Heap Overflow in Adonisjs with Jwt Tokens

A heap overflow in an AdonisJS application that uses JWT tokens typically arises when token payload validation or signature verification processes handle untrusted input in an unsafe manner. AdonisJS itself does not implement low-level memory operations, so a heap overflow would occur through a vulnerable dependency or an unsafe integration pattern rather than the framework core. When JWT tokens are parsed, the payload is often decoded from base64 and mapped into JavaScript objects. If a consumer of the token performs unsafe concatenation, buffer manipulation, or relies on a native addon that does not properly bound allocations, an attacker can craft an oversized payload that triggers a heap exhaustion or corruption condition.

The risk is elevated when token verification does not enforce size limits on the payload or when deeply nested objects are allowed without constraints. For example, an attacker can submit a token with a deeply nested claims structure that causes recursive parsing and leads to excessive memory allocation. In environments where the application shares memory with other services or runs in constrained containers, such allocations can degrade performance or lead to crashes that expose sensitive information through timing or error messages. The issue is not specific to JWTs per se, but the token’s role as an untrusted input makes the verification path a high-value target for probing memory-handling bugs.

Because middleBrick scans the unauthenticated attack surface, it can flag indicators such as missing size validation on token payloads, lack of depth limiting on JSON structures, and absence of rate limiting that would otherwise mitigate resource exhaustion attempts. These findings map to common weaknesses in the CWE and OWASP API Top 10 categories, emphasizing the importance of validating and constraining token content. Even when using managed JWT libraries, developers must ensure that the surrounding integration applies strict schema checks and does not propagate unchecked payloads into downstream services or native modules.

To reduce the risk associated with JWT tokens in AdonisJS, apply strict validation, size limits, and defensive parsing. Use a maintained library such as jsonwebtoken or @adonisjs/auth with updated dependencies, and enforce constraints on payload structure and size. The following examples illustrate secure patterns for verifying tokens and limiting exposure.

Example 1: Validating token size and payload structure

const jwt = require('jsonwebtoken');

function verifyToken(token) {
  if (!token || typeof token !== 'string') {
    throw new Error('Invalid token type');
  }
  // Enforce a reasonable size limit before decoding
  if (token.length > 8192) {
    throw new Error('Token exceeds maximum allowed length');
  }
  const publicKey = process.env.JWT_PUBLIC_KEY;
  if (!publicKey) {
    throw new Error('JWT public key not configured');
  }
  try {
    const decoded = jwt.verify(token, publicKey, { algorithms: ['RS256'] });
    // Validate expected shape and depth
    if (!decoded || typeof decoded !== 'object' || Array.isArray(decoded)) {
      throw new Error('Invalid decoded token structure');
    }
    if (typeof decoded.sub !== 'string' || !decoded.sub) {
      throw new Error('Missing or invalid subject');
    }
    // Reject unexpected or deeply nested claims
    const hasExcessiveDepth = (obj, depth = 0) => {
      if (depth > 4) return true;
      if (obj && typeof obj === 'object' && !Array.isArray(obj)) {
        return Object.values(obj).some((v) => hasExcessiveDepth(v, depth + 1));
      }
      return false;
    };
    if (hasExcessiveDepth(decoded)) {
      throw new Error('Token payload exceeds maximum nesting depth');
    }
    return decoded;
  } catch (err) {
    throw new Error(`Token verification failed: ${err.message}`);
  }
}

Example 2: Using AdonisJS auth utilities with constrained claims

const { createMiddlewareClient } = require('@adonisjs/auth');

async function handleProtectedRoute(ctx) {
  const client = createMiddlewareClient({ ctx });
  const token = client.getBearerToken();
  if (!token) {
    ctx.response.status(401).send({ error: 'Unauthorized' });
    return;
  }
  try {
    const verified = await jwt.verify(token, process.env.JWT_PUBLIC_KEY, {
      algorithms: ['HS256'],
      maxAge: '15m',
    });
    // Apply schema validation (e.g., using Joi or Yup)
    const schema = Joi.object({
      sub: Joi.string().required(),
      role: Joi.string().valid('user', 'admin').required(),
      iat: Joi.number().required(),
      exp: Joi.number().required(),
    }).max(5); // limit number of top-level claims
    const { error, value } = schema.validate(verified);
    if (error || !value) {
      ctx.response.status(400).send({ error: 'Invalid token claims' });
      return;
    }
    ctx.auth.user = value;
  } catch (err) {
    ctx.response.status(401).send({ error: 'Invalid token' });
  }
}

These examples emphasize input validation, size capping, and schema enforcement to reduce the attack surface. They also align with middleBrick’s checks for authentication weaknesses, input validation, and property authorization, providing actionable guidance that maps to compliance frameworks such as OWASP API Top 10 and PCI-DSS.