MEDIUM insufficient loggingfiberjwt tokens

Insufficient Logging in Fiber with Jwt Tokens

Insufficient Logging in Fiber with Jwt Tokens — how this compromise creates or exposes risk

Insufficient Logging in a Fiber API that uses JWT tokens can weaken visibility and delay incident response. When JWT tokens are accepted but requests are not recorded with enough context, an attacker can probe endpoints, submit malformed or unsigned tokens, or attempt token replay without leaving a reliable audit trail. This lack of traceability makes it harder to detect brute-force attempts, token manipulation, or lateral movement across authenticated routes.

In a typical Fiber setup, developers may add JWT validation middleware but omit structured logging of token validation outcomes, user identities, or request metadata. Without logs that capture token issuance source (if available), scopes, expiration, and validation failures, suspicious patterns—such as repeated invalid signatures or expired tokens from the same IP—are difficult to surface. Attackers can exploit this by testing stolen or forged tokens against admin routes, knowing that failures will not be recorded or alerted.

Additionally, if logs exclude request identifiers that tie HTTP calls to specific token claims, correlating events across services becomes unreliable. For example, an endpoint that accepts a JWT with a role claim may authorize access but not log the authorization decision or the original token payload. This gap can allow privilege escalation attempts (e.g., modifying a role claim) to go unnoticed. Even when tokens are validated successfully, missing timestamps and user context reduce the usefulness of logs for forensic analysis, particularly when incidents are reviewed against frameworks like OWASP API Top 10 or common authentication weaknesses.

middleBrick can detect insufficient logging when scanning an unauthenticated Fiber endpoint that uses JWT tokens. By sending requests with missing, malformed, and valid-looking tokens, the scanner can observe whether outcomes are recorded and whether logs would support incident investigation. Findings highlight missing event details such as token validation result, user ID, scopes, request path, and correlation data, providing remediation guidance tied to authentication logging best practices.

Jwt Tokens-Specific Remediation in Fiber — concrete code fixes

To address insufficient logging in Fiber when using JWT tokens, enrich your middleware to record structured, actionable events for each request and validation outcome. Below are concrete Go examples using the Fiber framework and a JWT middleware approach that logs key details without exposing secrets.

Example 1: Structured logging for token validation outcomes

Use a middleware that validates the token and logs success or failure with relevant, non-sensitive metadata. Avoid logging the full token or private claims.

//go
package main

import (
	"log"
	"net/http"
	"time"

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

type LogFields struct {
	Timestamp    string `json:"@timestamp"`
	Method       string
	Path         string
	ClientIP     string
	TokenStatus  string // "valid", "invalid", "missing"
	UserID       string // derived from claims, if available
	Scopes       string
	ErrorCode    string
	ErrorMessage string
}

func jwtLogger(next fiber.Handler) fiber.Handler {
	return func(c *fiber.Ctx) error {
		tokenString := c.Get("Authorization")
		fields := LogFields{
			Timestamp:   time.Now().UTC().Format(time.RFC3339),
			Method:      c.Method(),
			Path:        c.Path(),
			ClientIP:    c.IP(),
			TokenStatus: "missing",
		}

		if tokenString == "" {
			log.Printf("auth_event %v", fields)
			return c.Status(fiber.StatusUnauthorized).JSON(fiber.Map{"error": "authorization header missing"})
		}

		// Remove "Bearer " prefix if present
		if len(tokenString) > 7 && tokenString[:7] == "Bearer " {
			tokenString = tokenString[7:]
		}

		claims := jwt.MapClaims{}
		token, err := jwt.Parse(tokenString, func(token *jwt.Token) (interface{}, error) {
			// TODO: provide your key or validation function
			return []byte("your-secret"), nil
		})

		if err != nil || !token.Valid {
			fields.TokenStatus = "invalid"
			fields.ErrorCode = "invalid_token"
			fields.ErrorMessage = err.Error()
			log.Printf("auth_event %v", fields)
			return c.Status(fiber.StatusUnauthorized).JSON(fiber.Map{"error": "invalid token"})
		}

		if claims, ok := token.Claims.(jwt.MapClaims); ok && token.Valid {
			fields.TokenStatus = "valid"
			if sub, ok := claims["sub"].(string); ok {
				fields.UserID = sub
			}
			if scopes, ok := claims["scopes"].(string); ok {
				fields.Scopes = scopes
			}
			log.Printf("auth_event %v", fields)
		}

		return next(c)
	}
}

func main() {
	app := fiber.New()
	app.Use(jwtLogger)
	app.Get("/api/secure", func(c *fiber.Ctx) error {
		return c.JSON(fiber.Map{"message": "authorized"})
	})
	app.Listen(":3000")
}

