Modèles d’isolation des données des locataires au niveau des lignes
Imposez les frontières entre locataires dans les requêtes avec la sécurité au niveau des lignes et des couches d’accès aux données limitées au périmètre approprié.
Modèles d’isolation des données des locataires au niveau des lignes est une leçon Next.js 15 Fullstack (App Router + Server Actions) gratuite sur CoddyKit. Ceci est la leçon 2 sur 4. Tu peux lire la leçon complète ci-dessous gratuitement — puis la pratiquer en direct dans le navigateur avec un éditeur de code intégré et un tuteur IA 24/7. Elle fait partie du parcours d'apprentissage Next.js 15 Fullstack (App Router + Server Actions), et ta progression se synchronise sur le web et l'application CoddyKit. Le cours Next.js 15 Fullstack (App Router + Server Actions) comprend 4 leçons au total.
Certaines parties de cette leçon n'ont pas encore été traduites et s'affichent en anglais.
Why Tenant Isolation Is a First-Class Concern
In a multi-tenant SaaS application, every user belongs to a tenant (an organisation, workspace, or account). Without explicit isolation, a single bug in a query can expose one tenant's data to another — a catastrophic security breach.
- Logical isolation stores all tenants in shared tables, distinguished by a
tenant_idcolumn. - Physical isolation gives each tenant their own schema or database — simpler security, but far more expensive to operate.
- Most SaaS products choose logical isolation and enforce boundaries in the application layer, the database layer, or both.
This lesson focuses on row-level isolation patterns inside a Next.js 15 App Router application backed by PostgreSQL, showing how to make tenant leakage structurally impossible rather than relying on developer discipline alone.
The Naive Approach and Its Risks
The most common mistake is sprinkling WHERE tenant_id = ? manually throughout the codebase. This pattern is fragile: any query that forgets the clause leaks data.
Consider this vulnerable Server Action:
'use server';
import { db } from '@/lib/db';
// DANGEROUS: tenant_id is never checked
export async function getInvoices() {
// This returns ALL invoices from ALL tenants!
const invoices = await db.query(
'SELECT * FROM invoices ORDER BY created_at DESC'
);
return invoices.rows;
}Resolving the Current Tenant in Next.js 15
Before we can scope any query, we need a reliable way to identify the current tenant. In Next.js 15, the idiomatic place is a server-side utility that reads the session from a cookie or JWT and resolves the tenant.
Key rules:
- Never trust a tenant ID supplied by the client in a request body or query string — always derive it from the verified session.
- Throw an error early if no valid session exists, so downstream code can never accidentally execute without a tenant context.
// lib/tenant.ts
import { cookies } from 'next/headers';
import { verifyJwt } from '@/lib/auth';
export interface TenantContext {
tenantId: string;
userId: string;
}
export async function requireTenantContext(): Promise<TenantContext> {
const cookieStore = await cookies();
const token = cookieStore.get('session')?.value;
if (!token) {
throw new Error('Unauthenticated');
}
const payload = await verifyJwt(token);
if (!payload?.tenantId || !payload?.userId) {
throw new Error('Invalid session: missing tenant context');
}
return {
tenantId: payload.tenantId as string,
userId: payload.userId as string,
};
}Building a Scoped Data Access Layer (DAL)
A scoped data access layer centralises tenant filtering so that no individual query can accidentally omit it. The idea is simple: create repository functions that require a TenantContext parameter, and always apply it.
This makes the tenant boundary visible in every function signature — if you call a data function without a context, TypeScript refuses to compile.
// lib/dal/invoices.ts
import { db } from '@/lib/db';
import type { TenantContext } from '@/lib/tenant';
export interface Invoice {
id: string;
tenantId: string;
amount: number;
status: string;
createdAt: Date;
}
export async function listInvoices(
ctx: TenantContext,
page = 1,
pageSize = 20
): Promise<Invoice[]> {
const offset = (page - 1) * pageSize;
const result = await db.query<Invoice>(
`SELECT id, tenant_id AS "tenantId", amount, status, created_at AS "createdAt"
FROM invoices
WHERE tenant_id = $1
ORDER BY created_at DESC
LIMIT $2 OFFSET $3`,
[ctx.tenantId, pageSize, offset]
);
return result.rows;
}
export async function getInvoiceById(
ctx: TenantContext,
invoiceId: string
): Promise<Invoice | null> {
const result = await db.query<Invoice>(
`SELECT id, tenant_id AS "tenantId", amount, status, created_at AS "createdAt"
FROM invoices
WHERE tenant_id = $1 AND id = $2`,
[ctx.tenantId, invoiceId]
);
return result.rows[0] ?? null;
}Using the DAL in Server Actions
With the DAL in place, Server Actions become thin orchestrators: resolve the tenant context, call the DAL, and return data. The tenant filter is enforced structurally, not by convention.
