Password Spraying in Buffalo with Dynamodb

Password spraying is an authentication-layer attack where a small number of common passwords are tried against many accounts to avoid account lockouts. When an API built on Buffalo uses Amazon DynamoDB as its user store without adequate protections, the combination can expose endpoints to efficient, low-noise credential validation.

In Buffalo, typical login flows involve a controller action that queries DynamoDB for a user by email or username and then verifies the provided password. If the application does not enforce per-user rate limits or consistent timing behavior, an attacker can send many authentication requests using common passwords (e.g., Password1, Welcome123) across a list of known usernames or emails. Because DynamoDB GetItem or Query operations can return existence timing differences and HTTP 401/403 responses are often distinguishable from successful authentication, attackers can infer whether a username exists and whether the password is correct.

DynamoDB itself does not introduce the vulnerability, but its characteristics can amplify risk in Buffalo apps:

• Low-latency responses allow timing-based username enumeration when error handling or response codes differ between valid-user and invalid-user paths.
• Lack of server-side throttling means an attacker can perform thousands of login attempts per minute from a single source unless the application or an external layer enforces rate limits.
• Use of public endpoints or misconfigured IAM policies can expose user data, enabling attackers to build targeted username lists for spraying.

For example, consider a Buffalo login handler that performs a DynamoDB GetItem and then conditionally verifies the password. If the handler returns a generic error for both missing users and wrong passwords but varies in response time or HTTP status, an attacker can iterate over usernames with a common password and observe which accounts accept the password. This aligns with the OWASP API Top 10 category Broken Authentication and can lead to account compromise at scale.

To detect this pattern, middleBrick runs 12 security checks in parallel, including Authentication, Input Validation, Rate Limiting, and Unsafe Consumption checks. These checks analyze unauthenticated attack surfaces and can surface indicators such as inconsistent error responses, missing account lockout mechanisms, or endpoints that accept high request volumes without throttling.

To mitigate password spraying in Buffalo when using DynamoDB, implement defensive controls at the application and infrastructure levels. Focus on constant-time validation, robust rate limiting, and careful error handling to eliminate observable differences between valid and invalid requests.

Constant-time user existence check

Ensure your login flow does not leak user existence through timing or status differences. Use a dummy record or a consistent flow for missing users.

// handlers/sessions_controller.go
package handlers

import (
	"context"
	"time"

	"github.com/gobuffalo/buffalo"
	"github.com/gobuffalo/packr/v2"
	"github.com/aws/aws-sdk-go/aws"
	"github.com/aws/aws-sdk-go/aws/session"
	"github.com/aws/aws-sdk-go/service/dynamodb"
	"github.com/aws/aws-sdk-go/service/dynamodb/dynamodbattribute"
)

var dynamoSvc *dynamodb.DynamoDB

func init() {
	sess := session.Must(session.NewSession())
	dynamoSvc = dynamodb.New(sess)
}

// Login performs a constant-time check by always running a verification step.
func Login(c buffalo.Context) error {
	email := c.Params().Get("email")
	password := c.Params().Get("password")

	// Step 1: Fetch user (or a dummy item) to keep timing consistent.
	const dummyEmail = "dummy@example.invalid"
	targetEmail := email
	if email == "" {
		targetEmail = dummyEmail
	}

	out, err := dynamoSvc.GetItem(&dynamodb.GetItemInput{
		TableName: aws.String("users"),
		Key: map[string]*dynamodb.AttributeValue{
			"email": {S: aws.String(targetEmail)},
		},
	})
	if err != nil {
		// Log the error but return a generic response to avoid leaking info.
		c.Response().WriteHeader(401)
		return c.Render(401, r.JSON(map[string]string{"error": "Invalid credentials"}))
	}

	var user map[string]interface{}
	if out.Item != nil {
		err = dynamodbattribute.UnmarshalMap(out.Item, &user)
		if err != nil {
			c.Response().WriteHeader(401)
			return c.Render(401, r.JSON(map[string]string{"error": "Invalid credentials"}))
		}
	}

	// Step 2: Always perform a password hash check with a dummy hash if user not found.
	expectedHash := "{dummy hash}"
	if user != nil {
		expectedHash = user["password_hash"].(string)
	}

	// Use a constant-time comparison function to prevent timing attacks.
	if subtleCompare(expectedHash, password) {
		c.Session().Set("user_email", email)
		c.Response().WriteHeader(200)
		return c.Render(200, r.JSON(map[string]string{"ok": "true"}))
	}

	c.Response().WriteHeader(401)
	return c.Render(401, r.JSON(map[string]string{"error": "Invalid credentials"}))
}

// subtleCompare is a placeholder for a constant-time comparison.
func subtleCompare(a, b string) bool {
	if len(a) != len(b) {
		return false
	}
	var equal byte
	for i := 0; i < len(a); i++ {
		equal |= a[i] ^ b[i]
	}
	return equal == 0
}

Rate limiting and account lockout

Introduce rate limiting at the HTTP handler or gateway level to restrict the number of authentication attempts per source IP or user identifier within a time window.

// middleware/rate_limit.go
package middleware

import (
	"net/http"
	"time"

	"github.com/buffalo/buffalo"
	"github.com/didip/tollbooth"
	"github.com/didip/tollbooth/limiter"
)

func RateLimiter(next buffalo.Handler) buffalo.Handler {
	return func(c buffalo.Context) error {
		lmt := tollbooth.NewLimiter(5, &limiter.ExpirableOptions{
			DefaultExpirationTTL: time.Minute * 15,
		})
		lmt.SetIPLookups([]string{"RemoteAddr"})
		lmt.AddMiddleware(limiter.Middleware)
		return lmt.Middleware(next)(c)
	}
}

Apply this middleware to your login route in actions/app.go:

// actions/app.go
package actions

import (
	"middleware"
	// other imports
)

var App *buffalo.App

func init() {
	App = buffalo.New(buffalo.Options{}) 
	App.GET("/login", LoginHandler)
	App.POST("/login", RateLimiter(LoginHandler))
}

Consistent error messages and status codes

Return identical HTTP status codes and generic messages for both missing users and incorrect passwords to remove signal leakage.

// handlers/sessions_controller.go (error path)
c.Response().WriteHeader(401)
return c.Render(401, r.JSON(map[string]string{"error": "Invalid credentials"}))

Consider adding CAPTCHA challenges after repeated failures or integrating an external rate-limiting service to further reduce spray effectiveness.

middleBrick’s checks align with these practices by flagging inconsistent error handling and missing rate limiting. If you use the Pro plan, you can enable continuous monitoring so that future regressions in authentication hardening are surfaced early via GitHub Action or Slack alerts.