Broken Authentication in Adonisjs with Cockroachdb

Broken Authentication in an Adonisjs application using Cockroachdb can occur when session management, token handling, or credential verification are implemented inconsistently between the framework and the database layer. Adonisjs relies on secure, framework-managed sessions or JWTs, but misconfiguration can expose authentication state to tampering or leakage. Cockroachdb, as a distributed SQL database, stores user credentials and session records; if queries are constructed without strict input validation or parameterized statements, attackers can exploit subtle inconsistencies between Adonisjs middleware and Cockroachdb behavior.

One common pattern is storing session identifiers or user roles directly in Cockroachdb tables with non-unique or predictable keys. If Adonisjs generates session IDs using a weak entropy source and stores them in a Cockroachdb column without proper constraints, an attacker can brute-force or guess valid session identifiers. Additionally, Adonisjs may deserialize user objects from Cockroachdb rows; if deserialization does not validate type integrity or origin, an attacker can inject malicious payloads that bypass intended access controls.

Another vector involves authentication bypass through improper handling of Cockroachdb connection parameters within Adonisjs environment configuration. If database credentials or connection strings are exposed via logs, error messages, or insecure endpoints, an attacker can harvest details needed to authenticate directly to Cockroachdb, circumventing Adonisjs middleware entirely. This is particularly relevant when Adonisjs uses multiple database connections and one Cockroachdb instance is inadvertently exposed to unauthenticated network paths.

Rate limiting and lockout mechanisms implemented in Adonisjs may not align with Cockroachdb transaction semantics. For example, an attacker can perform rapid authentication requests that trigger concurrent Cockroachdb writes, exhausting connection pools or triggering row-level lock contention that degrades service while leaving authentication state partially updated. This can lead to scenarios where a user appears authenticated in one region of the cluster but not in another, due to replication lag, allowing unauthorized access across inconsistent read replicas.

Finally, LLM/AI Security checks highlight risk when authentication logic or error messages are generated by AI-assisted code patterns without review. If prompts used to generate Adonisjs authentication code inadvertently expose system details or Cockroachdb schema structure, attackers can use that information to tailor injection or enumeration attacks. middleBrick’s LLM/AI Security testing actively probes for such leakage and unsafe consumption patterns in API endpoints that interface with authentication logic and Cockroachdb.

Remediation focuses on strict input validation, secure session handling, and safe database interactions within Adonisjs when interfacing with Cockroachdb. Always use parameterized queries to prevent SQL injection and ensure that authentication state is never derived from unvalidated client data.

Example: Secure user login using Adonisjs Lucid models with Cockroachdb, leveraging parameterized queries and hashed passwords:

import { schema } from '@ioc:Adonis/Core/Validator'
import User from 'App/Models/User'
import { hash } from '@ioc:Adonis/Extras/Hashing'

export const loginSchema = schema.create({
  email: schema.string({ trim: true, normalize: true }),
  password: schema.string.optional(),
})

export default class AuthController {
  public async login({ request, auth, response }) {
    const payload = await request.validate({ schema: loginSchema })
    const user = await User.query().where('email', payload.email).preload('roles').first()

    if (!user || !(await hash.verify(payload.password, user.password))) {
      return response.badRequest({ message: 'Invalid credentials' })
    }

    const token = await auth.generate(user)
    return response.ok({ token, userId: user.id })
  }
}

Ensure Cockroachdb tables use strongly typed columns and constraints. For example, define a users table with a UUID primary key and enforce uniqueness on email:

import BaseSchema from '@ioc:Adonis/Lucid/Schema'

export default class UsersSchema extends BaseSchema {
  protected tableName = 'users'

  public up() {
    this.schema.createTable(this.tableName, (table) => {
      table.uuid('id').primary()
      table.string('email', 255).notNullable().unique()
      table.string('password_hash', 128).notNullable()
      table.timestamps(true, true)
    })
  }

  public down() {
    this.schema.dropTable(this.tableName)
  }
}

For session management, prefer encrypted, signed cookies or server-side storage with short TTLs. When persisting sessions in Cockroachdb, use a dedicated table with foreign keys to users and indexed expiration timestamps:

import BaseSchema from '@ioc:Adonis/Lucid/Schema'

export default class SessionsSchema extends BaseSchema {
  protected tableName = 'sessions'

  public up() {
    this.schema.createTable(this.tableName, (table) => {
      table.string('id', 64).primary()
      table.uuid('user_id').notNullable().unsignedReferences('users.id')
      table.json('payload')
      table.timestamp('expires_at').index()
    })
  }

  public down() {
    this.schema.dropTable(this.tableName)
  }
}

Implement consistent rate limiting using Adonisjs middleware that tracks attempts per user identifier and aligns with Cockroachdb’s transactional isolation to avoid race conditions:

import { HttpContextContract } from '@ioc:Adonis/Core/HttpContext'
import RateLimiter from 'async-ratelimiter'

const limiter = new RateLimiter({
  db: new (require('cockroachdb-client'))({
    host: process.env.DB_HOST,
    port: process.env.DB_PORT,
    user: process.env.DB_USER,
    database: process.env.DB_NAME,
  }),
  max: 5,
  duration: 60000,
})

export default class RateLimitMiddleware {
  public async handle(ctx: HttpContextContract, next: () => Promise) {
    const key = ctx.request.ip()
    const remaining = await limiter.get({ key })
    if (remaining === 0) {
      ctx.response.status(429).send({ error: 'Too many requests' })
      return
    }
    await limiter.hit({ key })
    await next()
  }
}

Finally, integrate middleBrick scans to validate that authentication endpoints and Cockroachdb interactions do not expose system details or accept unsafe consumption patterns. The CLI tool allows quick validation from the terminal: middlebrick scan <url>, while the GitHub Action can enforce security thresholds in CI/CD pipelines. For AI-assisted development, the MCP Server enables scanning directly from IDEs to catch risky patterns before deployment.