase.co/rest/v1/rpc/<fn>
• Storage: https://<ref>.supabase.co/storage/v1
• GraphQL: https://<ref>.supabase.co/graphql/v1
• Realtime: wss://<ref>.supabase.co/realtime/v1
• Auth: https://<ref>.supabase.co/auth/v1
• Functions: https://<ref>.functions.supabase.co/

Headers

• apikey: <anon-or-service> — identifies project
• Authorization: Bearer <JWT> — binds user context

Roles

• anon, authenticated — standard roles
• service_role — bypasses RLS, must never be client-exposed

Key Principle auth.uid() returns current user UUID from JWT. Policies must never trust client-supplied IDs over server context.

High-Value Targets

• Tables with sensitive data (users, orders, payments, PII)
• RPC functions (especially SECURITY DEFINER)
• Storage buckets with private files
• Edge Functions with service_role access
• Export/report endpoints generating signed outputs
• Admin/staff routes and privilege-granting endpoints

Reconnaissance

Enumerate Surfaces

/rest/v1/<table>
/rest/v1/rpc/<fn>
/storage/v1/object/public/<bucket>/
/storage/v1/object/list/<bucket>?prefix=
/graphql/v1
/auth/v1

Obtain Principals

• Unauthenticated (anon key only)
• Basic user A, user B
• Admin/staff (if available)
• Check if service_role key leaked in client bundle or Edge Function responses

Key Vulnerabilities

Row Level Security (RLS)

Enable RLS on every non-public table; absence or "permit-all" policies → bulk exposure.

Common Gaps

• Policies check auth.uid() for SELECT but forget UPDATE/DELETE/INSERT
• Missing tenant constraints (org_id/tenant_id) allow cross-tenant access
• Policies rely on client-provided columns (user_id in payload) instead of JWT
• Complex joins where policy is applied after filters, enabling inference via counts

Tests

# Compare row counts for two users
GET /rest/v1/<table>?select=*&Prefer=count=exact

# Cross-tenant probe
GET /rest/v1/<table>?org_id=eq.<other_org>
GET /rest/v1/<table>?or=(org_id.eq.other,org_id.is.null)

# Write-path
PATCH /rest/v1/<table>?id=eq.<foreign_id>
DELETE /rest/v1/<table>?id=eq.<foreign_id>
POST /rest/v1/<table> with foreign owner_id

PostgREST & REST

Filters

• eq, neq, lt, gt, ilike, or, is, in
• Embed relations: select=*,profile(*)—exploits overfetch if resolvers skip per-row checks
• Search leaks: generous LIKE/ILIKE filters combined with missing RLS → mass disclosure via wildcard queries

Headers

• Prefer: return=representation — echo writes
• Prefer: count=exact — exposure via counts
• Accept-Profile/Content-Profile — select schema

IDOR Patterns

/rest/v1/<table>?select=*&id=eq.<other_id>
/rest/v1/<table>?select=*&slug=eq.<other_slug>
/rest/v1/<table>?select=*&email=eq.<other_email>

Mass Assignment

• If RPC not used, PATCH can update unintended columns
• Verify restricted columns via database permissions/policies

RPC Functions

RPC endpoints map to SQL functions. SECURITY DEFINER bypasses RLS unless carefully coded; SECURITY INVOKER respects caller.

Anti-Patterns

• SECURITY DEFINER + missing owner checks → vertical/horizontal bypass
• set search_path left to public; function resolves unsafe objects
• Trusting client-supplied user_id/tenant_id rather than auth.uid()

Tests

# Call as different users with foreign IDs
POST /rest/v1/rpc/<fn> {"user_id": "<foreign_id>"}

# Remove JWT entirely
Authorization: Bearer <anon_token>

Verify functions perform explicit ownership/tenant checks inside SQL.

Storage

Buckets

• Public vs private; objects in storage.objects with RLS-like policies

Misconfigurations

# Public bucket with sensitive data
GET /storage/v1/object/public/<bucket>/<path>

# List prefixes without auth
GET /storage/v1/object/list/<bucket>?prefix=

# Signed URL reuse across tenants/paths

Content-Type Abuse

• Upload HTML/SVG served as text/html or image/svg+xml
• Verify X-Content-Type-Options: nosniff and Content-Disposition: attachment

Path Confusion

• Mixed case, URL-encoding, .. segments may be rejected at UI but accepted by API
• Test path normalization differences between client validation and server handling

Realtime

Endpoint: wss://<ref>.supabase.co/realtime/v1

Risks

• Channel names derived from table/schema/filters leaking other users' updates when RLS or channel guards are weak
• Broadcast/presence channels allowing cross-room join/publish without auth

