Out Of Bounds Read in Fiber with Jwt Tokens

An Out Of Bounds Read occurs when a program reads memory beyond the intended buffer. In the context of a Fiber application that uses JWT tokens, this typically arises during token parsing, validation, or claims extraction when lengths or indices are not properly bounded. Because JWT tokens are often transmitted in HTTP headers (e.g., Authorization: Bearer <token>), mishandling the token string or its decoded payload can expose memory contents or lead to information disclosure.

Consider a Fiber route that extracts a user identifier from a JWT claim without validating the token length or the position of elements within the claims map. If the application assumes a fixed structure or uses integer indices derived from attacker-controlled data, it may read beyond the allocated slice/array representing the claims. For example, using a numeric index to access a claims map without checking map size can result in reading uninitialized memory or adjacent data, potentially leaking private information embedded in the process memory.

Additionally, if the application manually parses the JWT compact representation (header.payload.signature) using string splits and index-based segment access, an attacker-supplied token with an unexpected number of segments or an abnormally large payload can trigger an out-of-bounds condition. This is especially risky when the code uses C-style byte operations or conversions on the raw token bytes, as the runtime may not enforce safe bounds. MiddleBrick’s LLM/AI Security checks include detection of unsafe consumption patterns and system prompt leakage, which can surface insecure handling of tokens in AI-integrated endpoints that rely on JWTs for authorization.

Insecure usage patterns may also intersect with other security checks such as Input Validation and Authentication. For instance, a missing validation layer on the token’s structure can bypass authentication checks, while improper bounds around the payload enable data exposure. The scanner evaluates these interactions by correlating runtime behavior with the OpenAPI specification, including $ref resolution, to identify whether JWT handling endpoints expose unsafe memory access patterns.

Using the CLI tool, developers can quickly identify endpoints that process JWT tokens unsafely by running: middlebrick scan <url>. The resulting report highlights findings related to Data Exposure and Unsafe Consumption with remediation guidance. For teams on the Pro plan, continuous monitoring ensures that any changes to token handling logic trigger re-scans and alerts, helping to catch regressions early.

To remediate Out Of Bounds Read risks when working with JWT tokens in Fiber, enforce strict validation, avoid index-based map access, and use well-audited libraries for token parsing. Below are concrete code examples that demonstrate secure handling.

Secure token validation and claims extraction

Use a maintained JWT library and validate the token structure before extracting claims. Ensure you check the length of the token and validate expected claims such as issuer and audience.

// Secure JWT handling in Fiber
package main

import (
	"github.com/gofiber/fiber/v2"
	"github.com/golang-jwt/jwt/v5"
)

func main() {
	app := fiber.New()
	app.Get("/profile", func(c *fiber.Ctx) error {
		auth := c.Get("Authorization")
		if len(auth) < 8 || auth[:7] != "Bearer " {
			return c.Status(fiber.StatusUnauthorized).JSON(fiber.Map{"error": "invalid authorization header format"})
		}
		tokenString := auth[7:]
		if len(tokenString) == 0 {
			return c.Status(fiber.StatusBadRequest).JSON(fiber.Map{"error": "missing token"})
		}

		claims := jwt.MapClaims{}
		token, err := jwt.ParseWithClaims(tokenString, claims, func(token *jwt.Token) (interface{}, error) {
			// TODO: provide your signing key or public key
			return []byte("your-secret-key"), nil
		})
		if err != nil || !token.Valid {
			return c.Status(fiber.StatusUnauthorized).JSON(fiber.Map{"error": "invalid token"})
		}

		// Access specific claims with presence checks
		if sub, ok := claims["sub"].(string); ok && len(sub) > 0 {
			return c.JSON(fiber.Map{"user": sub})
		}
		return c.Status(fiber.StatusBadRequest).JSON(fiber.Map{"error": "invalid claims"})
	})
	app.Listen(":3000")
}

Avoid index-based access on claims maps

Do not use numeric indices to access map entries. Instead, use typed assertions and verify keys exist to prevent reading unexpected memory regions.

// Safe claim access
if name, ok := claims["name"].(string); ok {
	// use name safely
} else {
	// handle missing claim
}

Input validation and schema checks

Validate the token payload against an expected schema. This reduces the risk of processing malformed tokens that could trigger boundary issues.

// Basic schema validation example
if len(claims) == 0 {
	return c.Status(fiber.StatusBadRequest).JSON(fiber.Map{"error": "empty claims"})
}
if exp, ok := claims["exp"].(float64); ok {
	// compare exp with current time
}

For teams using the GitHub Action, add API security checks to your CI/CD pipeline to fail builds if risk scores exceed your threshold. The MCP Server enables scanning APIs directly from AI coding assistants, helping to catch insecure token handling during development.