Regex Dos in Fiber with Jwt Tokens

A Regular Expression Denial of Service (Regex DoS) occurs when an untrusted input is matched against a regular expression that can exhibit catastrophic backtracking. In Fiber, a popular high-performance web framework for Go, this risk is present when route path parameters or custom middleware apply complex regex patterns to validate or extract data such as JWT tokens. JWT tokens are typically Base64Url-encoded strings containing structured claims, and while they are often passed in the Authorization header as a bearer token, developers sometimes use regex-based validation directly on path segments or query parameters that could echo or parse the token.

When a Fiber route uses a permissive or overly complex regex to capture a supposed JWT from the URL path, an attacker can supply crafted input that causes exponential backtracking. For example, a route like /api/:token([a-zA-Z0-9_\-\.]+) may appear safe, but if the regex is modified to include optional groups or nested quantifiers (e.g., ^(?:[a-zA-Z0-9_\-\.]*)*$) to accommodate variations, an attacker can send a long string of characters that matches the pattern superficially but causes the engine to explore an enormous number of paths. Because JWT tokens often contain dots and alphanumeric segments that can satisfy character classes, a malicious token can trigger repeated partial matches, consuming CPU heavily and leading to service slowdown or unresponsiveness within the 5–15 second scan window that middleBrick uses for black-box testing.

Moreover, because middleBrick scans the unauthenticated attack surface and runs 12 security checks in parallel including Input Validation and Rate Limiting, it can detect signs of inefficient regex usage that may lead to denial of service. If a JWT is expected in the Authorization header but the application also exposes a route with a vulnerable regex on a public endpoint, the risk surface expands. An attacker does not need valid credentials; they simply send malformed or long tokens in the path or parameters to probe for excessive CPU consumption. The scanner’s Input Validation checks can flag patterns known to be problematic, while the Rate Limiting check can highlight endpoints that do not adequately throttle requests, both of which are relevant when JWT tokens are handled with fragile regex logic.

SSRF and other checks performed by middleBrick do not directly test for Regex DoS, but the scanner’s cross-referencing of OpenAPI specs with runtime findings can reveal endpoints where regex-based validation is used in unexpected ways, such as in path templates that include token-like parameters. This helps identify where JWT handling logic might intersect with routing in a way that invites backtracking attacks. Since JWTs are frequently used for authentication, ensuring that their parsing and validation do not rely on vulnerable regex patterns is essential for maintaining availability and performance.

To mitigate Regex DoS when handling JWT tokens in Fiber, avoid using complex or nested quantifiers in route parameter patterns. Instead, rely on simple, linear character class patterns and perform token validation outside the routing layer, ideally using a dedicated JWT parsing library. For example, define a route that captures a token with a straightforward pattern and then validate and parse it in a handler or middleware.

// Example: Safe JWT handling in Fiber without risky regex routing
const fcie = require('fiber');
const { parse } = require('jsonwebtoken'); // or a similar JWT library

const app = fcie();

// Use a simple pattern to capture token-like strings without complex regex
app.get('/api/resource/:token', (req, res) => {
  const token = req.params.token;
  // Basic sanity checks before passing to JWT library
  if (!token || typeof token !== 'string' || token.split('.').length !== 3) {
    return res.status(400).send({ error: 'Invalid token format' });
  }
  try {
    // Validate and decode using a robust JWT library
    const decoded = parse(token, process.env.JWT_SECRET, { algorithms: ['HS256'] });
    res.json({ message: 'Authorized', user: decoded.sub });
  } catch (err) {
    res.status(401).send({ error: 'Invalid or expired token' });
  }
});

app.listen(3000, () => console.log('Server running on port 3000'));

If you must use regex in route definitions, keep it minimal and avoid optional groups or repetition that can cause backtracking. For instance, a pattern like [a-zA-Z0-9_\-\.]{20,} is safer than patterns with nested quantifiers. Prefer length checks and character whitelisting, and reject tokens that contain unexpected structures before they reach regex matching.

// Minimal regex usage example, avoiding dangerous constructs
app.get('/api/token/:token([a-zA-Z0-9_\-\.]{20,})', (req, res) => {
  // Proceed with JWT library validation
});

Additionally, enforce rate limiting at the Fiber level to reduce the impact of abusive requests targeting regex endpoints. MiddleBrick’s Pro plan can integrate with GitHub Actions to enforce CI/CD pipeline gates based on security scores, ensuring that any changes to routing or validation logic do not introduce new Regex DoS risks. Continuous monitoring helps catch regressions early, especially when JWT handling logic evolves over time.