Tests

• Subscribe to public:realtime changes on protected tables; confirm visibility aligns with RLS
• Attempt joining other users' channels: room:<user_id>, org:<org_id>

GraphQL

Endpoint: /graphql/v1 using pg_graphql with RLS

Risks

• Introspection reveals schema relations
• Overfetch via nested relations where resolvers skip per-row ownership checks
• Global node IDs leaked and reusable via different viewers

Tests

• Compare REST vs GraphQL responses for same principal and query shape
• Query deep nested fields; verify RLS holds at each edge

Auth & Tokens

GoTrue issues JWTs with claims (sub=uid, role, aud=authenticated).

Verification Requirements

• Issuer, audience, expiration, signature, tenant context

Pitfalls

• Storing tokens in localStorage → XSS exfiltration
• Treating apikey as identity (it's project-scoped, not user identity)
• Exposing service_role key in client bundle or Edge Function responses
• Refresh token mismanagement leading to long-lived sessions beyond intended TTL

Tests

• Replay tokens across services; check audience/issuer pinning
• Try downgraded tokens (expired/other audience) against custom endpoints

Edge Functions

Deno-based functions often initialize Supabase client with service_role.

Risks

• Trusting Authorization/apikey headers without verifying JWT against issuer/audience
• CORS: wildcard origins with credentials; reflected Authorization in responses
• SSRF via fetch; secrets exposed via error traces or logs

Tests

• Call functions with and without Authorization; compare behavior
• Try foreign resource IDs in payloads; verify server re-derives user/tenant from JWT
• Attempt to reach internal endpoints (metadata services) via function fetch

Tenant Isolation

Ensure every query joins or filters by tenant_id/org_id derived from JWT context, not client input.

Tests

• Change subdomain/header/path tenant selectors while keeping JWT tenant constant
• Export/report endpoints: confirm queries execute under caller scope

Bypass Techniques

• Content-type switching: application/json ↔ application/x-www-form-urlencoded ↔ multipart/form-data
• Parameter pollution: duplicate keys in JSON/query (PostgREST chooses last/first depending on parser)
• GraphQL+REST parity probing: protections often drift; fetch via the weaker path
• Race windows: parallel writes to bypass post-insert ownership updates

Blind Enumeration

• Use Prefer: count=exact and ETag/length diffs to infer unauthorized rows
• Conditional requests (If-None-Match) to detect object existence
• Storage signed URLs: timing/length deltas to map valid vs invalid tokens

Testing Methodology

1. Inventory surfaces - Map REST, Storage, GraphQL, Realtime, Auth, Functions endpoints
2. Obtain principals - Collect tokens for anon, user A/B, admin; check for service_role leaks
3. Build matrix - Resource × Action × Principal
4. REST vs GraphQL - Test both to find parity gaps
5. Seed IDs - Start with list/search endpoints to gather IDs
6. Cross-principal - Swap IDs, tenants, and transports across principals

Tooling

• PostgREST: httpie/curl + jq; enumerate tables; fuzz filters (or=, ilike, neq, is.null)
• GraphQL: graphql-inspector, voyager; deep queries for field-level enforcement
• Realtime: custom ws client; subscribe to suspicious channels; diff payloads per principal
• Storage: enumerate bucket listing APIs; script signed URL patterns
• Auth/JWT: jwt-cli/jose to validate audience/issuer; replay against Edge Functions
• Policy diffing: maintain request sets per role; compare results across releases

Validation Requirements

• Owner vs non-owner requests for REST/GraphQL showing unauthorized access (content or metadata)
• Mis-scoped RPC or Storage signed URL usable by another user/tenant
• Realtime or GraphQL exposure matching missing policy checks
• Minimal reproducible requests with role contexts documented

Platform Methodology

Supabase Security Testing

penkit51 AI — professional penetration testing skill pack. Authorized testing only.

Deep Exploitation Guide

Supabase

Security testing for Supabase applications. Focus on mis-scoped Row Level Security (RLS), unsafe RPCs, leaked service_role keys, lax Storage policies, and Edge Functions trusting headers without binding to issuer/audience/tenant.

