Auth Bypass in Chi with Dynamodb

Chi is a lightweight, idiomatic routing library for the Crystal programming language. When Chi routes call DynamoDB as the persistence layer, a misconfiguration in how identity and authorization are enforced can lead to an authentication bypass. This typically occurs when route-level authorization logic is omitted or incorrectly mapped to DynamoDB identity attributes, allowing an attacker to access or modify resources by manipulating identifiers or tokens.

In a typical Crystal service using Chi and the official AWS SDK for DynamoDB, developers may rely on external authentication (e.g., JWT verification) but fail to enforce ownership checks at the DynamoDB query level. For example, a route like /users/:id/profile might verify a JWT to extract a user ID, then directly use that ID in a DynamoDB GetItem or Query without confirming the authenticated subject matches the item’s partition key. If the route handler uses a raw ID from the request (e.g., params.get("id", "string")) instead of the subject derived from the authenticated session, an attacker can change the ID to another user’s ID and read or alter data.

DynamoDB itself does not enforce application-level permissions; it enforces only fine-grained IAM policies at the AWS account/role level. If the service’s IAM role is broad (for example, allowing dynamodb:GetItem and dynamodb:Query on the table without conditionals), and the application does not scope queries to the authenticated subject, the combination creates an authorization bypass. An authenticated user can iterate over other partition key values, effectively bypassing intended access controls. This is an Auth Bypass (BOLA/IDOR) pattern: Insecure Direct Object Reference at the DynamoDB query layer.

Another vector involves unauthenticated LLM endpoints exposed alongside Chi routes. If a Chi route dispatches to an endpoint that calls an LLM without validating the session, and DynamoDB is used to store or retrieve prompts or user data without ownership checks, an attacker can exploit the LLM endpoint to indirectly access or infer data belonging to other users. middleBrick’s LLM security checks detect unauthenticated LLM endpoints and system prompt leakage, which can complement manual reviews of Chi routes that integrate AI features.

Using OpenAPI spec analysis, middleBrick cross-references spec definitions with runtime behavior to highlight missing authentication requirements on endpoints that interact with DynamoDB. This is valuable because a missing security scheme on a route that performs DynamoDB operations can indicate an oversight in enforcing identity checks. Developers should ensure each Chi route that accesses DynamoDB either enforces authentication at the router level or applies subject-based filters in every DynamoDB request.

Remediation focuses on ensuring that every DynamoDB operation is scoped to the authenticated subject and that Chi routes enforce authentication consistently. Below are concrete code examples in Crystal using the AWS SDK for DynamoDB and Chi routing.

1. Enforce authentication at the Chi route level

Use Chi’s middleware to require authentication before entering protected routes. Extract the subject from the session or JWT and pass it to downstream handlers.

require "jwt"
require "chi"

router = Chi::Router.new do
  # Public routes
  get "/public/health" do |env|
    { status: 200, body: { ok: true }.to_json }.tap { |h| h["Content-Type"] = "application/json" }
  end

  # Protected routes: require a valid JWT with subject (sub)
  before do |env|
    token = env.request.headers["Authorization"]?.try &.delete_prefix("Bearer ")
    unless token?
      env.response.status_code = 401
      return { error: "unauthorized" }.to_json
    end

    begin
      decoded = JWT.decode(token, ENV["JWT_SECRET"], true, { algorithm: "HS256" }).first
      env["current_user"] = decoded["sub"]
    rescue
      env.response.status_code = 401
      return { error: "invalid_token" }.to_json
    end
  end

  # Protected example
  get "/users/:id/profile" do |env|
    user_id = env.url_params["id"]? || env["current_user"]?
    if user_id != env["current_user"]?
      env.response.status_code = 403
      return { error: "forbidden" }.to_json
    end
    # handler continues with DynamoDB call scoped to current_user
  end
end

2. Scope DynamoDB queries to the authenticated subject

Always use the authenticated subject (e.g., env["current_user"]) as the partition key value in DynamoDB requests. Avoid using request-provided IDs directly unless they have been validated to match the subject.

require "aws-sdk-dynamodb"

class UserRepository
  def initialize(@table_name : String, @dynamodb_client : Aws::DynamoDB::Client)
  end

  def get_profile(user_id : String)
    resp = @dynamodb_client.get_item({
      table_name: @table_name,
      key: {
        "pk" => { s: "USER##{user_id}" },
        "sk" => { s: "PROFILE" },
      },
    })
    item = resp.item
    item ? from_ddb(item) : nil
  end

  def get_own_profile(current_user_id : String, requested_id : String)
    # Ensure the requested_id matches the current_user_id to prevent IDOR
    unless current_user_id == requested_id
      raise "Forbidden: cannot access another user’s profile"
    end
    get_profile(requested_id)
  end

  private def from_ddb(item : Hash(String, Aws::DynamoDB::Types::AttributeValue))
    { id: item["pk"]?.as_s.split("##")[-1], name: item["name"]?.as_s }
  end
end

3. Avoid broad IAM roles; use condition keys in DynamoDB requests when possible

While IAM policies are managed outside the application, you can further reduce risk by scoping requests with explicit key conditions and avoiding wildcard permissions in your service role. In code, prefer queries that include the subject in the key expression rather than scanning the entire table.

# Good: query scoped to user partition
resp = dynamodb_client.query({
  table_name: "app_table",
  key_condition_expression: "pk = :p",
  expression_attribute_values: {
    ":p" => { s: "USER##{current_user_id}" },
  },
})

# Avoid: scan or query without key condition on pk
# resp = dynamodb_client.scan(table_name: "app_table")

4. Validate and normalize identifiers

Ensure that IDs used in DynamoDB keys are normalized (e.g., prefix with entity type) and validated to prevent injection or malformed key errors. This complements application-level authorization and prevents path traversal or key confusion issues.

def normalize_user_key(user_id : String) : String
  # Reject unexpected characters
  unless user_id =~ /^[-a-zA-Z0-9_]+$/
    raise "Invalid user_id"
  end
  "USER##{user_id}"
end