Example 2: Enriching logs with request IDs and outcomes

Include a request-scoped correlation ID so you can trace a request across logs and services. Combine this with explicit outcome recording for authorization decisions.

//go
package main

import (
	"context"
	"log"
	"net/http"
	"os"

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

func requestID(next fiber.Handler) fiber.Handler {
	return func(c *fiber.Ctx) error {
		reqID := c.Get("X-Request-Id")
		if reqID == "" {
			reqID = "unknown"
		}
		c.Locals("reqID", reqID)
		return next(c)
	}
}

func jwtAuthWithAudit(next fiber.Handler) fiber.Handler {
	return func(c *fiber.Ctx) error {
		reqID := c.Locals("reqID").(string)
		tokenString := c.Get("Authorization")
		audit := map[string]interface{}{
			"request_id": reqID,
			"method":     c.Method(),
			"path":       c.Path(),
			"client_ip":  c.IP(),
		}

		if tokenString == "" {
			audit["token_status"] = "missing"
			audit["error"] = "authorization header missing"
			logAudit(audit)
			return c.Status(fiber.StatusUnauthorized).JSON(fiber.Map{"error": "authorization header missing"})
		}

		if len(tokenString) > 7 && tokenString[:7] == "Bearer " {
			tokenString = tokenString[7:]
		}

		claims := jwt.MapClaims{}
		token, err := jwt.Parse(tokenString, func(token *jwt.Token) (interface{}, error) {
			return []byte("your-secret"), nil
		})

		if err != nil || !token.Valid {
			audit["token_status"] = "invalid"
			audit["error"] = err.Error()
			logAudit(audit)
			return c.Status(fiber.StatusUnauthorized).JSON(fiber.Map{"error": "invalid token"})
		}

		audit["token_status"] = "valid"
		if claims != nil {
			if sub, ok := claims["sub"].(string); ok {
				audit["user_id"] = sub
			}
			if scopes, ok := claims["scopes"].(string); ok {
				audit["scopes"] = scopes
			}
		}
		logAudit(audit)
		return next(c)
	}
}

func logAudit(audit map[string]interface{}) {
	// Send audit entry to your logging backend; keep PII and secrets out
	log.Println(audit)
}

func main() {
	app := fiber.New()
	app.Use(requestID())
	app.Use(jwtAuthWithAudit)
	app.Get("/api/secure", func(c *fiber.Ctx) error {
		return c.JSON(fiber.Map{"message": "authorized"})
	})
	app.Listen(":3000")
}

These examples show how to log token status, user ID, scopes, request identifiers, and errors in a structured way. Ensure logs are centralized and retention policies align with compliance requirements. Avoid logging raw tokens or secrets. middleBrick’s scanner can validate whether such logging is present and whether events are emitted for critical outcomes like invalid tokens or authorization denials.

Frequently Asked Questions

What constitutes insufficient logging when JWT tokens are used in Fiber APIs?
Insufficient logging occurs when requests that use JWT tokens are not recorded with structured details such as token validation outcome (valid/invalid/missing), user identity (e.g., subject claim), scopes, request path, method, client IP, timestamps, and correlation identifiers. Missing these fields prevents detection of brute-force or token-replay attacks and hinders forensic analysis.
How can I verify that my logging improvements are effective without exposing sensitive data?
Use structured logs that include non-sensitive metadata (request ID, path, HTTP method, token status, user ID derived from claims, scopes, and error codes) without logging raw tokens or secrets. You can validate effectiveness by running a scanner like middleBrick, which can check whether critical events are emitted and whether logs contain actionable context for incident investigation.