Brute Force Attack in Buffalo with Cockroachdb

A brute force attack against a Buffalo application using CockroachDB as the backend combines application-layer session handling with a distributed SQL database. The risk arises when authentication endpoints or session management logic do not enforce adequate rate limiting or account lockout, allowing an attacker to systematically guess credentials. Because Buffalo does not enforce server-side throttling by default, each login attempt reaches the CockroachDB node handling authentication queries. Repeated queries with different passwords generate measurable load and can be correlated across nodes if query logs or audit trails are enabled.

In a Buffalo app, developers typically use a models.User struct with GORM or similar ORM to query CockroachDB. If the query looks up a user by email without constant-time comparison and the endpoint is publicly accessible, an attacker can enumerate valid users and attempt password guesses. CockroachDB’s consistent transactional semantics do not prevent brute force; they simply ensure each login attempt is processed reliably, which can amplify the impact when combined with weak account policies. The database may also expose timing differences or error messages that hint at valid accounts, especially when connection retries or session writes are verbose.

Buffalo’s middleware stack can inadvertently expose authentication paths to unauthenticated scanning. Without explicit rate limiting or progressive delays, an attacker can issue many requests per second, and CockroachDB’s high concurrency can service them, leading to rapid credential guessing. Because the scan is unauthenticated and black-box, middleBrick’s Authentication and Rate Limiting checks can detect whether the login endpoint allows excessive attempts without introducing artificial delays or CAPTCHA challenges.

The interaction between Buffalo’s request lifecycle and CockroachDB’s SQL semantics also matters for observability. If authentication attempts write to a table with INSERT or UPDATE operations, CockroachDB will replicate these writes across nodes, potentially creating audit records that an attacker can probe indirectly. An insecurely configured API or debug route might expose these behaviors, and middleBrick’s Data Exposure and SSRF checks help identify unintended information leakage tied to authentication flows.

Credential stuffing or password spraying against a Buffalo+CockroachDB stack often leverages weak password policies or reused credentials. Because CockroachDB does not inherently enforce account lockout or exponential backoff, the application must implement these controls. MiddleBrick’s BFLA/Privilege Escalation and Rate Limiting checks evaluate whether the API enforces per-account or per-IP throttling and whether session tokens are invalidated after suspicious activity.

Remediation centers on enforcing server-side rate limiting, secure password handling, and minimizing information leakage in authentication paths. Below are concrete code examples for a Buffalo application using CockroachDB with GORM.

1. Rate-limited login endpoint with exponential backoff hints

Use a middleware or controller-level rate limiter to restrict attempts per email/IP. This example uses a simple in-memory token bucket via golang.org/x/time/rate. For production, consider a distributed store like Redis so limits are consistent across instances.

package actions

import (
	"context"
	"golang.org/x/time/rate"
	"net/http"
	"time"

	"github.com/gobuffalo/buffalo"
	"github.com/gobuffalo/packr/v2"
	"gorm.io/gorm"
)

var (
	loginLimiter = rate.NewLimiter(1, 5) // 1 req/sec burst=5
	db *gorm.DB
)

func LoginWithRateLimit(c buffalo.Context) error {
	// Apply rate limit before expensive DB work
	if !loginLimiter.Allow() {
		c.Response().WriteHeader(http.StatusTooManyRequests)
		return c.Render(429, r.JSON(map[string]string{"error": "too many requests"}))
	}

	email := c.Param("email")
	var user models.User
	if err := db.Where("email = ?", email).First(&user).Error; err != nil {
		// Use a constant delay to avoid timing leaks
		time.Sleep(2 * time.Second)
		c.Response().WriteHeader(http.StatusUnauthorized)
		return c.Render(401, r.JSON(map[string]string{"error": "invalid credentials"}))
	}

	// Verify password hash (e.g., bcrypt)
	if !CheckPasswordHash(c.Param("password"), user.PasswordHash) {
		// Still sleep to prevent timing analysis
		time.Sleep(2 * time.Second)
		c.Response().WriteHeader(http.StatusUnauthorized)
		return c.Render(401, r.JSON(map[string]string{"error": "invalid credentials"}))
	}

	// Reset any backoff for this user on success
	// ... issue session token
	return c.Render(200, r.JSON(map[string]string{"token": "s3cure"}))
}

2. Constant-time user lookup and password verification

Avoid branching on user existence before password check. Use a fixed hash comparison path to prevent timing attacks that CockroachDB query patterns might indirectly reveal.

package actions

import (
	"golang.org/x/crypto/bcrypt"
	"time"
)

func CheckPasswordHash(password, hash string) bool {
	// Always run bcrypt with a minimum time by using a dummy hash if necessary
	const dummyHash = "$2a$10$012345678901234567890u"
	h := hash
	if h == "" {
		h = dummyHash
	}
	// Use a constant-time comparison by always running bcrypt
	_ = bcrypt.CompareHashAndPassword([]byte(h), []byte(password))
	// Introduce a small delay to mask timing differences
	time.Sleep(250 * time.Millisecond)
	return bcrypt.CompareHashAndPassword([]byte(h), []byte(password)) == nil
}

3. Secure session handling with CockroachDB storage

Store sessions server-side in CockroachDB with randomized tokens and automatic expiration to mitigate brute force on session identifiers.

package models

import (
	"github.com/gobuffalo/pop/v6"
	"math/rand"
	"time"
)

type Session struct {
	ID        string    `db:"id"`
	UserID    int       `db:"user_id"`
	Token     string    `db:"token"`
	ExpiresAt time.Time `db:"expires_at"`
}

func CreateSession(tx *pop.Connection, userID int) (*Session, error) {
	randBytes := make([]byte, 32)
	if _, err := rand.Read(randBytes); err != nil {
		return nil, err
	}
	session := &Session{
		ID:        uuid.NewString(),
		UserID:    userID,
		Token:     hex.EncodeToString(randBytes),
		ExpiresAt: time.Now().Add(24 * time.Hour),
	}
	if err := tx.Create(session); err != nil {
		return nil, err
	}
	return session, nil
}

4. Middleware to enforce global request limits

Add a Buffalo middleware that tracks request counts per IP and introduces incremental delays when thresholds are approached, helping to smooth traffic toward CockroachDB without dropping connections abruptly.

package middleware

import (
	"github.com/gobuffalo/buffalo"
	"github.com/gobuffalo/buffalo/middleware"
	"net/http"
	"sync"
)

type RateTracker struct {
	mu      sync.Mutex
	entries map[string]int
}

func (rt *RateTracker) Inc(ip string) int {
	rt.mu.Lock()
	defer rt.mu.Unlock()
	rt.entries[ip]++
	return rt.entries[ip]
}

func RateLimit(next buffalo.Handler) buffalo.Handler {
	rt := &RateTracker{entries: make(map[string]int)}
	return func(c buffalo.Context) error {
		ip := c.Request().Header.Get("X-Forwarded-For")
		if ip == "" {
			ip = c.Request().RemoteAddr
		}
		count := rt.Inc(ip)
		if count > 100 {
			c.Response().WriteHeader(http.StatusTooManyRequests)
			return nil
		}
		// Optional: add incremental delay
		if count > 50 {
			time.Sleep(time.Duration(count-50) * 10 * time.Millisecond)
		}
		return next(c)
	}
}

These changes ensure brute force attempts are met with server-side constraints, reducing the effectiveness of high-volume attacks against the Buffalo+CockroachDB combination. middleBrick’s checks can validate that these controls are present and that the authentication path does not leak information via error handling or timing.