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testland/cross-tenant-data-leak-tests

Workflow-driven skill that plans and implements the cross-tenant leak-test suite - from surface inventory to the runtime CI gate a multi-tenant codebase must pass on every PR. The planning section inventories tenant-bearing surfaces (tables, APIs, object storage, search, queues, caches), classifies each by isolation model (silo / pool / bridge, per references/isolation-models.md), and derives the OWASP WSTG-ATHZ-02 coverage matrix. The battery defines the canonical test patterns (read-other-tenant-by-id, list-leak, spoofed-tenant-id-in-body, JWT-replay, FK-cross-tenant, unique-collision side channel, object-storage IDOR, search-index-direct-query, async-job-context-reload, cache-key-collision), the 404-vs-403 disclosure trade-off, the Postgres-RLS-direct patterns, and the CI integration (non-superuser non-BYPASSRLS role, fail the build on any leak). Use when designing or implementing a tenant-isolation test suite, adding the CI gate to an existing project, or investigating a leak finding.

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Impact

94%

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High

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Overview
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Files

isolation-models.mdreferences/

Tenant-isolation models

Companion reference for cross-tenant-data-leak-tests. The isolation model in use (silo / pool / bridge / vertically-partitioned) decides which test surfaces the planning section must cover.

Overview

Tenant isolation is the foundational concern of every B2B SaaS architecture: the AWS Well-Architected SaaS Lens calls it essential and treats crossing a tenant boundary as a significant, potentially unrecoverable event for a SaaS business. Isolation is a continuum, not a binary - Microsoft's Azure Architecture Center frames it as a spectrum from shared-nothing to everything-shared, with architectures often picking different points per tier (UI shared, app shared, data isolated). This is a pure reference consumed by the leak-test planning section and the tenant-leak critic; it executes nothing.

When to use

  • Designing the tenant-isolation model for a new B2B SaaS product or feature.
  • Auditing an existing model - does the testing surface match the declared isolation level?
  • Choosing what to test: each model creates a distinct set of failure modes the test suite must cover.
  • PR review of architecture changes that move components along the isolation continuum.

Tenant vs deployment

A tenant is a logical customer boundary; a deployment (also called a stamp or supertenant) is a physical set of infrastructure. One deployment can host many tenants (shared model), or each tenant can have its own deployment (silo). The tenant-to-deployment mapping is durable state: a routing table must exist somewhere so requests reach the right deployment.

The four canonical models

ModelComputeDataNetworkCost/tenantBlast radiusNoisy neighbor
Automated single-tenant (silo)DedicatedDedicatedDedicatedHighestOne tenantNone
Fully multitenant (pool)SharedShared (tenant_id discriminator)SharedLowestAll tenantsHigh
Horizontally partitioned (bridge)SharedDedicated per tenantSharedMediumData isolatedData tier: none
Vertically partitionedMixMixMixMixedPer-tierPer-tier

Per-model when-to-choose guidance, the sourced Microsoft framing, and each model's test surface are in models.md.

Isolation enforcement primitives

Tenant isolation is implemented by combining:

  • Identity context - tenant_id in JWT claims (auth.jwt() in Supabase per supabase.com/docs/guides/database/postgres/row-level-security) or AWS Cognito ID token; the source of truth for "who is this request for".
  • Authorisation policy - Postgres Row-Level Security per rls-reference, AWS IAM dynamic policies generated per tenant, application-level authorisation middleware.
  • Resource ABAC tags - tag each tenant resource with tenant-id=<x>, then enforce via IAM condition keys.
  • Network segmentation - per-tenant VPCs / subnets / security groups (silo only).
  • Encryption keys - per-tenant KMS keys (silo / bridge); useful for crypto-shredding on tenant offboarding.

Anti-patterns

Anti-patternWhy it failsFix
tenant_id filter only in application codeOne missed query path = cross-tenant leakPush the filter to the database (RLS) or row-attribute IAM
tenant_id from request header / bodySpoofable; tenant A can claim to be tenant BAlways derive tenant_id from authenticated JWT/session, never from request payload
Trust the JWT raw_user_meta_data for tenant claimsUser-modifiable per Supabase docsUse raw_app_meta_data (server-set) or a server-side claim store
Single connection pool for all tenantsOne slow tenant query blocks allPer-tenant pools, or quota-aware pools
Shared object-storage bucket without prefix isolationObject enumeration leaks across tenantsPer-tenant prefix + IAM condition on the prefix
No isolation tests in CIModels drift over timeCross-tenant leak tests in every PR per cross-tenant-data-leak-tests
Migration scripts run without tenant contextSchema changes touch all tenants at once; high blast radiusStamp pattern with progressive rollout

Test surface

The required test categories per model, plus the per-tier isolation mapping, are in test-surfaces.md. The cross-tenant data leak suite is the universal floor: even silo deployments share some surface (account-management APIs, billing, identity providers) where pool-like leaks are possible.

Limitations

  • No model is leak-proof by construction. Silo defends against most cross-tenant leaks but inherits leak risk in any shared management surface (admin UI, billing). RLS defends the DB but not application caches.
  • Cost vs isolation is a real trade-off. Per Microsoft, if a single tenant requires a given infrastructure cost, 100 tenants in pure silo require roughly 100 times that cost.
  • Compliance scope. Some regulators (e.g., FedRAMP High, certain healthcare regimes) effectively mandate silo for certain data classifications. Check counsel-of-record before assuming pool is acceptable.
  • Azure subscription / AWS account limits. Shared infrastructure reaches account-level scale limits faster than silo.

References

SKILL.md

tile.json