Regex Dos in Echo Go with Basic Auth

A Regex DoS (ReDoS) occurs when a regular expression exhibits catastrophic backtracking on crafted input, causing CPU consumption to spike and making the service unresponsive. In Echo Go, combining Basic Auth middleware with poorly constructed regex patterns in route or validation handlers can create a severe availability risk. Basic Auth requires the server to parse the Authorization header, extract the base64-encoded credentials, and validate them against a backend source. If the application then applies additional regex checks—such as validating usernames, passwords, or tokens—those patterns become an active attack surface.

Consider an Echo Go handler that uses a custom middleware to enforce a complex password policy via regex after extracting Basic Auth credentials. An attacker can send many requests with specially crafted Authorization headers that pass the initial base64 decode but trigger exponential backtracking in the downstream regex. Because Echo Go processes requests concurrently, a small number of malicious requests can consume disproportionate CPU, degrading performance for all users. This is especially dangerous when the regex validates something derived from the credentials (for example, a token or a scope string) and uses nested quantifiers or overlapping character classes without atomic grouping or bounds.

Another angle is OpenAPI/Swagger spec analysis: if the spec defines regex patterns for string formats (e.g., pattern in JSON Schema) and those patterns are naively translated into Go regexp.Regexp objects, the generated expressions may inherit the same backtracking pitfalls. During a black-box scan, middleBrick tests unauthenticated attack surfaces and can detect indicators of expensive regex behavior by probing endpoints that accept credentials in headers and validating input with pattern-based rules. The presence of Basic Auth increases the likelihood that regex logic will handle sensitive strings, so inefficient patterns amplify the impact. Real-world CVEs in other frameworks have shown how a single vulnerable regex in authentication flows can lead to denial of service, and similar risks apply when regex validation is layered on top of Basic Auth in Go services.

To identify this during a scan, middleBrick runs multiple security checks in parallel, including Input Validation and Authentication. It inspects OpenAPI specs for regex patterns, observes runtime behavior with crafted payloads, and flags routes where authentication headers interact with pattern checks. The goal of the scan is not to fix but to highlight high-risk combinations and provide remediation guidance so developers can adjust patterns or move validation out of hot paths.

Remediation focuses on simplifying or removing expensive regex in authentication paths and ensuring that Basic Auth validation is efficient and side-channel resistant. Avoid using complex, nested quantifiers in patterns applied to credentials; prefer straightforward length and character-set checks that do not rely on backtracking-heavy constructs. When regex is necessary, compile patterns once at initialization and reuse the compiled object. Use Go’s regexp package safely by avoiding FindAllString or repeated matches on untrusted input where backtracking can grow exponentially.

Below are concrete, working examples for securing Basic Auth in Echo Go.

Example 1: Simple, safe Basic Auth validation without costly regex

package main

import (
	"encoding/base64"
	"net/http"
	"strings"

	"github.com/labstack/echo/v4"
)

func basicAuthMiddleware(next echo.HandlerFunc) echo.HandlerFunc {
	return func(c echo.Context) error {
		auth := c.Request().Header.Get("Authorization")
		if auth == "" || !strings.HasPrefix(auth, "Basic ") {
			return c.String(http.StatusUnauthorized, "Authorization header missing")
		}
		payload, err := base64.StdEncoding.DecodeString(auth[7:])
		if err != nil {
			return c.String(http.StatusUnauthorized, "Invalid authorization header")
		}
		creds := strings.SplitN(string(payload), ":", 2)
		if len(creds) != 2 {
			return c.String(http.StatusUnauthorized, "Invalid credentials format")
		}
		username, password := creds[0], creds[1]
		// Replace with constant-time comparison and backend validation
		if !validateUser(username, password) {
			return c.String(http.StatusUnauthorized, "Invalid credentials")
		}
		return next(c)
	}
}

func validateUser(username, password string) bool {
	// Use efficient checks; avoid regex on secrets
	if len(username) < 1 || len(username) > 64 {
		return false
	}
	// Example character checks without backtracking-prone patterns
	for _, ch := range username {
		if !(ch >= 'a' && ch <= 'z' || ch >= 'A' && ch <= 'Z' || ch >= '0' && ch <= '9' || ch == '_' || ch == '-') {
			return false
		}
	}
	// Password validation should be handled server-side with secure storage
	return true
}

Example 2: If regex is required, compile once and avoid dangerous patterns

package main

import (
	"regexp"
	"sync"
)

var (
	usernameRegex *regexp.Regexp
	regexOnce     sync.Once
)

func initUsernameRegex() {
	// Prefer bounded patterns; avoid nested quantifiers and overlapping classes
	// This pattern allows alphanumeric and underscore, length 1–64
	usernameRegex = regexp.MustCompile(`\A[a-zA-Z0-9_]{1,64}\z`)
}

func safeUsernameCheck(username string) bool {
	regexOnce.Do(initUsernameRegex)
	return usernameRegex.MatchString(username)
}

By applying these patterns in Echo Go, you reduce the risk of ReDoS while preserving the intended security checks. middleBrick can support this process by scanning endpoints for regex usage in validation logic and flagging patterns that are likely to exhibit catastrophic backtracking.