Notice that requireTenantContext() is called at the top of every action — if it throws, the action aborts before any data is touched.
'use server';
import { requireTenantContext } from '@/lib/tenant';
import { listInvoices, getInvoiceById } from '@/lib/dal/invoices';
export async function fetchInvoicesAction(page: number = 1) {
const ctx = await requireTenantContext();
return listInvoices(ctx, page);
}
export async function fetchInvoiceAction(invoiceId: string) {
const ctx = await requireTenantContext();
const invoice = await getInvoiceById(ctx, invoiceId);
if (!invoice) {
// Could be not found OR a cross-tenant access attempt —
// return the same error to avoid leaking existence information.
throw new Error('Invoice not found');
}
return invoice;
}PostgreSQL Row-Level Security (RLS)
The application-layer DAL is a strong first line of defence, but a second line exists at the database level: PostgreSQL Row-Level Security (RLS). With RLS enabled, the database itself rejects any query that touches rows belonging to a different tenant — even if the application forgets to filter.
The pattern works by:
- Enabling RLS on every multi-tenant table.
- Creating a policy that compares
tenant_idagainst a session variable set by the application before each query. - Setting the variable via
SET LOCAL app.current_tenant_id = '...'inside a transaction.
-- Run once per table during migrations
ALTER TABLE invoices ENABLE ROW LEVEL SECURITY;
-- Deny all access by default (belt-and-suspenders)
ALTER TABLE invoices FORCE ROW LEVEL SECURITY;
-- Allow SELECT/INSERT/UPDATE/DELETE only for the current tenant
CREATE POLICY tenant_isolation ON invoices
USING (tenant_id = current_setting('app.current_tenant_id', true))
WITH CHECK (tenant_id = current_setting('app.current_tenant_id', true));
-- The app sets this variable in every transaction:
-- SET LOCAL app.current_tenant_id = '<uuid>';Wiring RLS into the Database Client
To make RLS work automatically, wrap every database operation in a transaction that first sets the app.current_tenant_id session variable. This can be done with a single helper that wraps pg's PoolClient.
This ensures the tenant variable is always set before any query runs, and is automatically cleared when the transaction ends.
// lib/db.ts
import { Pool, PoolClient } from 'pg';
export const pool = new Pool({
connectionString: process.env.DATABASE_URL,
});
export async function withTenantTransaction<T>(
tenantId: string,
fn: (client: PoolClient) => Promise<T>
): Promise<T> {
const client = await pool.connect();
try {
await client.query('BEGIN');
// Scope this setting to the current transaction only
await client.query(
`SET LOCAL app.current_tenant_id = $1`,
[tenantId]
);
const result = await fn(client);
await client.query('COMMIT');
return result;
} catch (err) {
await client.query('ROLLBACK');
throw err;
} finally {
client.release();
}
}Updating the DAL to Use RLS Transactions
Now update the DAL functions to use withTenantTransaction. The application-level WHERE tenant_id = $1 filter is kept for clarity and performance (index utilisation), while RLS provides a safety net at the database level.
This defence-in-depth strategy means tenant leakage requires two independent failures simultaneously — significantly reducing risk.
// lib/dal/invoices.ts (updated)
import { withTenantTransaction } from '@/lib/db';
import type { TenantContext } from '@/lib/tenant';
import type { Invoice } from './types';
export async function listInvoices(
ctx: TenantContext,
page = 1,
pageSize = 20
): Promise<Invoice[]> {
const offset = (page - 1) * pageSize;
return withTenantTransaction(ctx.tenantId, async (client) => {
const result = await client.query<Invoice>(
`SELECT id, tenant_id AS "tenantId", amount, status, created_at AS "createdAt"
FROM invoices
WHERE tenant_id = $1
ORDER BY created_at DESC
LIMIT $2 OFFSET $3`,
[ctx.tenantId, pageSize, offset]
);
return result.rows;
});
}Schema-Per-Tenant Isolation with Prisma
For applications requiring stronger guarantees, a schema-per-tenant approach assigns each tenant their own PostgreSQL schema (e.g., tenant_abc.invoices). This eliminates cross-tenant leakage at the structural level — policies and filters are unnecessary because the data is physically separate.
