Insecure Deserialization in Fiber with Jwt Tokens

Insecure deserialization occurs when an application processes untrusted serialized objects without sufficient validation. In the context of Fiber and JWT tokens, the risk typically arises not from JWT deserialization itself—since JWTs are usually parsed as signed tokens with verifiable claims—but from how application code may deserialize additional data structures that are influenced by or derived from token contents.

Consider a Fiber route that accepts a JWT in the Authorization header and then uses claims from the token to guide further deserialization of user-controlled input. For example, a server might read a role claim such as role and use it to decide which concrete type to instantiate when unmarshaling a JSON, XML, or gob payload. If the type selection is based directly on attacker-influenced data (including data that ultimately derives from the token), an attacker may supply a malicious type or gadget chain, leading to arbitrary code execution or unintended object graph construction. This is effectively an Object Injection or Insecure Deserialization issue mapped to the OWASP API Top 10 and commonly cataloged as a critical or high severity finding in scans.

Even when JWT validation is correctly performed using a trusted library, the surrounding application logic can reintroduce risk. For instance, a token may include metadata or a serialized object reference that the server fetches and deserializes without integrity checks or strict allow-lists. Because middleBrick tests unauthenticated attack surfaces, it can surface endpoints where token-derived parameters affect deserialization paths, exposing unsafe patterns such as missing type constraints or reflection-based unmarshaling. These patterns may align with known gadget chains observed in previous CVEs involving popular Go or Java libraries, depending on the backend runtime.

In a black-box scan, middleBrick runs checks such as Input Validation, Property Authorization, and Unsafe Consumption in parallel with the LLM/AI Security suite. For JWT-related flows, this includes verifying whether tokens influence data handling in ways that bypass authorization or enable injection. The scanner does not assume trust from the presence of a valid signature; it examines how claims propagate into business logic and whether deserialization points are bounded by strict schemas and allow-lists.

To mitigate insecure deserialization risks while using JWT tokens in Fiber, ensure that token claims are treated as authoritative metadata only for access control and not as a basis for dynamic type selection or unsafe deserialization. Below are concrete, idiomatic code examples for a secure approach.

First, validate and parse the JWT using a well-maintained library and enforce strict claims expectations:

package main

import (
    "github.com/gofiber/fiber/v2"
    "github.com/gofiber/fiber/v2/middleware/jwt"
)

func main() {
    app := fiber.New()
    config := jwt.Config{
        SigningKey:   []byte("your-strong-secret"),
        ContextKey:   "user",
        SigningMethod: "HS256",
    }
    app.Use(jwt.New(config))

    app.Get("/profile", func(c *fiber.Ctx) error {
        user := c.Locals("user").(*jwt.Token)
        claims := user.Claims.(jwt.MapClaims)
        // Use claims only for authorization, not for type selection
        if claims["role"] != "admin" {
            return c.Status(fiber.StatusForbidden).JSON(fiber.Map{"error": "insufficient permissions"})
        }
        // Safe: static response assembly, no deserialization of untrusted type hints
        return c.JSON(fiber.Map{"message": "profile for admin"})
    })

    app.Listen(":3000")
}

Second, if you must deserialize user-controlled data, avoid reflection-based or interface-heavy unmarshaling and use explicit, allow-listed structures:

import (
    "encoding/json"
    "github.com/gofiber/fiber/v2"
)

type SafePayload struct {
    Action string `json:"action"`
    Target string `json:"target"`
}

func SafeHandler(c *fiber.Ctx) error {
    var p SafePayload
    if err := c.BodyParser(&p); err != nil {
        return c.Status(fiber.StatusBadRequest).JSON(fiber.Map{"error": "invalid payload"})
    }
    // Apply business logic based on enumerated actions, not on deserialized types
    if p.Action != "update" && p.Action != "view" {
        return c.Status(fiber.StatusBadRequest).JSON(fiber.Map{"error": "action not allowed"})
    }
    // Proceed with safe handling of Target, ensuring no further deserialization
    return c.JSON(fiber.Map{"received": p.Target})
}

Finally, integrate middleBrick into your workflow to continuously verify that endpoints using JWTs do not expose dangerous deserialization patterns. With the CLI tool, you can run middlebrick scan <url> to obtain a security risk score and prioritized findings. For teams with pipelines, the GitHub Action can add API security checks to CI/CD and fail builds if the score drops below your chosen threshold, while the Pro plan supports continuous monitoring and alerts. The MCP Server enables scanning APIs directly from AI coding assistants within your IDE, helping catch insecure patterns early.