Brute Force Attack in Echo Go with Basic Auth

A brute force attack against an Echo Go service using HTTP Basic Auth attempts many username and password combinations to find valid credentials. Because Basic Auth encodes credentials in each request (typically with Base64, not encryption), an attacker who can reach the endpoint can systematically guess credentials. Echo Go does not inherently provide mechanisms to detect or slow down password guessing, so an unauthenticated attacker can iterate through credentials without triggering automated defenses.

In this setup, the vulnerability arises from the combination of predictable or weak passwords and the absence of rate limiting or account lockout policies. If the API also exposes account enumeration behaviors—such as different HTTP status codes or response bodies for valid versus invalid users—an attacker can further optimize their guesses. middleBrick scans this attack surface in an unauthenticated, black-box manner, identifying whether the service leaks information via timing differences or error messages that facilitate credential guessing.

Because Basic Auth transmits credentials per request, interception risks are elevated if transport encryption is misconfigured or absent. Even when TLS is used, weak passwords remain susceptible to offline cracking if captured. The 12 parallel security checks include Authentication and Rate Limiting, which together evaluate whether the service allows rapid, unthrottled attempts and whether responses reveal user existence. Findings include severity-ranked guidance to harden authentication paths and reduce the attack surface.

To mitigate brute force risks with Basic Auth in Echo Go, implement rate limiting, account lockout, and secure credential handling. The following example shows a secure handler using middleware to enforce request limits and avoid user enumeration.

package main

import (
	"net/http"
	"strings"
	"time"

	"github.com/labstack/echo/v4"
	"github.com/labstack/echo/v4/middleware"
)

// In-memory attempt tracking (use Redis in production)
type attemptKey struct {
	username string
	ip       string
}

var attempts = make(map[attemptKey]int)
var lockouts = make(map[string]time.Time)

func basicAuthWithRateLimit(next echo.HandlerFunc) echo.HandlerFunc {
	return func(c echo.Context) error {
		user, pass, ok := c.Request().BasicAuth()
		if !ok {
			return c.String(http.StatusUnauthorized, "Authorization header required")
		}

		ip := c.RealIP()
		key := attemptKey{username: user, ip: ip}

		// Check if account is temporarily locked
		if lockoutTime, found := lockouts[user]; found && time.Now().Before(lockoutTime) {
			return c.String(http.StatusTooManyRequests, "account temporarily locked")
		}

		// Validate credentials securely (constant-time comparison recommended)
		if !validateCredentials(user, pass) {
			attempts[key]++
			if attempts[key] >= 5 {
				lockouts[user] = time.Now().Add(15 * time.Minute)
				delete(attempts, key)
				return c.String(http.StatusTooManyRequests, "account temporarily locked")
			}
			return c.String(http.StatusUnauthorized, "invalid credentials")
		}

		// Reset attempts on success
		delete(attempts, key)
		return next(c)
	}
}

func validateCredentials(username, password string) bool {
	// Replace with secure lookup and constant-time comparison
	// Example hardcoded check for demonstration only
	return username == "admin" && password == "SuperSecurePass123!"
}

func main() {
	e := echo.New()

	// Use secure TLS configuration in production
	e.Use(middleware.TLSWithConfig(middleware.TLSConfig{

		Certificates: []tls.Certificate{},
		Next:          middleware.DefaultTLSConfig.Next,
	}))

	// Apply rate-limited Basic Auth to protected routes
	e.GET("/secure", basicAuthWithRateLimit(func(c echo.Context) error {
		return c.String(http.StatusOK, "authenticated")
	}))

	// Start server with TLS in production
	// e.StartTLS(":8443", "cert.pem", "key.pem")
	e.Start(":8080")
}

In production, store credentials in a secure backend with constant-time comparison, and use a distributed store like Redis for attempt tracking to handle horizontal scaling. middleBrick’s Authentication and Rate Limiting checks help verify that these protections are present and effective.