Brute Force in Buffalo

Brute force attacks are a common threat to web applications, and Buffalo-based APIs are no exception. These attacks involve an adversary repeatedly sending requests to an endpoint, typically a login or password reset endpoint, in an attempt to guess valid credentials or exploit other vulnerabilities. Because Buffalo, as a Go web framework, does not include built-in rate limiting, developers must explicitly add protection. Without it, an attacker can automate thousands of attempts using tools like Hydra or Burp Suite, potentially compromising user accounts or causing a denial-of-service by exhausting server resources.

Consider a typical Buffalo login handler. The following code processes a POST request to /login and checks credentials against a database:

func (v *HomeHandler) Login(c buffalo.Context) error {
    type LoginRequest struct {
        Username string `json:"username"`
        Password string `json:"password"`
    }
    var req LoginRequest
    if err := c.Bind(&req); err != nil {
        return c.Error(400, err)
    }
    // Authenticate user (simplified)
    user, err := models.FindUserByUsername(req.Username)
    if err != nil || user.Password != hash(req.Password) {
        return c.Error(401, errors.New("invalid credentials"))
    }
    // Set session, return success...
    return c.Render(200, r.JSON(map[string]string{"status": "ok"}))
}

This handler performs no rate limiting. An attacker can send an unlimited number of requests with different passwords, each receiving a generic "invalid credentials" response. This not only risks account takeover but also may leak information through timing differences or error messages. Moreover, the unbounded requests can consume database resources, affecting other users.

Buffalo applications often expose multiple endpoints that are susceptible to brute force: authentication endpoints (login, register, password reset), API keys, or even business logic endpoints like coupon validation. The attack pattern is consistent: rapid, repeated requests from a single IP or using rotating IPs to bypass naive IP-based blocks. Since Buffalo does not enforce any default limits, every request reaches the application logic, making brute force feasible unless explicitly mitigated.

Detecting missing rate limiting in a Buffalo API is straightforward with middleBrick. middleBrick's security scans include a dedicated rate limiting check among its 12 parallel tests. The scanner performs a black-box assessment: it sends a burst of requests to each discovered endpoint (including those derived from OpenAPI specs) and observes the responses. Specifically, it looks for HTTP 429 Too Many Requests status codes or other indicators like X-RateLimit-* headers that signal the presence of a rate limiter. If the scanner can send, for example, 20 requests within a few seconds without any throttling response, it flags the endpoint as lacking rate limiting.

For a Buffalo application, middleBrick will test all endpoints, but it pays special attention to those that typically handle authentication or sensitive operations. The findings are presented in the report with a severity rating (high or critical for brute-force prone endpoints) and actionable remediation guidance. The report also maps the issue to OWASP API Top 10 (API4:2023 - Unrestricted Resource Consumption) and compliance frameworks like PCI-DSS and HIPAA, which require protection against brute force attacks.

To scan your Buffalo API, simply use the middleBrick web dashboard or the CLI tool. For example:

middlebrick scan https://your-buffalo-api.com

The scan completes in 5–15 seconds and returns a security score (A–F) along with a per-category breakdown. The "Rate Limiting" category will show whether your endpoints are protected. If not, you'll see a prioritized finding with details like the endpoint URL, number of requests sent, and the absence of any throttling response.

It's important to note that middleBrick does not require any credentials or configuration; it tests the unauthenticated attack surface exactly as an external attacker would. This makes it ideal for continuous monitoring of Buffalo APIs in CI/CD pipelines via the GitHub Action or the MCP Server for IDE integration.

Remediating brute force vulnerabilities in Buffalo applications involves implementing rate limiting at the application layer. Since Buffalo does not provide built-in rate limiting, you must add middleware that limits the number of requests a client can make within a given time window. The recommended approach is to use Go's standard golang.org/x/time/rate package, which implements a token bucket limiter. This allows fine-grained control over request rates and bursts.

Below is an example of a Buffalo middleware that applies per-IP rate limiting. It creates a limiter with a rate of 10 requests per second and a burst of 20. The middleware is applied to specific routes (e.g., all /auth/* endpoints).

package middleware

import (
    "errors"
    "net/http"
    "sync"
    "time"

    "github.com/gobuffalo/buffalo"
    "golang.org/x/time/rate"
)

type RateLimiter struct {
    limiters sync.Map
    rate     rate.Limit
    burst    int
}

func NewRateLimiter(r rate.Limit, b int) *RateLimiter {
    return &RateLimiter{
        rate: r,
        burst: b,
    }
}

func (rl *RateLimiter) Middleware(next buffalo.Handler) buffalo.Handler {
    return func(c buffalo.Context) error {
        ip := c.Request().RemoteAddr
        limiter, _ := rl.limiters.LoadOrStore(ip, rate.NewLimiter(rl.rate, rl.burst))
        if !limiter.(*rate.Limiter).Allow() {
            return c.Error(429, errors.New("too many requests"))
        }
        return next(c)
    }
}

You would then register this middleware in your Buffalo application's route groups. Buffalo's grouping feature allows you to apply middleware to a set of routes easily. For example, to protect all authentication endpoints:

func App() *buffalo.App {
    app := buffalo.New(appOptions)
    // ... other middleware

    authLimiter := middleware.NewRateLimiter(10, 20) // 10 rps, burst 20

    app.Group("/auth", func(g *buffalo.Group) {
        g.Use(authLimiter.Middleware)
        g.POST("/login", HomeHandler.Login)
        g.POST("/register", HomeHandler.Register)
        // ... other auth endpoints
    })

    // ... other routes
    return app
}

This example uses a simple per-IP limiter. For more sophisticated scenarios (e.g., per-user after authentication), you would key the limiter by user identifier. Also, consider using a distributed store like Redis if your Buffalo app runs on multiple servers, so rate limits are shared across instances. There are Buffalo middleware packages that integrate with Redis, but the core idea remains the same.

After implementing the middleware, rescan your API with middleBrick to verify that the rate limiting is detected. The scanner should now see 429 responses after exceeding the threshold, and the Rate Limiting category score will improve. Remember to tune the rate values to balance security and usability: too strict may block legitimate users, too lenient may not prevent attacks.

Additionally, complement application-level rate limiting with infrastructure-level controls (e.g., cloud load balancer rules) for defense in depth. But the Buffalo-specific fix is to ensure every sensitive endpoint has proper rate limiting via middleware.