Token Leakage in Buffalo
How Token Leakage Manifests in Buffalo
Token leakage in Buffalo applications typically occurs through several specific code patterns that expose sensitive authentication credentials to unintended parties. The most common manifestation appears in middleware chains where authentication tokens are passed between handlers without proper isolation.
Consider a typical Buffalo middleware setup where a token is extracted from a request header, processed, and then inadvertently logged or exposed:
func AuthMiddleware(next buffalo.Handler) buffalo.Handler {
return func(c buffalo.Context) error {
token := c.Request().Header.Get("Authorization")
// Token is now available to all downstream handlers
c.Set("authToken", token)
// Critical vulnerability: logging the raw token
log.Printf("Processing request with token: %s", token)
return next(c)
}
}
This pattern creates multiple attack vectors. First, the token is logged in plaintext, creating a persistent record that could be accessed by anyone with log access. Second, the token is stored in the context and becomes accessible to any handler in the chain, including those that might not need it.
Another Buffalo-specific pattern involves improper use of the Bind method with struct tags that inadvertently expose token information:
type UserRequest struct {
Token string `json:"token" db:"-"`
// Other fields
}
func (u *UserRequest) Bind(c buffalo.Context) error {
// Bind will populate Token field from request body
return c.Bind(u)
}
When this struct is used in handlers, the token field becomes part of the request payload, potentially appearing in error messages, logs, or debug responses. Buffalo's automatic binding and validation can inadvertently expose these sensitive fields.
Session management in Buffalo also presents token leakage risks. The default session store may serialize sensitive data without proper encryption:
func MyHandler(c buffalo.Context) error {
// Storing token in session without encryption
session := c.Session()
session.Set("authToken", c.Request().Header.Get("Authorization"))
session.Save()
return c.Render(200, r.JSON(map[string]string{"status": "ok"}))
}
If the session store is compromised or improperly configured, tokens stored this way become accessible to attackers. Buffalo's default cookie store, while convenient, requires explicit encryption configuration to prevent token exposure.
Buffalo-Specific Detection
Detecting token leakage in Buffalo applications requires both static code analysis and runtime scanning. Static analysis focuses on identifying code patterns that expose tokens, while runtime scanning with middleBrick can detect actual token exposure in deployed APIs.
Static detection using Go's AST package can identify dangerous patterns:
package main
import (
"go/ast"
"go/parser"
"go/token"
"log"
"os"
)
func detectTokenLeakage(filename string) {
fset := token.NewFileSet()
node, err := parser.ParseFile(fset, filename, nil, parser.ParseComments)
if err != nil {
log.Fatal(err)
}
ast.Inspect(node, func(n ast.Node) bool {
switch x := n.(type) {
case *ast.CallExpr:
// Detect log.Printf with token variable
if isLogCall(x) && containsToken(x.Args) {
log.Printf("Potential token leakage in %s:%d", filename, fset.Position(n.Pos()).Line)
}
// Detect session.Set with token
if isSessionSetCall(x) && containsToken(x.Args) {
log.Printf("Token stored in session at %s:%d", filename, fset.Position(n.Pos()).Line)
}
}
return true
})
}
func isLogCall(expr *ast.CallExpr) bool {
if fun, ok := expr.Fun.(*ast.SelectorExpr); ok {
if fmt, ok := fun.X.(*ast.Ident); ok && fmt.Name == "log" && fun.Sel.Name == "Printf" {
return true
}
}
return false
}
func containsToken(args []ast.Expr) bool {
for _, arg := range args {
if lit, ok := arg.(*ast.BasicLit); ok && lit.Kind == token.STRING {
if containsSensitivePatterns(lit.Value) {
return true
}
}
}
return false
}
Runtime detection with middleBrick provides comprehensive scanning of deployed Buffalo APIs. The CLI tool can scan your API endpoints for token leakage patterns:
# Install middleBrick CLI
npm install -g middlebrick
# Scan your Buffalo API
middlebrick scan https://your-buffalo-api.com --output json
# Scan with specific focus on authentication endpoints
middlebrick scan https://your-buffalo-api.com/auth --category authentication
middleBrick's black-box scanning tests the unauthenticated attack surface, looking for exposed tokens in responses, headers, and error messages. The scanner checks for common token formats (JWT, OAuth2, API keys) and reports any instances where these credentials appear in places they shouldn't.
