Identification Failures in Adonisjs with Mongodb

Identification failures occur when an API fails to ensure that a subject (for example, a user or service) is correctly and reliably identified before performing authorization checks. In the AdonisJS ecosystem, developers typically rely on the built-in authentication layer to set the current user, while data access often uses MongoDB drivers or ODMs such as Mongoose-like libraries. When identification is weak or bypassed, an attacker can manipulate identifiers in requests to reference other users’ resources, leading to direct object-level access.

With MongoDB, identification failures are commonly tied to how identifiers are passed into queries. If an endpoint accepts a user-supplied id or _id and directly interpolates it into a MongoDB filter without validating that the authenticated subject owns that identifier, the endpoint exposes a BOLA/IDOR surface. For example, an endpoint like /users/:id/profile may fetch a document using { _id: req.params.id } while relying solely on route parameters instead of tying the query to the authenticated user’s ID. Because MongoDB queries are highly flexible, an attacker can also supply nested or polymorphic identifiers, or even attempt NoSQL injection patterns if input validation is weak, escalating the impact of identification gaps.

AdonisJS projects often integrate MongoDB through custom providers or third-party packages that implement document modeling. If these integrations do not enforce a binding between the authenticated entity and the queried entity, the unauthenticated or low-privilege context can read or modify records that should be restricted. This becomes especially dangerous when identifiers are predictable (e.g., sequential ObjectIds), as attackers can iterate through values and enumerate valid resources. Compounded with missing rate controls, such endpoints can be probed at scale. The OpenAPI/Swagger analysis integrated in middleBrick highlights these risks by cross-referencing spec definitions with runtime behavior, ensuring that authentication and ownership checks are explicitly modeled and tested.

Furthermore, identification failures are not limited to simple string IDs. In AdonisJS, session-based or token-based identity may be represented by complex objects, and MongoDB documents may reference users via ObjectIds or composite keys. If middleware resolves the user but later queries do not explicitly include the user’s identifier in the filter, the system defaults to an unsafe state where data exposure can occur across tenants. middleBrick’s 12 security checks run in parallel to detect such mismatches, including Authentication, BOLA/IDOR, and Property Authorization, providing prioritized findings with severity and remediation guidance to tighten the identity-to-query chain.

To mitigate identification failures, AdonisJS applications using MongoDB must bind every data access to the authenticated subject. This requires validating and merging the authenticated identity into the query filter rather than relying solely on route parameters. Below are concrete, working examples using the native MongoDB driver in an AdonisJS controller.

// app/Controllers/Http/ProfileController.ts
import { HttpContextContract } from '@ioc:Adonis/Core/HttpContext'
import { Db, ObjectId } from 'mongodb'

export default class ProfileController {
  constructor(private db: Db) {}

  public async show(ctx: HttpContextContract) {
    const userId = ctx.auth.user?.id
    const requestedId = ctx.request.param('id')

    // Ensure authenticated user exists
    if (!userId) {
      ctx.response.unauthorized('Authentication required')
      return
    }

    // Validate requestedId is a valid ObjectId
    let objectId: ObjectId
    try {
      objectId = new ObjectId(requestedId)
    } catch {
      ctx.response.badRequest('Invalid identifier')
      return
    }

    // Bind query to authenticated user to prevent IDOR
    const profile = await this.db.collection('profiles').findOne({
      _id: objectId,
      userId: userId, // explicit ownership check
    })

    if (!profile) {
      ctx.response.notFound('Profile not found or access denied')
      return
    }

    ctx.response.send(profile)
  }

  public async update(ctx: HttpContextContract) {
    const userId = ctx.auth.user?.id
    const requestedId = ctx.request.param('id')
    const body = ctx.request.only(['displayName', 'email'])

    if (!userId) {
      ctx.response.unauthorized('Authentication required')
      return
    }

    let objectId: ObjectId
    try {
      objectId = new ObjectId(requestedId)
    } catch {
      ctx.response.badRequest('Invalid identifier')
      return
    }

    const result = await this.db.collection('profiles').updateOne(
      {
        _id: objectId,
        userId: userId,
      },
      {
        $set: {
          displayName: body.displayName,
          email: body.email,
          updatedAt: new Date(),
        },
      }
    )

    if (result.matchedCount === 0) {
      ctx.response.notFound('Unable to update: not found or access denied')
      return
    }

    ctx.response.ok({ message: 'Updated successfully' })
  }
}

These examples demonstrate how to explicitly include the authenticated user’s identifier in the MongoDB filter, ensuring that operations are scoped to the owner. Always validate and cast identifiers to the expected type (e.g., ObjectId) to avoid injection or type confusion. middleBrick’s CLI can be used to scan endpoints like these and surface BOLA/IDOR findings, while the GitHub Action can enforce that new changes do not introduce regression by failing builds when risk thresholds are exceeded.

Additionally, apply strict input validation and avoid exposing raw MongoDB errors to clients, as error messages may leak identifiers or schema details. Use middleware to normalize authentication so that controllers consistently resolve ctx.auth.user. The MCP Server allows you to run scans directly from AI coding assistants, catching identification issues early as you write queries. For long-term protection, the Pro plan’s continuous monitoring and configurable schedules help detect drift in endpoint behavior across releases.