Distributed Denial Of Service in Fiber with Api Keys

Distributed Denial of Service (DDoS) in a Fiber-based API can be amplified or exposed when API keys are used for authentication. While API keys provide a lightweight mechanism to identify and rate-limit clients, they do not inherently prevent resource exhaustion attacks. If key validation is performed on every request without additional protections, an attacker who obtains or guesses a valid key can flood the endpoint, consuming server-side resources such as memory, goroutines, and connection pools. This can degrade service for legitimate users even when the key itself is not weak.

In a black-box scan, middleBrick tests for BFLA and Rate Limiting across authenticated and unauthenticated paths. For a Fiber API that validates API keys on each request, an attacker can send a high volume of requests using a single valid key to observe whether the service remains responsive. Because scanning is unauthenticated, middleBrick can probe endpoints that expose key validation logic indirectly, for example by checking whether the server performs consistent work regardless of key validity. Findings may reveal missing or insufficient rate limiting tied to the key scope, lack of per-key quotas, or missing concurrency caps, which are common in microservices that rely on API keys for routing or tenant identification.

Another risk involves key distribution and storage. If API keys are embedded in client-side code or transmitted over insecure channels, they can be extracted and reused to launch DDoS campaigns. middleBrick checks for Data Exposure and Encryption to ensure keys are not leaked in responses or logs during scanning. Because API keys often authorize access to rate-limited tiers, a compromised key can bypass intended usage limits, enabling attackers to saturate backend services. The scanner also evaluates whether the API surface includes endpoints that are expensive to compute, such as those performing heavy data transformation or external calls, and whether those endpoints are guarded by per-key rate limits.

When integrating with external services, API keys may be validated against a remote authorization service. If that validation introduces synchronous waits or retries, it can increase request latency and leave connections open longer than necessary, making the service more susceptible to slowloris-style attacks. middleBrick tests for SSRF and Input Validation to ensure that keys cannot be forced to trigger unintended external calls or cause the server to hang on malicious payloads. The scanner runs multiple checks in parallel, including Authentication and Rate Limiting, to highlight configurations where key-based controls do not adequately limit request rates per identity.

In summary, DDoS risks in Fiber APIs using API keys arise from insufficient rate limiting tied to the key, expensive operations without adequate guards, and potential exposure of keys through insecure handling. By running a scan with middleBrick, you can identify whether your endpoints enforce per-key quotas, validate input before key lookup, and protect costly operations. The findings include severity-ranked items and remediation guidance mapped to frameworks such as OWASP API Top 10, helping you prioritize fixes that reduce the impact of volumetric attacks without changing your core authentication model.

To reduce DDoS risk when using API keys in Fiber, implement per-key rate limiting and ensure validation logic does not introduce resource amplification. Use a token bucket or sliding window algorithm scoped to each key, and enforce strict request caps. Below are concrete examples showing how to set up API key validation and rate limiting in Fiber.

Example 1: Basic API key validation with per-key rate limiting

package main

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

func main() {
	app := fiber.New()

	// In-memory stores for demonstration; use Redis or another shared store in production
	keyLimits := map[string]limiter.Config{
		"abc123": {Max: 100, Expiration: 60},
		"def456": {Max: 200, Expiration: 60},
	}

	app.Use(keyauth.New(keyauth.Config{
		KeyLookup: &keyauth.KeyLookup{
			Header: "X-API-Key",
		},
		KeyValidator: func(c *fiber.Ctx) bool {
			key := c.Get("X-API-Key")
			cfg, exists := keyLimits[key]
			if !exists {
				return false
			}
			limiter := limiter.New(cfg)
			return limiter.Check(c) == nil
		},
	}))

	app.Get("/v1/resource", func(c *fiber.Ctx) error {
		return c.SendString("OK")
	})

	app.Listen(":3000")
}

Example 2: Scoped rate limiting with middleware and shared store

package main

import (
	"context"
	"github.com/gofiber/fiber/v2"
	"github.com/gofiber/fiber/v2/middleware/keyauth"
	"github.com/redis/go-redis/v9"
)

var ctx = context.Background()

func main() {
	app := fiber.New()

	client := redis.NewClient(&redis.Options{
		Addr: "localhost:6379",
	})

	app.Use(keyauth.New(keyauth.Config{
		KeyLookup: &keyauth.KeyLookup{
			Query: "api_key",
		},
		KeyValidator: func(c *fiber.Ctx) bool {
			key := c.Query("api_key")
			if key == "" {
				return false
			}
			// Use Redis to store and check per-key request counts with TTL
			count, err := client.Incr(ctx, "rl:"+key).Result()
			if err != nil {
				return false
			}
			if count == 1 {
				client.Expire(ctx, "rl:"+key, 60)
			}
			return count <= 100
		},
	}))

	app.Post("/v1/submit", func(c *fiber.Ctx) error {
		return c.SendString("Accepted")
	})

	app.Listen(":3000")
}

These examples show how to bind rate limits to API keys and use shared storage to enforce quotas across instances. They also highlight the importance of validating input before key lookup to avoid unnecessary work for invalid keys. middleBrick can verify that such controls are in place by scanning your endpoints and checking whether rate limiting is consistently applied per key and whether expensive paths are adequately protected.