Type Confusion in Fiber with Jwt Tokens

Type confusion in the Fiber web framework when handling Jwt Tokens occurs when the application incorrectly treats the token or its payload as a different data type than expected, bypassing intended access controls or validation. This typically arises when middleware decodes a Jwt Token but stores or casts the resulting claims into a loosely typed structure, allowing an attacker to manipulate type expectations.

Consider a route that expects a numeric user identifier extracted from a Jwt Token payload but receives a string due to missing validation. If the application uses this identifier in sensitive operations such as fetching user data or authorizing access, the type mismatch can lead to logic flaws like IDOR or authentication bypass. For example, a string "1" might be treated as equivalent to integer 1 depending on comparison logic, enabling horizontal privilege escalation.

Real-world attack patterns mirror findings in the OWASP API Top 10 and can be detected by scanning with middleBrick, which runs checks for BOLA/IDOR, Input Validation, and Property Authorization alongside unauthenticated LLM security probes. middleBrick scans an unauthenticated attack surface in 5–15 seconds, returning a security risk score and per-category breakdowns that highlight type confusion risks tied to Jwt Token handling.

Using the OpenAPI/Swagger spec analysis feature, middleBrick resolves $ref definitions and cross-references them with runtime behavior, identifying mismatches between declared schemas and actual usage. This is particularly useful when Jwt Token claims are defined as one type in the spec but handled as another in the implementation. The scanner maps findings to frameworks such as OWASP API Top 10 and provides prioritized remediation guidance without assuming internal architecture.

An example of vulnerable code that lacks strict type handling:

// Vulnerable: no strict type assertion on claims
const claims = jwt.decode(token, { complete: true })?.payload;
if (claims?.isAdmin) { 
  res.send('Admin access');
}

In the above, claims is loosely evaluated, which can lead to type confusion if the payload contains unexpected types. An attacker could supply a Jwt Token where isAdmin is a string like "true" that still passes a truthy check, bypassing intended authorization.

middleBrick’s authentication and input validation checks are designed to detect such weaknesses during black-box scanning. Because the tool does not fix or block, it supplies actionable findings with remediation steps, allowing developers to tighten type handling and validation for Jwt Token processing in Fiber.

Remediation focuses on strict type validation, schema enforcement, and avoiding implicit type coercion when processing Jwt Tokens in Fiber. Use typed structures to decode and verify claims, and validate each field before use.

1. Enforce strict type assertions and validation after decoding the Jwt Token. Instead of relying on interface{} or loosely typed maps, define a struct that matches the expected payload and use a validated Jwt parsing library.

2. Reject tokens with unexpected types by implementing explicit checks and rejecting malformed or ambiguous claims before they reach business logic.

3. Apply consistent type handling across middleware and route handlers to prevent confusion between string and numeric identifiers, especially when used in authorization decisions.

Example of secure Jwt Token handling in Fiber:

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

type CustomClaims struct {
	UserID   int64  `json:"user_id"`
	Username string `json:"username"`
	IsAdmin  bool   `json:"is_admin"`
	jwt.RegisteredClaims
}

func VerifyToken(tokenString string) (*CustomClaims, error) {
	claims := &CustomClaims{}
	token, err := jwt.ParseWithClaims(tokenString, claims, func(token *jwt.Token) (interface{}, error) {
		// supply your key or verification method here
		return []byte('your-secret-key'), nil
	})
	if err != nil {
		return nil, err
	}
	if !token.Valid {
		return nil, fmt.Errorf("invalid token")
	}
	return claims, nil
}

app.Get("/profile", func(c *fiber.Ctx) error {
	tokenString := c.Get("Authorization")
	if tokenString == "" {
		return c.Status(fiber.StatusUnauthorized).JSON(fiber.Map{"error": "missing authorization header"})
	}
	// strip Bearer prefix if present
	if len(tokenString) > 7 && tokenString[:7] == "Bearer " {
		tokenString = tokenString[7:]
	}
	claims, err := VerifyToken(tokenString)
	if err != nil {
		return c.Status(fiber.StatusUnauthorized).JSON(fiber.Map{"error": "invalid token"})
	}
	// strict type usage: claims.UserID is int64, claims.IsAdmin is bool
	if claims.UserID == 0 || !validateUserExists(claims.UserID) {
		return c.Status(fiber.StatusForbidden).JSON(fiber.Map{"error": "insufficient permissions"})
	}
	return c.JSON(fiber.Map{
		"user_id": claims.UserID,
		"username": claims.Username,
		"is_admin": claims.IsAdmin,
	})
})

In this example, the Jwt Token payload is decoded into a strongly typed CustomClaims struct, ensuring that UserID is an int64 and IsAdmin is a boolean. This prevents type confusion attacks that rely on loose comparisons or unexpected claim types. The middleware checks for a properly formatted Authorization header and handles Bearer prefix stripping explicitly.

middleBrick’s GitHub Action can be added to CI/CD pipelines to fail builds if security scores drop below a defined threshold, helping catch regressions in token handling before deployment. The CLI tool allows scanning from the terminal with middlebrick scan <url>, producing JSON or text output that details findings related to Jwt Token validation and type handling.

For continuous monitoring, the Pro plan provides scheduled scans and alerts, while the MCP Server enables scanning APIs directly from AI coding assistants within the development environment. These integrations support a secure development workflow without introducing runtime agents or requiring credentialed access during scans.