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    Spring Boot Multi-tenant SaaS

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    Audit Spring Boot and Java SaaS backends for tenant isolation, context propagation, and cross-tenant data leaks.

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    Spring Boot Multi-tenant SaaS

    Spring Boot Multi-tenant SaaS

    Example session with this skill installed

    Audit our multi-tenancy in the /app folder. We use Spring Boot with a schema-per-tenant approach and PgBouncer. Check for data leaks.

    • Read your context and instructions
    • Compiled the spring boot multi-tenant

    I have completed the multi-tenant architecture audit for the /app directory. I identified a

    schema-per-tenant model with high confidence based on the TenantIdentifierResolver implementation.

    Multi-Tenant Audit Report — backend-service @ 2023-10-24

    Scope: src/main/java/**, src/main/resources/**. Tenancy model: Schema-per-tenant (High confidence).

    Summary — P0: 1 | P1: 2 | P2: 0 | Can't-tell: 1

    Findings

    [P0] MT-02 — Session-level SET with Connection Pooler

    • Evidence: src/main/java/com/saas/config/TenantSchemaInterceptor.java:42
    statement.execute("SET search_path TO " + tenantId);

    Why it matters: Using SET instead of SET LOCAL inside a transaction while using PgBouncer can leak the schema context to the next tenant using the same physical connection.

    How to verify: Deploy to a staging env with PgBouncer in transaction mode and trace schema resolution across concurrent requests.

    Suggested fix: Wrap in a transaction and use SET LOCAL search_path TO... or use a dedicated MultiTenantConnectionProvider.

    [P1] MT-06 — Async path without tenant propagation

    • Evidence: src/main/java/com/saas/service/ReportService.java:112

    Why it matters: The @Async method generateExport() triggers without capturing the TenantContext. The background thread will default to the 'public' schema or fail.

    • Suggested fix: Use a TaskDecorator to copy the ThreadLocal context to the new thread.

    [P1] MT-04 — Cache keys without tenant prefix

    • Evidence: src/main/java/com/saas/repository/ProductRepo.java:15

    Why it matters: @Cacheable(value = "products") lacks a tenant discriminator. Tenant A may see Tenant B's cached products.

    • Suggested fix: Update the cache key to include tenantId: key = "#root.target.tenantId + #id".

    Next steps

    1. Patch the SET LOCAL P0 finding immediately to prevent cross-contamination in production.
    2. Implement a TaskDecorator for the ThreadPoolTaskExecutor to fix the async leaks.
    3. Update the RedisCacheManager configuration to globally prefix keys with the tenant identifier.

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    About this skill

    Building multi-tenant SaaS on Spring Boot is high-stakes. A single missing ThreadLocal cleanup or a forgotten SET LOCAL search_path can lead to cross-tenant data leaks. This skill performs a targeted static analysis of your Java backend to ensure tenant isolation is ironclad across synchronous and asynchronous execution paths.

    What it does

    • Identify tenancy models by detecting schema-per-tenant, row-level, or database-per-tenant patterns in your source code.
    • Trace context propagation through HTTP filters, @Async methods, @Scheduled jobs, and Kafka consumers.
    • Audit data access for native queries that bypass scoping and connection pooler misconfigurations like session-level SET commands.
    • Scan cache and logs to ensure Redis keys and audit trails are correctly scoped with tenant prefixes.
    • Check provisioning logic for idempotency and migration safety across per-tenant Flyway instances.

    How it works

    1. Recon Phase: Scans for tenant_id columns, search_path wiring, and JWT parsing to establish the current isolation strategy.
    2. Propagation Trace: Maps every execution path to verify the TenantContext is set before business logic executes and cleared in finally blocks.
    3. Severity Audit: Executes a checklist of P0 to P2 findings, verifying each against specific file and line references.
    4. Report Generation: Produces a structured audit report with evidence snippets, risk assessments, and concrete remediation steps.

    Frameworks & tools

    Built specifically for Spring Boot and Java environments. It analyzes components like Spring Security, Hibernate, Flyway, Redis, Kafka, and PostgreSQL connection poolers like PgBouncer.

    Why this beats prompting it yourself

    Generic AI reviews often miss the subtle lifecycle of a ThreadLocal or the nuances of how a connection pooler interacts with PostgreSQL schemas. This skill uses a rigid severity-ordered checklist designed specifically for SaaS architecture, ensuring no execution path or caching layer is left unverified.

    Use cases

    • Reviewing a new microservice for tenant isolation before it goes to production.
    • Auditing legacy code for potential data leaks after migrating from row-level to schema-per-tenant.
    • Verifying that background workers and cron jobs are correctly scoped to specific tenants.
    • Ensuring per-tenant database migrations won't conflict during auto-provisioning.

    Known limitations

    This is a static analysis tool that reads code only. It cannot detect runtime environmental misconfigurations or infrastructure-level leaks outside of the application code.

    How to use

    Skills on Agensi run inside your AI agent. Copy the prompt, paste it into your agent, and it connects to Agensi and installs this skill for you. If a payment is needed, your agent shows it to you first.

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