For continuous monitoring, the GitHub Action integration can automatically scan your Buffalo API in CI/CD pipelines:
- name: Run middleBrick Security Scan
uses: middlebrick/middlebrick-action@v1
with:
api_url: ${{ secrets.API_URL }}
fail_below_score: B
categories: authentication, bolad, data-exposure
This setup ensures that any token leakage introduced during development is caught before deployment. The action can fail builds if authentication-related issues are detected, preventing insecure code from reaching production.
Buffalo-Specific Remediation
Remediating token leakage in Buffalo requires a multi-layered approach using Buffalo's built-in security features and Go best practices. The first layer is proper middleware design that isolates token handling:
func SecureAuthMiddleware(next buffalo.Handler) buffalo.Handler {
return func(c buffalo.Context) error {
// Extract token without storing in context
token := c.Request().Header.Get("Authorization")
// Validate token format without logging
if !isValidTokenFormat(token) {
return c.Error(401, errors.New("invalid token format"))
}
// Use token for authentication without exposure
claims, err := validateJWTToken(token)
if err != nil {
return c.Error(401, errors.New("invalid token"))
}
// Store only necessary claims, not raw token
c.Set("userID", claims.UserID)
return next(c)
}
}
func isValidTokenFormat(token string) bool {
// Check JWT format without logging contents
parts := strings.Split(token, ".")
return len(parts) == 3 && len(parts[2]) > 0
}
This pattern ensures the raw token never appears in logs or is accessible to downstream handlers beyond what's necessary for authentication.
For struct binding, use explicit field tagging and avoid automatic binding of sensitive fields:
type SecureUserRequest struct {
UserID string `json:"userID" db:"user_id"`
// Other non-sensitive fields
// No token field - handle authentication separately
}
func (u *SecureUserRequest) Bind(c buffalo.Context) error {
// Only bind non-sensitive fields
return c.BindWith(u, binding.JSON)
}
func AuthenticatedHandler(c buffalo.Context) error {
// Handle authentication separately
token := c.Request().Header.Get("Authorization")
claims, err := validateJWTToken(token)
if err != nil {
return c.Error(401, errors.New("unauthorized"))
}
// Create request with only necessary data
req := SecureUserRequest{UserID: claims.UserID}
if err := c.Bind(&req); err != nil {
return err
}
// Process request
return c.Render(200, r.JSON(map[string]string{"status": "ok"}))
}
Session management should use encrypted storage and avoid storing raw tokens:
func init() {
// Configure encrypted session store
sessionconf := session.Options{
Encrypt: true,
HashKey: []byte("32-byte-hash-key-here"),
BlockKey: []byte("32-byte-block-key-here"),
}
app.SessionStore = sessions.NewCookieStore(
[]byte("secret-session-key"),
[]byte("another-secret"),
)
app.SessionStore.(*sessions.CookieStore).Options = &sessionconf
}
func SecureSessionHandler(c buffalo.Context) error {
session := c.Session()
// Store only user ID, not token
session.Set("userID", c.Value("userID"))
session.Save()
return c.Render(200, r.JSON(map[string]string{"status": "session saved"}))
}
Buffalo's error handling should be configured to avoid leaking token information in error responses:
func init() {
app.ErrorHandler = func(status int, err error, c buffalo.Context) error {
// Log error without sensitive data
log.Printf("Error %d: %v", status, err)
// Return generic error message
return c.Render(status, r.JSON(map[string]string{
"error": http.StatusText(status),
}))
}
}
For comprehensive security, integrate middleBrick's continuous monitoring to catch any new token leakage patterns:
# Add to GitHub Actions for continuous scanning
- name: middleBrick Security Scan
uses: middlebrick/middlebrick-action@v1
with:
api_url: ${{ secrets.API_URL }}
scan_frequency: hourly
alert_channels: slack
categories: authentication, data-exposure
This combination of secure coding practices and automated scanning ensures that token leakage is prevented at both the development and deployment stages.