Attack Surface

Data Access

• PostgREST: table CRUD, filters, embeddings, RPC (remote functions)
• GraphQL: pg_graphql over Postgres schema with RLS interaction
• Realtime: replication subscriptions, broadcast/presence channels

Storage

• Buckets, objects, signed URLs, public/private policies

Authentication

• Auth (GoTrue): JWTs, cookie/session, magic links, OAuth flows

Server-Side

• Edge Functions (Deno): server-side code calling Supabase with secrets

Architecture

Endpoints

• REST: https://<ref>.supabase.co/rest/v1/<table>
• RPC: https://<ref>.supabase.co/rest/v1/rpc/<fn>
• Storage: https://<ref>.supabase.co/storage/v1
• GraphQL: https://<ref>.supabase.co/graphql/v1
• Realtime: wss://<ref>.supabase.co/realtime/v1
• Auth: https://<ref>.supabase.co/auth/v1
• Functions: https://<ref>.functions.supabase.co/

Headers

• apikey: <anon-or-service> — identifies project
• Authorization: Bearer <JWT> — binds user context

Roles

• anon, authenticated — standard roles
• service_role — bypasses RLS, must never be client-exposed

Key Principle auth.uid() returns current user UUID from JWT. Policies must never trust client-supplied IDs over server context.

High-Value Targets

• Tables with sensitive data (users, orders, payments, PII)
• RPC functions (especially SECURITY DEFINER)
• Storage buckets with private files
• Edge Functions with service_role access
• Export/report endpoints generating signed outputs
• Admin/staff routes and privilege-granting endpoints

Reconnaissance

Enumerate Surfaces

/rest/v1/<table>
/rest/v1/rpc/<fn>
/storage/v1/object/public/<bucket>/
/storage/v1/object/list/<bucket>?prefix=
/graphql/v1
/auth/v1

Obtain Principals

• Unauthenticated (anon key only)
• Basic user A, user B
• Admin/staff (if available)
• Check if service_role key leaked in client bundle or Edge Function responses

Key Vulnerabilities

Row Level Security (RLS)

Enable RLS on every non-public table; absence or "permit-all" policies → bulk exposure.

Common Gaps

• Policies check auth.uid() for SELECT but forget UPDATE/DELETE/INSERT
• Missing tenant constraints (org_id/tenant_id) allow cross-tenant access
• Policies rely on client-provided columns (user_id in payload) instead of JWT
• Complex joins where policy is applied after filters, enabling inference via counts

Tests

# Compare row counts for two users
GET /rest/v1/<table>?select=*&Prefer=count=exact

# Cross-tenant probe
GET /rest/v1/<table>?org_id=eq.<other_org>
GET /rest/v1/<table>?or=(org_id.eq.other,org_id.is.null)

# Write-path
PATCH /rest/v1/<table>?id=eq.<foreign_id>
DELETE /rest/v1/<table>?id=eq.<foreign_id>
POST /rest/v1/<table> with foreign owner_id

PostgREST & REST

Filters

• eq, neq, lt, gt, ilike, or, is, in
• Embed relations: select=*,profile(*)—exploits overfetch if resolvers skip per-row checks
• Search leaks: generous LIKE/ILIKE filters combined with missing RLS → mass disclosure via wildcard queries

Headers

• Prefer: return=representation — echo writes
• Prefer: count=exact — exposure via counts
• Accept-Profile/Content-Profile — select schema

IDOR Patterns

/rest/v1/<table>?select=*&id=eq.<other_id>
/rest/v1/<table>?select=*&slug=eq.<other_slug>
/rest/v1/<table>?select=*&email=eq.<other_email>

Mass Assignment

• If RPC not used, PATCH can update unintended columns
• Verify restricted columns via database permissions/policies

RPC Functions

RPC endpoints map to SQL functions. SECURITY DEFINER bypasses RLS unless carefully coded; SECURITY INVOKER respects caller.

Anti-Patterns

• SECURITY DEFINER + missing owner checks → vertical/horizontal bypass
• set search_path left to public; function resolves unsafe objects
• Trusting client-supplied user_id/tenant_id rather than auth.uid()

Tests

# Call as different users with foreign IDs
POST /rest/v1/rpc/<fn> {"user_id": "<foreign_id>"}

# Remove JWT entirely
Authorization: Bearer <anon_token>

Verify functions perform explicit ownership/tenant checks inside SQL.

