Excessive Data Exposure in Chi with Dynamodb

Excessive Data Exposure occurs when an API returns more data than necessary for a given operation, and this risk is amplified in Chi applications that rely on Amazon DynamoDB as a backend. In Chi, developers often map HTTP endpoints directly to DynamoDB table operations without implementing fine-grained field-level filtering. Because DynamoDB stores semi-structured items that can contain many attributes, a single query that retrieves an item by primary key may return sensitive fields such as internal identifiers, email addresses, role flags, or payment metadata if the response is not explicitly limited.

When a Chi route performs a get or query on a DynamoDB table and serializes the raw DynamoDB record into JSON, the API can inadvertently expose attributes that were intended for server-side use only. For example, a user profile endpoint that fetches an item by user_id may return password_hash, refresh_token, or is_admin because the DynamoDB table stores these fields and the Chi handler does not prune them. This becomes a significant confidentiality issue when the API serves untrusted clients such as web or mobile frontends.

Additionally, DynamoDB’s schema-less design encourages storing nested and metadata-rich items, including system attributes like __created_at or __last_modified. If the Chi application does not apply a strict projection or transformation layer, these metadata fields can leak through API responses. Attackers can chain Excessive Data Exposure with other weaknesses such as BOLA/IDOR to escalate impact by harvesting sensitive attributes that facilitate further unauthorized access.

The combination of Chi’s routing style and DynamoDB’s flexible data model means that developers must consciously define which fields are safe to return. Without output filtering, any attribute present in the DynamoDB item can be exposed. This is especially critical for compliance frameworks such as OWASP API Top 10 (2023) A5:2023 – Security Misconfiguration and GDPR data minimization principles, where unnecessary data exposure constitutes a non-compliant data processing practice.

middleBrick detects this pattern during black-box scanning by observing API responses that contain unexpected or sensitive fields and mapping them against known sensitive keywords. The scanner does not assume intent; it highlights items where fields like password, token, or role appear in API output without explicit justification, providing remediation guidance to apply field-level filtering in Chi handlers.

To remediate Excessive Data Exposure in Chi with DynamoDB, you should enforce strict field selection and avoid returning raw DynamoDB items. Use Chi’s route handlers to transform DynamoDB responses into lean data transfer objects (DTOs) that contain only the fields required by the client.

First, define a DTO type that represents the safe subset of data. Then, map the DynamoDB item to this DTO in your handler. Below is a concrete Chi example in Nim that demonstrates this pattern using the dynogels library (note: the example is illustrative; adapt to your actual DynamoDB client):

import chi
import json_serialization
import dynogels

type
  UserProfileDTO = object
    userId: string
    email: string
    name: string
    avatarUrl: string

proc userProfileHandler(req: Request, res: Response) =
  let userId = req.pathParams["userId"]
  # Assume `User` is a DynamoDB mapped model with many fields
  let maybeUser = User.get(userId)
  if maybeUser.isNone:
    res.status_code = 404
    res.write("not found")
    return

  let user = maybeUser.get
  # Explicitly construct a DTO to avoid exposing sensitive fields
  let dto = UserProfileDTO(
    userId: user.id,
    email: user.email,
    name: user.fullName,
    avatarUrl: user.avatar
  )
  res.json = dto

Second, if you must return a subset of attributes dynamically, use DynamoDB’s ProjectionExpression or ExpressionAttributeNames to limit the fields fetched from the table. This reduces both network overhead and exposure surface. For example, using the AWS SDK for JavaScript within a Chi backend (via a Node.js bridge) would look like:

const { DynamoDB } = require("aws-sdk");
const dynamo = new DynamoDB.DocumentClient();

async function getUserPublicFields(userId) {
  const params = {
    TableName: "Users",
    Key: { userId },
    ProjectionExpression: "userId, email, name, avatarUrl"
  };
  const data = await dynamo.get(params).promise();
  return data.Item;
}

Third, avoid using DynamoDB Scan operations in Chi handlers unless absolutely necessary, as scans can return many items with diverse attributes. If you must scan, apply a FilterExpression and select only required attributes via Select to minimize data exposure. Combine this with Chi’s middleware to enforce that no handler performs unrestricted scans without explicit justification.

Finally, validate that your Chi application does not serialize DynamoDB’s internal metadata such as __type or ApproximateNumberOfDecodableValues. Use serialization annotations or custom toJson methods to ensure only intended fields appear in HTTP responses. middleBrick’s continuous monitoring in the Pro plan can alert you if new sensitive fields appear in API outputs over time, helping you maintain a low exposure posture as your data model evolves.