Api Rate Abuse in Gorilla Mux with Openid Connect

Gorilla Mux is a powerful HTTP router for Go that supports route variables and matchers, but it does not provide built-in rate limiting. When combined with OpenID Connect (OIDC) for authentication, APIs can still be abused if requests are not limited per identity. OIDC introduces identity via ID tokens, usually validated through an issuer and subject claim, but without rate limiting on token-based identity, attackers can flood specific user contexts.

An API protected only by OIDC authentication accepts valid bearer tokens and routes them through Gorilla Mux. If no per-subject or per-client rate limits exist, an authenticated user (or a compromised token) can issue thousands of requests per second to high-cost endpoints. This is rate abuse by identity: the attacker does not need to bypass authentication; they abuse the granted access pattern.

Gorilla Mux makes it easy to extract route parameters and headers, including the Authorization header, but developers must explicitly enforce limits. Without middleware that checks the subject (e.g., sub claim) or the client ID (e.g., client_id claim) against a sliding window or token bucket, the endpoint is vulnerable. Real-world abuse includes credential stuffing bursts against user-specific endpoints or mass scraping of resources tied to a single OIDC subject.

Moreover, OIDC discovery and token introspection add latency; if rate limits are applied after expensive token validation, the service becomes susceptible to resource exhaustion even when the overall request volume appears normal. Attackers can target endpoints with complex validation paths, knowing that each request carries a valid identity, which may bypass IP-based defenses. This shifts the abuse surface from generic IP throttling to identity-aware flooding.

For example, an endpoint /api/v1/users/{userID}/preferences protected by Gorilla Mux and OIDC can be hammered by a single authenticated user modifying their own ID repeatedly. Without a per-subject rate limit, the single authenticated identity can drive high request rates, causing denial-of-service for that user or excessive load on backend stores. MiddleBrick detects such identity-based rate abuse patterns in scans, highlighting missing per-identity throttling alongside OIDC context.

To mitigate rate abuse in Gorilla Mux with OIDC, enforce per-identity rate limiting using claims extracted from validated ID tokens. Use middleware that runs after OIDC validation so the subject or client ID is available. Combine in-memory or distributed rate limiters (e.g., Redis + token bucket) with sensible defaults and configurable thresholds per endpoint sensitivity.

Below is a concise, realistic example of OIDC validation and rate limiting in Gorilla Mux. It uses a third-party OIDC provider for token validation and a simple in-memory rate limiter for demonstration; production systems should use a robust store like Redis.

package main

import (
	"context"
	"fmt"
	"log"
	"net/http"
	"strings"
	"time"

	"github.com/gorilla/mux"
	"golang.org/x/oauth2"
	"golang.org/x/oauth2/clientcredentials"
)

// RateLimiter is a simple token-bucket per key.
type RateLimiter struct {
	interval time.Duration
	limit    int
	tokens   map[string]int
	last     map[string]time.Time
}

func NewRateLimiter(qps int) *RateLimiter {
	return &RateLimiter{
		interval: time.Second,
		limit:    qps,
		tokens:   make(map[string]int), 
		last:     make(map[string]time.Time),
	}
}

func (rl *RateLimiter) Allow(key string) bool {
	now := time.Now()
	elapsed := now.Sub(rl.last[key])
	// refill tokens based on elapsed
	refill := int(elapsed / rl.interval) 
	if refill > 0 {
		rl.tokens[key] = min(rl.limit, rl.tokens[key]+refill)
		rl.last[key] = now
	}
	if rl.tokens[key] < rl.limit {
		rl.tokens[key]++
		return true
	}
	return false
}

func min(a, b int) int {
	if a < b {
		return a
	}
	return b
}

// OIDC validation middleware (simplified).
func oidcValidate(next http.Handler) http.Handler {
	return http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
		// In practice, validate the JWT using your OIDC provider's keys.
		// This example uses a bearer token extraction placeholder.
		auth := r.Header.Get("Authorization")
		if auth == "" {
			http.Error(w, "authorization header required", http.StatusUnauthorized)
			return
		}
		parts := strings.Split(auth, " ")
		if len(parts) != 2 || parts[0] != "Bearer" {
			http.Error(w, "invalid authorization format", http.StatusUnauthorized)
			return
		}
		// Simulate extracting subject from token.
		// Replace with real JWT parsing and claims validation.
		subject := "user-123" // e.g., from token claims
		ctx := context.WithValue(r.Context(), "subject", subject)
		next.ServeHTTP(w, r.WithContext(ctx))
	})
}

// RateLimitMiddleware uses subject from context.
func rateLimitMiddleware(rl *RateLimiter, next http.Handler) http.Handler {
	return http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
		sub, ok := r.Context().Value("subject").(string)
		if !ok || sub == "" {
			http.Error(w, "missing subject", http.StatusForbidden)
			return
		}
		if !rl.Allow(sub) {
			http.Error(w, "rate limit exceeded", http.StatusTooManyRequests)
			return
		}
		next.ServeHTTP(w, r)
	})
}

func preferencesHandler(w http.ResponseWriter, r *http.Request) {
	vars := mux.Vars(r)
	userID := vars["userID"]
	fmt.Fprintf(w, "preferences for %s", userID)
}

func main() {
	r := mux.NewRouter()
	rl := NewRateLimiter(5) // 5 requests per second per subject

	r.HandleFunc("/api/v1/users/{userID}/preferences", preferencesHandler).
		Methods("GET")

	chain := oidcValidate(rateLimitMiddleware(rl, r))
	http.ListenAndServe(":8080", chain)
}