Xss Cross Site Scripting in Fiber with Dynamodb

Cross-site scripting (XSS) in a Fiber application that uses DynamoDB typically arises when user-controlled data is rendered in HTML, XML, or JSON responses without proper encoding or validation. If your API stores or returns data that includes untrusted input—such as a user-supplied displayName or comment—and that data is later embedded in a UI without escaping, an attacker can inject executable scripts. In a DynamoDB context, this often means trusting data that was written as a string attribute and then returned by getItem, query, or scan operations and sent directly to the client.

In a black-box scan, middleBrick checks for XSS by observing whether reflected or stored data is present in dangerous contexts in responses (for example, inside <script>, event handlers, or unescaped JSON in HTML). For DynamoDB, middleBrick does not assume how you use the data; it flags endpoints where response fields match known injection/scripting patterns and highlights a lack of encoding or Content-Type mismatches. The risk is elevated when the same DynamoDB item is used both as a data store and as a partial template for HTML fragments, or when a JSON API response is consumed by a client framework that performs unsafe innerHTML assignments.

Consider a route that fetches an item by ID and returns it as JSON that a browser then renders unsafely:

// Unsafe: returning DynamoDB item directly and rendering with innerHTML in the browser
app.get('/user/:id', async (req, res) => {
  const { id } = req.params;
  const params = {
    TableName: 'users',
    Key: { userId: id }
  };
  const result = await dynamodb.get(params).promise();
  const item = result.Item;
  // If item.displayName contains <script>, the client executes it
  res.json({ displayName: item.displayName });
});

An attacker could store a malicious displayName such as <script>stealCookies()</script> in DynamoDB; when the client renders displayName via innerHTML, the script executes. middleBrick’s checks for XSS include inspecting response fields for reflected HTML/script context and verifying that frameworks enforce safe rendering practices. In a full OpenAPI/Swagger analysis with $ref resolution, middleBrick compares the declared response schemas with runtime payloads to detect mismatches where user-controlled string attributes appear in HTML-like contexts.

Beyond direct script injection, XSS with DynamoDB can stem from stored data used in other outputs such as URLs or JSON Web Tokens. For example, if a user-supplied value is placed into a redirect location or concatenated into a JavaScript snippet without escaping, attackers can achieve reflected XSS or data exfiltration via script sources. middleBrick’s input validation checks flag missing sanitization for string inputs that eventually reach client-facing outputs, encouraging strict allow-lists for fields like usernames or search terms and context-aware escaping when those values are serialized.

When scanning with middleBrick, you receive per-category breakdowns that map findings to frameworks such as OWASP API Top 10 and highlight the exact response paths and severity. This helps you prioritize fixing the storage-to-output chain: validate and encode on input, enforce strict content types, and apply context-specific escaping on the client. Remember that middleBrick detects and reports—it does not modify data or block requests. Use its remediation guidance to adjust validation rules, apply output encoding, and review client-side rendering logic.

Remediation focuses on ensuring that data from DynamoDB is never treated as trusted HTML, URL, or script context. On the server side in Fiber, you should treat all DynamoDB string attributes as opaque and encode them for the target context before sending them to the client. For JSON APIs, ensure that Content-Type is application/json and avoid embedding user data directly into HTML or inline event handlers. On the client side, use safe rendering APIs and avoid innerHTML for user-controlled strings.

One concrete approach is to validate and sanitize inputs when writing to DynamoDB and to encode outputs based on consumption context. For example, when storing user input, apply a strict allow-list and normalization:

import { DynamoDB } from 'aws-sdk';
import validator from 'validator';

const dynamodb = new DynamoDB.DocumentClient();

async function saveUserProfile(userId: string, rawDisplayName: string) {
  // Strict allow-list: only letters, numbers, space, hyphen, underscore
  if (!validator.matches(rawDisplayName, /^[A-Za-z0-9 _-]+$/)) {
    throw new Error('Invalid display name');
  }
  const params = {
    TableName: 'users',
    Item: {
      userId,
      displayName: rawDisplayName.trim()
    }
  };
  await dynamodb.put(params).promise();
}

When reading from DynamoDB and sending data to clients, encode for the appropriate context. For JSON responses, ensure strings are properly serialized by JSON.stringify and that you do not embed them into HTML. For HTML templates (if you render server-side), use an HTML-escaping function:

import escapeHtml from 'escape-html';

app.get('/user/:id', async (req, res) => {
  const params = {
    TableName: 'users',
    Key: { userId: req.params.id }
  };
  const result = await dynamodb.get(params).promise();
  const item = result.Item;
  // Safe: escape for HTML context if embedding in templates
  const safeDisplayName = escapeHtml(String(item.displayName || ''));
  // If sending JSON to a frontend, keep as plain string and let the frontend encode
  res.json({ displayName: item.displayName });
});

In client-side JavaScript, prefer textContent over innerHTML when displaying user data:

// Unsafe:
element.innerHTML = apiResponse.displayName;

// Safe:
element.textContent = apiResponse.displayName;

middleBrick’s scans will highlight where responses contain unescaped strings in HTML contexts and where OpenAPI specs do not enforce safe encoding practices. By combining server-side validation, context-aware encoding, and safe client-side rendering, you reduce the risk of XSS while preserving the utility of DynamoDB-stored data. The Pro plan’s continuous monitoring can help you detect regressions if future changes introduce unsafe patterns, and the GitHub Action can gate merges when risk scores drop below your chosen threshold.