Broken Access Control in Phoenix with Mongodb

Broken Access Control occurs when authorization checks are missing or incorrectly enforced, allowing a user to access resources or perform actions they should not be able to. In a Phoenix application using Mongodb as the primary datastore, the risk arises from a mismatch between how access control is expressed in Elixir code and how data is stored and queried in Mongodb.

Phoenix does not enforce data-level permissions by default. If controllers or context modules query the database without scoping queries to the current user, an authenticated attacker may manipulate request parameters (such as changing an :id in a URL) to access or modify other users' records. This is a classic Broken Object Level Authorization (BOLA) / Insecure Direct Object Reference (IDOR) pattern.

Mongodb's flexible schema and rich query language can inadvertently enable these issues when developers construct queries by naively inserting user-supplied IDs without validating ownership. For example, a query like [%{user_id: user_id} | _] = Posts.find(%{_id: post_id}) may appear safe, but if user_id is not verified against the authenticated subject or if the query uses a string-based _id without ensuring it belongs to the requesting user, the document can be retrieved regardless of ownership. Additionally, projection issues—returning more fields than necessary—can expose sensitive fields such as roles, permissions, or internal references.

Another contributing factor is the use of dynamic pipeline stages built from user input, where an attacker might attempt to inject conditions that bypass intended filters. While Mongodb itself is not at fault, the way pipelines are assembled in Phoenix code can create paths that skip authorization. For instance, merging user-provided filters into an aggregation pipeline without strict allow-listing can change the result set in ways the developer did not anticipate.

Broken access control in this stack also intersects with data exposure and insecure consumption. If API endpoints return full Mongodb documents—including internal fields like __v, hashed passwords, or role arrays—without careful projection, clients may learn sensitive information. Similarly, if input validation is weak, an attacker might supply crafted ObjectId-like strings that trigger server-side errors or information leakage through verbose stack traces, aiding further exploitation.

Because middleBrick scans the unauthenticated attack surface and includes specific checks for BOLA/IDOR and Property Authorization, it can highlight mismatches between documented behavior and runtime exposure in endpoints that use Mongodb backends. The scanner does not rely on internal architecture, but its ability to correlate OpenAPI definitions with runtime responses helps surface findings where access control appears missing or inconsistent.

Remediation focuses on ensuring every data access is scoped to the requesting user and that responses expose only necessary fields. Below are concrete patterns and code examples tailored for Phoenix with Mongodb.

1. Scope all queries by authenticated subject

Always include the user identifier in your query filter. Do not rely on route parameters alone.

def get_user_post(user_id, post_id) do
  case Posts.find_one(%{
    "user_id" => user_id,
    "_id" => post_id
  }) do
    nil -> {:error, :not_found}
    post -> {:ok, post}
  end
end

2. Use allow-lists for projections

Explicitly return only the fields you need to avoid leaking sensitive data stored in the same document.

Posts.find_one(%{"user_id" => user_id, "_id" => post_id},
  projection: %{"title" => 1, "body" => 1, "_id" => 1, "user_id" => 1}
)

3. Validate identifiers before querying

Ensure identifiers are in the expected format and map to the current tenant or user context before using them in a Mongodb query.

def safe_find_post(%{"id" => id, "user_id" => user_id}) when is_binary(id) and is_binary(user_id) do
  with {:ok, _} <- Ecto.UUID.cast(id), do:
    get_user_post(user_id, id)
end

4. Avoid merging raw user input into pipeline stages

Build pipelines with static structure; only allow controlled parameters that you have validated and transformed.

pipeline = [
  %{"$match" => %{"user_id" => user_id}},
  %{"$project" => %{"name" => 1, "value" => 1}}
]
# Do NOT append user-provided stages directly
result = Posts.aggregate(pipeline)

5. Use consistent data models and avoid overprivileged roles

Keep role information out of documents returned to clients and enforce roles server-side in your context modules rather than trusting document metadata.

def can_edit?(user, post) do
  user.role in ["admin", "editor"] and post.user_id == user.id
end

By combining strict scoping, projection control, input validation, and disciplined pipeline construction, you reduce the attack surface introduced by the flexibility of Mongodb. middleBrick can then verify that these controls are reflected in the runtime behavior of your endpoints.