Storage

Buckets

• Public vs private; objects in storage.objects with RLS-like policies

Misconfigurations

# Public bucket with sensitive data
GET /storage/v1/object/public/<bucket>/<path>

# List prefixes without auth
GET /storage/v1/object/list/<bucket>?prefix=

# Signed URL reuse across tenants/paths

Content-Type Abuse

• Upload HTML/SVG served as text/html or image/svg+xml
• Verify X-Content-Type-Options: nosniff and Content-Disposition: attachment

Path Confusion

• Mixed case, URL-encoding, .. segments may be rejected at UI but accepted by API
• Test path normalization differences between client validation and server handling

Realtime

Endpoint: wss://<ref>.supabase.co/realtime/v1

Risks

• Channel names derived from table/schema/filters leaking other users' updates when RLS or channel guards are weak
• Broadcast/presence channels allowing cross-room join/publish without auth

Tests

• Subscribe to public:realtime changes on protected tables; confirm visibility aligns with RLS
• Attempt joining other users' channels: room:<user_id>, org:<org_id>

GraphQL

Endpoint: /graphql/v1 using pg_graphql with RLS

Risks

• Introspection reveals schema relations
• Overfetch via nested relations where resolvers skip per-row ownership checks
• Global node IDs leaked and reusable via different viewers

Tests

• Compare REST vs GraphQL responses for same principal and query shape
• Query deep nested fields; verify RLS holds at each edge

Auth & Tokens

GoTrue issues JWTs with claims (sub=uid, role, aud=authenticated).

Verification Requirements

• Issuer, audience, expiration, signature, tenant context

Pitfalls

• Storing tokens in localStorage → XSS exfiltration
• Treating apikey as identity (it's project-scoped, not user identity)
• Exposing service_role key in client bundle or Edge Function responses
• Refresh token mismanagement leading to long-lived sessions beyond intended TTL

Tests

• Replay tokens across services; check audience/issuer pinning
• Try downgraded tokens (expired/other audience) against custom endpoints

Edge Functions

Deno-based functions often initialize Supabase client with service_role.

Risks

• Trusting Authorization/apikey headers without verifying JWT against issuer/audience
• CORS: wildcard origins with credentials; reflected Authorization in responses
• SSRF via fetch; secrets exposed via error traces or logs

Tests

• Call functions with and without Authorization; compare behavior
• Try foreign resource IDs in payloads; verify server re-derives user/tenant from JWT
• Attempt to reach internal endpoints (metadata services) via function fetch

Tenant Isolation

Ensure every query joins or filters by tenant_id/org_id derived from JWT context, not client input.

Tests

• Change subdomain/header/path tenant selectors while keeping JWT tenant constant
• Export/report endpoints: confirm queries execute under caller scope

Bypass Techniques

• Content-type switching: application/json ↔ application/x-www-form-urlencoded ↔ multipart/form-data
• Parameter pollution: duplicate keys in JSON/query (PostgREST chooses last/first depending on parser)
• GraphQL+REST parity probing: protections often drift; fetch via the weaker path
• Race windows: parallel writes to bypass post-insert ownership updates

Blind Enumeration

• Use Prefer: count=exact and ETag/length diffs to infer unauthorized rows
• Conditional requests (If-None-Match) to detect object existence
• Storage signed URLs: timing/length deltas to map valid vs invalid tokens

Testing Methodology

1. Inventory surfaces - Map REST, Storage, GraphQL, Realtime, Auth, Functions endpoints
2. Obtain principals - Collect tokens for anon, user A/B, admin; check for service_role leaks
3. Build matrix - Resource × Action × Principal
4. REST vs GraphQL - Test both to find parity gaps
5. Seed IDs - Start with list/search endpoints to gather IDs
6. Cross-principal - Swap IDs, tenants, and transports across principals

Tooling

• PostgREST: httpie/curl + jq; enumerate tables; fuzz filters (or=, ilike, neq, is.null)
• GraphQL: graphql-inspector, voyager; deep queries for field-level enforcement
• Realtime: custom ws client; subscribe to suspicious channels; diff payloads per principal
• Storage: enumerate bucket listing APIs; script signed URL patterns
• Auth/JWT: jwt-cli/jose to validate audience/issuer; replay against Edge Functions
• Policy diffing: maintain request sets per role; compare results across releases

Validation Requirements

• Owner vs non-owner requests for REST/GraphQL showing unauthorized access (content or metadata)
• Mis-scoped RPC or Storage signed URL usable by another user/tenant
• Realtime or GraphQL exposure matching missing policy checks
• Minimal reproducible requests with role contexts documented

Validation & Reporting

• Confirm every finding with reproducible PoC before reporting
• Document: severity (CVSS), affected asset, steps, evidence, remediation
• Use record_vulnerability when running inside the penkit51 platform
• Chain low-severity findings into higher-impact attack paths
• Never report without evidence — distinguish hypothesis from confirmed vuln

Validation & Reporting

• Confirm every finding with reproducible PoC before reporting
• Document: severity (CVSS), affected asset, steps, evidence, remediation
• Use record_vulnerability when running inside the penkit51 platform
• Chain low-severity findings into higher-impact attack paths
• Never report without evidence — distinguish hypothesis from confirmed vuln