Prototype Pollution in Fiber with Jwt Tokens

Prototype pollution in a Fiber application becomes particularly concerning when JWT tokens are used for authentication. If user-controlled input influences how JWT claims are parsed, validated, or merged into application objects, an attacker can inject properties into Object.prototype or other shared prototypes. This can alter behavior across requests, for example changing how token verification logic interprets roles or permissions.

Consider a scenario where a Fiber endpoint accepts a JSON payload that is merged into a JWT claims set before signing or verification. If the merge operation is shallow or uses a vulnerable utility, an attacker can provide a payload such as {"__proto__": {"isAdmin": true}}. When the application later checks claims for authorization, the polluted prototype may cause obj.isAdmin to evaluate to true even when the token did not originally contain that claim. This bypasses intended access controls without needing to forge the token signature.

Another risk arises when JWT headers or claims are deserialized using libraries that recursively merge user input into shared objects. An attacker might supply keys like __proto__, constructor, or prototype within nested objects. Because these keys have special meaning in JavaScript, the merged result can modify the prototype chain, leading to unexpected behavior in later token processing or in downstream logic that relies on mutated objects.

In a black-box scan, middleBrick tests for Prototype Pollution across request parameters, headers, and JWT claim fields. It checks whether crafted payloads result in modified prototypes or unintended property access. Findings include evidence that injected properties affect object behavior across requests, which can undermine token-based authorization assumptions. The scanner also highlights areas where input validation is insufficient, such as missing allowlists for object keys or unsafe merging routines that do not sanitize special properties.

Because JWT tokens often carry authorization decisions, prototype pollution can escalate from a generic injection issue to a security bypass. For example, an application that derives scopes from token claims may inadvertently include polluted properties in scope checks, effectively granting elevated privileges. middleBrick flags such cross-category risks by correlating its Authentication and BOLA/IDOR checks with Prototype Pollution findings, providing a prioritized view of how an attacker might chain weaknesses.

To secure JWT handling in Fiber, ensure that user input never directly mutates objects used in claims or headers processing. Use strict parsing and merging strategies that exclude dangerous keys and prefer immutable updates. The following examples show safe patterns for decoding, validating, and signing tokens in Fiber using the golang-jwt/jwt library.

Safe JWT parsing with explicit claims mapping

Define a concrete claims struct and parse tokens without generic map merging. This prevents attacker-controlled keys from being interpreted as prototype properties.

// Define a custom claims type with only expected fields
type AppClaims struct {
    Username string `json:"username"`
    Role     string `json:"role"`
    jwt.RegisteredClaims
}

func ParseToken(tokenString string) (*AppClaims, error) {
    token, err := jwt.ParseWithClaims(tokenString, &AppClaims{}, func(token *jwt.Token) (interface{}, error) {
        // Use a secure key source in production
        return []byte("your-256-bit-secret"), nil
    })
    if err != nil {
        return nil, err
    }
    if claims, ok := token.Claims.(*AppClaims); ok && token.Valid {
        return claims, nil
    }
    return nil, errors.New("invalid token")
}

Validating and sanitizing input before merging into JWT claims

If you must merge user data into claims, explicitly allowlist permitted fields and reject any keys that could trigger prototype pollution.

func SanitizeClaims(input map[string]interface{}) (map[string]interface{}, error) {
    allowed := map[string]bool{
        "username": true,
        "role":     true,
        "scope":    true,
    }
    out := make(map[string]interface{})
    for k, v := range input {
        if !allowed[k] {
            continue // drop disallowed keys
        }
        out[k] = v
    }
    return out, nil
}

func BuildToken(claims map[string]interface{}) (string, error) {
    sanitized, err := SanitizeClaims(claims)
    if err != nil {
        return "", err
    }
    token := jwt.NewWithClaims(jwt.SigningMethodHS256, sanitized)
    return token.SignedString([]byte("your-256-bit-secret"))
}

Securing token creation and avoiding unsafe merges

Never use generic merge functions that iterate over user-supplied maps and assign keys directly onto shared objects. Instead, construct claims from explicitly defined fields.

func CreateToken(username, role string) (string, error) {
    claims := jwt.MapClaims{
        "username": username,
        "role":     role,
        "exp":      time.Now().Add(time.Hour * 72).Unix(),
        "iat":      time.Now().Unix(),
        "iss":      "fiber-app",
    }
    token := jwt.NewWithClaims(jwt.SigningMethodHS256, claims)
    return token.SignedString([]byte("your-256-bit-secret"))
}

Middleware validation in Fiber

Use Fiber middleware to validate incoming tokens before they reach handlers, ensuring only expected claim shapes are processed.

func JWTAuth() fiber.Handler {
    return func(c *fiber.Ctx) error {
        auth := c.Get("Authorization")
        if auth == "" {
            return c.Status(fiber.StatusUnauthorized).JSON(fiber.Map{"error": "missing authorization header"})
        }
        tokenString := strings.TrimPrefix(auth, "Bearer ")
        claims, err := ParseToken(tokenString)
        if err != nil || !claims.VerifyIssuer(c.Context().Value("issuer").(string), true) {
            return c.Status(fiber.StatusUnauthorized).JSON(fiber.Map{"error": "invalid token"})
        }
        c.Locals("claims", claims)
        return c.Next()
    }
}

By strictly controlling how JWT claims are built and parsed, you reduce the risk that user-controlled input can influence object prototypes. middleBrick supports this posture by scanning endpoints that accept JWT-related inputs and validating that unsafe merging patterns are not present.