Stack Overflow in Fiber with Jwt Tokens

When building HTTP services with the Fiber web framework, developers commonly use JWT tokens for authentication. If token validation is implemented inconsistently—for example, by skipping verification for selected routes or by trusting the raw Authorization header without re-checking signature and claims—an attacker can exploit trust boundaries to trigger a Stack Overflow. This often occurs when a crafted JWT with a deeply nested payload or a maliciously large claims set is accepted by the application before being passed to downstream handlers, parsers, or middleware that recursively traverse the claims.

In a black-box scan using middleBrick, the tool submits a URL and runs unauthenticated checks including Input Validation and Unsafe Consumption. When JWT tokens are involved, middleBrick tests whether the API accepts oversized or malformed tokens and whether validation logic is applied uniformly. A Stack Overflow may be triggered by sending a JWT with an extremely nested payload or by chaining routes where authentication is intermittently bypassed. Because the scan does not require credentials, it can surface this class of issue in the unauthenticated attack surface, surfacing findings such as high input complexity causing excessive memory or CPU use during token parsing.

Consider an endpoint that decodes a JWT but does not enforce strict claims checks or size limits on the payload. An attacker could supply a token with a deeply nested JSON structure in the payload or in a custom claim, and if the application recursively processes that claim (for example, walking roles or permissions), it may consume excessive stack space. middleBrick’s Input Validation and Unsafe Consumption checks help detect conditions that can lead to resource exhaustion, while the system prompt and output scanning for LLM-related endpoints would identify whether any AI-facing endpoints similarly mishandle JWT-derived data.

Because middleBrick also inspects OpenAPI/Swagger specs with full $ref resolution and cross-references definitions with runtime behavior, it can highlight mismatches—for instance, a documented security scheme that is not enforced on all routes. This is relevant when JWT-based security is defined in the spec but omitted on one or more endpoints, creating a path where an attacker can interact with less-protected routes and indirectly stress components that process JWT claims.

In practice, to observe the issue, you can send a request with an abnormally large or deeply nested JWT to a Fiber route that decodes but does not validate or limit claim depth. The stack may overflow during recursive traversal of claims, leading to crashes or denial of service. middleBrick flags such conditions under its prioritized findings, providing severity and remediation guidance without attempting to fix the service.

To mitigate Stack Overflow risks when using JWT tokens in Fiber, enforce strict validation, limit payload size, and avoid recursive processing of claims. Below are concrete, realistic code examples using the middleBrick-compatible approach of checking behavior without relying on internal engine details.

1. Validate every token and do not trust the raw header

Always verify the token signature and validate standard claims before using any payload. In Fiber, use the jwt package to parse and verify rather than manually decoding the header and payload.

const jwt = require('jsonwebtoken');
const express = require('express');
const app = express();

const PUBLIC_KEY = `-----BEGIN PUBLIC KEY-----
MIIBIjANBgkqhkiG9w0BAQEFAAOCAQ8AMIIBCgKCAQEAwIDAQAB
...
-----END PUBLIC KEY-----`;

app.get('/profile', (req, res) => {
  const authHeader = req.headers.authorization;
  if (!authHeader || !authHeader.startsWith('Bearer ')) {
    return res.status(401).json({ error: 'authorization header required' });
  }
  const token = authHeader.split(' ')[1];
  try {
    const decoded = jwt.verify(token, PUBLIC_KEY, { algorithms: ['RS256'] });
    // Use decoded claims safely, with no recursive traversal
    res.json({ user: decoded.sub, roles: decoded.roles || [] });
  } catch (err) {
    return res.status(401).json({ error: 'invalid token' });
  }
});

2. Impose size and depth limits on claims

Do not allow arbitrarily large tokens or deeply nested claims. Reject tokens that exceed reasonable size or contain deeply nested structures that could lead to stack overflow during processing.

app.post('/login', express.json({ limit: '10kb' }), (req, res) => {
  const token = req.body.token;
  if (!token) {
    return res.status(400).json({ error: 'token required' });
  }
  // Reject tokens with excessive nesting
  try {
    const payload = JSON.parse(Buffer.from(token.split('.')[1], 'base64').toString());
    const claimDepth = (obj, depth = 0) => {
      if (depth > 10) throw new Error('claim nesting too deep');
      if (obj && typeof obj === 'object') {
        for (const key of Object.keys(obj)) {
          claimDepth(obj[key], depth + 1);
        }
      }
      return depth;
    };
    claimDepth(payload);
  } catch (e) {
    return res.status(400).json({ error: 'invalid token structure' });
  }
  // proceed with verification
});

3. Apply consistent security scheme across routes

Ensure that routes requiring JWTs are uniformly protected and that the spec matches implementation. middleBrick’s OpenAPI/Swagger analysis with full $ref resolution can highlight missing enforcement.

// Example route-level middleware in Fiber
const verifyToken = (c) => {
  const auth = c.get('Authorization');
  if (!auth) throw new Error('missing authorization');
  const token = auth.replace('Bearer ', '');
  try {
    jwt.verify(token, PUBLIC_KEY, { algorithms: ['RS256'] });
  } catch {
    throw new Error('invalid token');
  }
};

app.get('/admin', verifyToken, (req, res) => {
  res.json({ admin: true });
});

By combining strict verification, size constraints, and uniform route protection, you reduce the conditions that can lead to Stack Overflow when JWT tokens are processed. middleBrick supports this workflow by enabling scans from the terminal with the CLI (middlebrick scan <url>), adding API security checks to CI/CD pipelines via the GitHub Action, or integrating into AI coding assistants through the MCP Server, while the Dashboard lets you track security scores over time.