With Prisma, you can achieve this by dynamically constructing a client that uses a different schema for each request:
// lib/tenant-db.ts
import { PrismaClient } from '@prisma/client';
const clientCache = new Map<string, PrismaClient>();
export function getTenantPrismaClient(tenantId: string): PrismaClient {
const safeSchema = tenantId.replace(/[^a-z0-9_]/gi, '_');
if (clientCache.has(safeSchema)) {
return clientCache.get(safeSchema)!;
}
const client = new PrismaClient({
datasources: {
db: {
url: `${process.env.DATABASE_URL}?schema=${safeSchema}`,
},
},
});
clientCache.set(safeSchema, client);
return client;
}
// Usage in a Server Action:
// const db = getTenantPrismaClient(ctx.tenantId);
// const invoices = await db.invoice.findMany();Preventing Insecure Direct Object Reference (IDOR)
Tenant isolation must extend beyond list queries. A common vulnerability called Insecure Direct Object Reference (IDOR) occurs when an attacker changes a resource ID in the URL or request body to access another tenant's record.
The getInvoiceById DAL function already handles this correctly by including AND tenant_id = $1. If the invoice belongs to a different tenant, the query returns zero rows — the same response as a genuinely missing record. This prevents existence leakage.
Always verify ownership via the tenant context, never by trusting that the client-supplied ID is one the current user is allowed to see.
'use server';
import { requireTenantContext } from '@/lib/tenant';
import { withTenantTransaction } from '@/lib/db';
export async function deleteInvoiceAction(invoiceId: string) {
const ctx = await requireTenantContext();
await withTenantTransaction(ctx.tenantId, async (client) => {
const result = await client.query(
`DELETE FROM invoices
WHERE id = $1 AND tenant_id = $2`,
[invoiceId, ctx.tenantId]
);
// If rowCount is 0 the invoice either doesn't exist
// or belongs to another tenant — treat both identically.
if ((result.rowCount ?? 0) === 0) {
throw new Error('Invoice not found');
}
});
}Testing Tenant Isolation
Tenant isolation logic must be covered by automated tests. The key scenarios to test are:
- Happy path: Tenant A can read their own data.
- Cross-tenant read: Tenant A cannot read Tenant B's records (returns null or empty array).
- Cross-tenant delete/write: Tenant A's mutation on Tenant B's ID silently does nothing (rowCount = 0).
Use a test database and real SQL to catch regressions that mocks would miss. The following shows a Vitest integration test pattern:
// tests/dal/invoices.test.ts
import { describe, it, expect, beforeAll } from 'vitest';
import { listInvoices, getInvoiceById } from '@/lib/dal/invoices';
import { seedTestData, cleanTestData } from '../helpers/db';
const tenantA = { tenantId: 'tenant-aaa', userId: 'user-1' };
const tenantB = { tenantId: 'tenant-bbb', userId: 'user-2' };
beforeAll(async () => {
await cleanTestData();
await seedTestData([
{ id: 'inv-1', tenantId: 'tenant-aaa', amount: 100, status: 'paid' },
{ id: 'inv-2', tenantId: 'tenant-bbb', amount: 200, status: 'pending' },
]);
});
describe('listInvoices', () => {
it('returns only the requesting tenant\'s invoices', async () => {
const invoices = await listInvoices(tenantA);
expect(invoices).toHaveLength(1);
expect(invoices[0].id).toBe('inv-1');
});
});
describe('getInvoiceById', () => {
it('returns null when the invoice belongs to a different tenant', async () => {
// Tenant A tries to fetch Tenant B's invoice
const invoice = await getInvoiceById(tenantA, 'inv-2');
expect(invoice).toBeNull();
});
});Knowledge Check: Tenant Isolation Strategy
Test your understanding of the key design decisions covered in this lesson.
Recap: Row-Level Tenant Data Isolation Patterns
This lesson established a layered approach to enforcing tenant boundaries in a Next.js 15 App Router application:
- Session-derived tenant context — always resolve
tenantIdfrom a server-verified JWT or session cookie, never from client-supplied input. - Scoped Data Access Layer (DAL) — require a
TenantContextparameter in every repository function and applyWHERE tenant_id = $1at the SQL level, making omission a compile-time or code-review error. - PostgreSQL Row-Level Security (RLS) — enable RLS as a database-enforced safety net using
SET LOCAL app.current_tenant_idinside transactions, so even a buggy query cannot leak data. - IDOR prevention — include the tenant check in all single-record lookups and mutations; return identical errors for not-found and cross-tenant access to avoid existence leakage.
- Schema-per-tenant — an alternative pattern using separate PostgreSQL schemas for stronger structural isolation, at the cost of operational complexity.
- Integration tests — validate cross-tenant isolation with real queries against a test database, covering both read and write scenarios.
Combining application-layer filtering, database-layer RLS, and typed function signatures creates a multi-layered defence that makes tenant leakage structurally difficult even as the codebase grows.
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Toutes les leçons de ce cours
- Résolution des locataires par sous-domaine et par chemin
- Modèles d’isolation des données des locataires au niveau des lignes
- Thèmes et indicateurs de fonctionnalité par locataire
- Mesure de l’utilisation et application des abonnements