Buffer Overflow in Adonisjs with Jwt Tokens

A buffer overflow in the context of AdonisJS and JWT tokens does not typically arise from JavaScript runtime behavior, since Node.js manages memory automatically. Instead, the risk surface appears when token handling interacts with native addons, external parsers, or unsafe data passed into lower-level libraries. If AdonisJS applications deserialize untrusted JWT payloads using libraries that perform unchecked length operations—especially when interfacing with native C/C++ addons or older JSON parsing extensions—malformed tokens with extremely large header or payload fields can trigger memory overreads or overflows in those native components.

JWT tokens are structured as three dot-separated parts: header, payload, and signature. In AdonisJS, developers often use the jsonwebtoken package or AdonisJS-specific JWT utilities to verify tokens. If the application does not enforce strict size limits on the decoded payload before processing claims, an attacker can supply a token with an oversized payload section. When the application or a dependent library copies token data into fixed-size buffers—such as when logging raw token bytes or passing them to native crypto bindings—this can expose memory corruption vulnerabilities.

Specific attack patterns include crafting a JWT with an extremely long string in a claim like sub or a custom field, then passing it to token verification code that does not validate input length. If the verification routine or any underlying native module uses functions like strcpy or performs unchecked memcpy, the oversized claim can overflow a buffer. This may lead to erratic behavior, information disclosure via crash dumps, or potentially allow an attacker to influence execution flow, depending on how the native layer handles memory.

Additionally, token parsing steps that involve base64 decoding without proper bounds checking can exacerbate the issue. For example, a token with a large payload increases memory consumption during decoding, and if the implementation uses a fixed-size output buffer without resizing, the decoder may write past allocated memory. Although AdonisJS itself is written in safe JavaScript, integrations with native modules for performance or cryptographic acceleration can reintroduce these risks if those modules are not carefully audited.

To detect this class of issue, middleBrick scans perform black-box testing of the unauthenticated attack surface, including JWT verification endpoints. The scanner checks whether token acceptance is bounded and whether unusually large tokens trigger defensive responses. Findings highlight cases where token handling lacks input validation, with remediation guidance focused on size limits and safe parsing practices.

Remediation centers on strict validation of JWT payload size and claim values before processing, and avoiding unsafe operations when interacting with native modules. In AdonisJS, use the built-in JWT utilities or jsonwebtoken with explicit options that limit accepted token sizes and enforce claim constraints.

First, configure token verification to reject tokens that exceed reasonable size limits. This can be enforced by inspecting the raw token before decoding and setting a maximum length for the payload segment. For example, before calling jwt.verify, you can validate the token structure and reject suspiciously large tokens:

const jwt = use('jsonwebtoken')
const MAX_TOKEN_SIZE = 8192 // reasonable upper bound

function verifyToken(token) {
  if (typeof token !== 'string' || token.length > MAX_TOKEN_SIZE) {
    throw new Error('Token size exceeds allowed limit')
  }
  const parts = token.split('.')
  if (parts.length !== 3) {
    throw new Error('Invalid token format')
  }
  const payload = JSON.parse(Buffer.from(parts[1], 'base64url').toString())
  // enforce claim constraints
  if (payload.sub && payload.sub.length > 256) {
    throw new Error('Subject claim too long')
  }
  return jwt.verify(token, process.env.JWT_SECRET)
}

Second, define explicit schemas for expected claims using a validation library like Joi to ensure that no single claim consumes excessive memory:

const Joi = use('joi')

const tokenPayloadSchema = Joi.object({
  sub: Joi.string().max(255).required(),
  email: Joi.string().email().max(255),
  iat: Joi.number().integer().min(1000000000).max(3000000000),
  exp: Joi.number().integer().min(1000000000).max(3000000000),
  custom_data: Joi.object().max(10) // limit nested depth and size
}).max(10) // limit total number of claims

function validatePayload(token) {
  const parts = token.split('.')
  const payload = JSON.parse(Buffer.from(parts[1], 'base64url').toString())
  const { error, value } = tokenPayloadSchema.validate(payload)
  if (error) {
    throw new Error('Invalid token claims: ' + error.message)
  }
  return value
}

Third, when integrating with AdonisJS middleware, ensure that JWT verification occurs before allocating large buffers for user data. Use streaming or chunked processing if you must handle large payloads, and avoid concatenating raw token segments into strings that could grow unbounded:

const jwtMiddleware = async ({ request, response, next }) => {
  const authHeader = request.header('authorization')
  if (!authHeader) {
    return response.unauthorized()
  }
  const token = authHeader.replace('Bearer ', '')
  try {
    const payload = validatePayload(token)
    request.authPayload = payload
    await next()
  } catch (error) {
    response.badRequest({ error: 'Invalid token', details: error.message })
  }
}

Finally, audit any native addons or native bindings used in your AdonisJS project for unsafe memory operations when handling external input, including JWTs. Prefer pure-JWT libraries maintained within the Node.js ecosystem and review dependency updates for security patches related to memory safety.