Password Spraying in Buffalo

Password spraying attacks target authentication endpoints by trying a small set of common passwords across many usernames, avoiding account lockout thresholds. In Buffalo applications, this often manifests in login handlers that lack per-IP or per-username rate limiting on credential validation. For example, a typical Buffalo resource.Handler for login might directly call models.Authenticate without checking attempt frequency, enabling attackers to spray passwords like 'Winter2024!' or 'Spring2024!' across harvested user lists.

Consider this vulnerable pattern in actions/auth.go:

func LoginHandler(c buffalo.Context) error {
    u := &models.User{}
    if err := c.Bind(u); err != nil {
        return c.Error(400, err)
    }
    // No rate limiting here — vulnerable to spraying
    if err := models.DB.Where("email = ?", u.Email).First(u); err != nil {
        // Generic error prevents user enumeration but doesn't stop spraying
        return c.Error(401, errors.New("invalid credentials"))
    }
    if !u.ValidatePassword(u.Password) {
        return c.Error(401, errors.New("invalid credentials"))
    }
    // ... session creation
    return c.Redirect(302, "/")
}

Attackers exploit this by sending POST requests to /users/sign_in with varying passwords but the same or cycling usernames. Since Buffalo’s default generators don’t include authentication throttling, the endpoint remains exposed. middleBrick detects this under the "Authentication" and "Rate Limiting" checks by observing successful login attempts after multiple failures from the same IP without delay or CAPTCHA, flagging missing mitigations as high-risk findings.

Identifying password spraying risk in Buffalo requires checking for absent or ineffective rate limiting on authentication routes. middleBrick performs unauthenticated black-box scans that simulate spraying behavior: it sends sequences of login attempts with common passwords across enumerated or guessed usernames (e.g., from /users exposure or predictable patterns like user{1..100}@example.com). If the API responds with 200 OK or 302 Found after a burst of failed attempts without enforcing delays, lockouts, or challenges, it triggers a finding.

For instance, middleBrick might observe:

• 10 login attempts from one IP in 8 seconds targeting different emails
• All return 401 Unauthorized with identical response times
• No 429 Too Many Requests, no increasing delay, no account lock
• Eventual success on attempt #7 with password 'Summer2024!'

This pattern indicates missing authentication throttling. middleBrick’s scan also checks for username enumeration via response timing or message differences — though Buffalo’s generic error messages often prevent this, the spraying itself remains viable. The finding appears in the report under "Authentication" with severity "High", noting: "Authentication endpoint allows unlimited login attempts; vulnerable to password spraying attacks." Remediation guidance references implementing rate limiting via Buffalo middleware.

To test locally, you can use the middleBrick CLI:

middlebrick scan https://api.example.com --timeout 15

The output will include a JSON section like:

{
  "check": "Rate Limiting",
  "status": "fail",
  "details": "No rate limiting detected on POST /users/sign_in. Observed 15 login attempts in 12 seconds without delay or lockout."
}

Fixing password spraying vulnerabilities in Buffalo involves adding rate limiting to authentication handlers using the framework’s middleware system. Buffalo supports custom middleware that can track request counts by IP or username and enforce delays or blocks after thresholds.

Implement a rate-limiting middleware in actions/ratelimit.go:

package actions

import (
    "github.com/gobuffalo/buffalo"
    "github.com/gobuffalo/buffalo/middleware"
    "golang.org/x/time/rate"
    "sync"
    "time"
)

var (
    limiterMap = make(map[string]*rate.Limiter)
    mutex      sync.Mutex
    // 5 attempts per minute per IP
    limiter    = rate.NewLimiter(5.0/60.0, 5)
)

func RateLimiter(next buffalo.Handler) buffalo.Handler {
    return func(c buffalo.Context) error {
        ip := c.Request().RemoteAddr
        mutex.Lock()
        l, exists := limiterMap[ip]
        if !exists {
            l = rate.NewLimiter(5.0/60.0, 5)
            limiterMap[ip] = l
        }
        mutex.Unlock()
        if !l.Allow() {
            return c.Error(429, buffalo.NewError(429, fmt.Errorf("too many login attempts")))
        }
        return next(c)
    }
}

Then apply it to your login route in actions/app.go:

func App() *buffalo.App {
    app := buffalo.New(buffalo.Options{})
    // ... other middleware
    app.POST("/users/sign_in", AuthController.Login, RateLimiter)
    return app
}

For more granular control, limit by username or email instead of IP to prevent spraying across IPs targeting one account. Store attempt counts in Redis (using github.com/gomodule/redigo/redis) for distributed systems:

func LoginHandler(c buffalo.Context) error {
    u := &models.User{}
    if err := c.Bind(u); err != nil {
        return c.Error(400, err)
    }
    key := fmt.Sprintf("login_attempts:%s", u.Email)
    count, err := redis.Int(c.Value("redis_conn").Do("INCR", key))
    if err != nil {
        return c.Error(500, err)
    }
    if count > 5 {
        // Lock account or require CAPTCHA after 5 fails
        return c.Error(429, errors.New("account temporarily locked"))
    }
    defer c.Value("redis_conn").Do("EXPIRE", key, 60) // reset after 60s
    // ... rest of login logic
}

After deploying fixes, rescan with middleBrick to confirm the "Rate Limiting" check passes. The CLI command middlebrick scan https://api.example.com will now show improved scores and no failing findings under authentication throttling.