Format String in Feathersjs with Basic Auth

A format string vulnerability occurs when user-controlled input is passed directly into a function that interprets format specifiers such as %s, %n, or %p without proper sanitization. In FeathersJS, services often receive data from requests, including headers and query parameters. When Basic Auth is used, the Authorization header is parsed to extract a base64-encoded username:password string. If the application decodes this value and uses it in logging, error messages, or dynamic string construction using functions like console.log or custom formatters, attacker-controlled format specifiers can lead to information disclosure or memory corruption.

Consider a Feathers service that logs authenticated user details. If the decoded username from Basic Auth is used directly in a format string, an attacker can supply values like %s %s %s to read stack memory or cause crashes:

// Risky: using user input directly in a format string
const authHeader = req.headers.authorization; // 'Basic dGVzdDp0ZXN0'
const decoded = Buffer.from(authHeader.split(' ')[1], 'base64').toString(); // 'test:test'
const [username] = decoded.split(':');
console.log(`User: %s`, username); // If username contains format specifiers, behavior is undefined

In this scenario, the combination of FeathersJS service hooks and Basic Auth creates a path for injection. The framework does not inherently sanitize inputs from authentication headers. If the developer uses string formatting utilities (or even template literals with indirect user input), they must treat the decoded Basic Auth username as untrusted. Attackers may also exploit this in error handling paths where stack traces or debug messages are emitted, potentially leaking memory contents or application internals. Because Basic Auth transmits credentials in each request, repeated exploitation can increase exposure. The vulnerability is not in Basic Auth itself but in how the application handles decoded values before formatting output.

Additionally, log injection can occur if usernames are embedded in log lines without sanitization, making it difficult to distinguish log entries during incident analysis. FeathersJS hooks that modify connection data or add metadata must ensure that any user-derived fields are escaped or validated before being used in logging or diagnostic routines. This is especially important when integrating with monitoring tools that parse structured logs.

Remediation focuses on avoiding direct use of decoded Basic Auth values in format strings and ensuring safe handling of credentials. Always treat data from req.headers.authorization as untrusted. Instead of decoding and directly interpolating values, use robust parsing libraries and validation, and avoid printf-style formatting with user input.

Below is a secure pattern for extracting and using Basic Auth credentials in a FeathersJS service hook:

// Safe: validate and sanitize before any formatting
const authHeader = req.headers.authorization;
if (authHeader && authHeader.startsWith('Basic ')) {
  const base64 = authHeader.split(' ')[1];
  const decoded = Buffer.from(base64, 'base64').toString('utf8');
  const [username, password] = decoded.split(':');
  // Validate format (e.g., alphanumeric only)
  if (!/^[a-zA-Z0-9_]{3,32}$/.test(username)) {
    throw new Error('Invalid username');
  }
  // Use username for business logic, not formatting
  req.username = username;
} else {
  throw new Error('Missing authorization header');
}

For logging, use structured logging with placeholders instead of format specifiers:

// Safe logging: avoid format strings with user input
const logger = require('./logger');
logger.info('Authentication attempt', { username: req.username });

In service hooks, ensure that any error messages do not echo user input directly. Use constant-time comparison for credentials if you perform manual checks, and prefer established authentication providers or OAuth where possible. The middleBrick CLI can be used to scan your Feathers endpoints and detect insecure handling of authentication headers:

middlebrick scan https://api.example.com/openapi.json

For teams needing continuous oversight, the middleBrick Pro plan provides ongoing monitoring and integrates with CI/CD pipelines via the GitHub Action to fail builds if security thresholds are not met. The MCP Server allows you to run scans directly from AI coding assistants within your development environment.