Heap Overflow in Fiber with Jwt Tokens

A heap-based buffer overflow in a Fiber application that processes JWT tokens typically arises when unbounded copying or concatenation occurs while parsing the token’s payload or headers. Because JWTs are often base64url-encoded strings, decoding these strings into mutable buffers on the heap can introduce risks if the implementation does not enforce strict size limits. In Go, the net/http package is commonly used with Fiber to handle requests; if the application decodes the JWT without validating its length and writes the result into a slice or buffer allocated on the heap, an oversized token can overflow the allocated memory region.

Consider an endpoint that directly decodes the JWT using a third-party library without length checks. The token’s payload or header may be crafted to be extremely large, leading to a heap allocation that grows beyond intended boundaries. This can corrupt adjacent memory, potentially allowing an attacker to influence program behavior. Even though Go’s runtime includes some memory safety features, logical errors such as using unchecked input sizes in byte slices can still lead to conditions that resemble heap overflows in terms of memory corruption or excessive resource consumption.

Additionally, if the application concatenates multiple JWTs or uses token data to construct dynamic data structures (e.g., building a session object or caching key), the lack of proper bounds checking exacerbates the risk. The combination of Fiber’s performance-oriented routing and the JWT’s presence as a frequently parsed element increases the attack surface when input validation is insufficient. This scenario aligns with common weaknesses in input validation and insecure consumption patterns identified by security checks such as those performed by middleBrick, which tests for unsafe consumption and input validation issues in unauthenticated scans.

To mitigate heap overflow risks when handling JWT tokens in Fiber, enforce strict size limits before decoding and avoid unbounded memory operations. Use well-maintained JWT libraries that validate token length and structure, and ensure that any byte buffers derived from token claims are bounded. Below are concrete code examples demonstrating secure handling in a Fiber application.

First, define a maximum allowed JWT size and validate the token string length before passing it to the parser. This prevents excessively large tokens from being processed and reduces the risk of heap-related issues.

const maxJWTSize = 8192 // 8 KB limit

func VerifyTokenLength(c *fiber.Ctx) error {
    token := c.Get("Authorization")
    if len(token) > maxJWTSize {
        return c.Status(fiber.StatusRequestEntityTooLarge).JSON(fiber.Map{
            "error": "token too large",
        })
    }
    // Proceed with validation
    return nil
}

Second, use a robust JWT library such as `golang-jwt/jwt` and decode tokens with strict claims validation, ensuring that the parsed payload does not trigger unbounded allocations. Configure the parser to reject tokens with unexpected sizes or malformed structures.

import (
    "github.com/golang-jwt/jwt/v5"
    "net/http"
)

func ParseAndValidateToken(tokenString string) (*jwt.Token, error) {
    token, err := jwt.Parse(tokenString, func(token *jwt.Token) (interface{}, error) {
        if _, ok := token.Method.(*jwt.SigningMethodHMAC); !ok {
            return nil, http.ErrNotSupported
        }
        return []byte("your-secret-key"), nil
    })
    if err != nil {
        return nil, err
    }
    if !token.Valid {
        return nil, http.ErrNotSupported
    }
    return token, nil
}

Finally, avoid using token data directly to size heap allocations. Instead, map claims to fixed-size structures and apply explicit checks on numeric claim values (e.g., exp, iat) to prevent logical errors that could lead to memory misuse. middleBrick’s scans can help identify missing length validations and unsafe consumption patterns, supporting compliance with OWASP API Top 10 and related frameworks.