Password Spraying in Echo Go with Hmac Signatures

Password spraying is an authentication abuse technique where an attacker uses a small set of commonly used passwords against many accounts. In Echo Go applications that rely on Hmac Signatures for request authentication, a subtle design mismatch can make password spraying viable even when per-request signatures are used.

Consider an API where the client computes an HMAC-SHA256 over a canonical string that includes a user identifier (e.g., userId) and a timestamp, then sends the signature in a header such as X-API-Signature. If the server’s login or token endpoint does not enforce rate limiting or account lockout and accepts a generic 401 response for both “invalid signature” and “unknown user,” an attacker can iterate over a list of candidate passwords for a known user ID without triggering distinct failure modes. Because the Hmac Signature itself does not reveal whether the user exists, the attacker can probe the endpoint with valid-format signatures derived from guessed passwords and observe only generic HTTP 401 responses, enabling offline password spraying.

Echo Go middleware that validates Hmac Signatures typically parses headers, reconstructs the signing string, and compares signatures in constant time. However, if authorization decisions (e.g., “is this user allowed?”) are evaluated after signature verification and the application returns the same generic error for bad signatures and for valid signatures belonging to a non-existent or locked account, the distinction between a bad signature and a bad password collapses. This uniform response removes the signal that would otherwise deter bulk attempts. Furthermore, if the canonical string includes a user-supplied userId that is not bound to a throttling policy, an attacker can cycle through passwords for a single user or iterate across many user IDs while keeping each request individually valid in format, bypassing naive rate limiters that only count requests per endpoint.

Real-world analogs include findings mapped to OWASP API Top 10 2023:7 — Authentication and Security Misconfiguration — where weak or inconsistent failure modes enable credential-based attacks. Public examples such as CVE-2022-27065 illustrate how uniform error handling and lack of per-account rate limiting can turn Hmac-based auth into a vector for password spraying. middleBrick scans detect these behavioral patterns during black-box testing, noting whether authentication endpoints provide distinct responses or enforce per-user throttling, and surface findings with severity and remediation guidance in the scan report.

To validate the issue, you can use the CLI tool to scan an endpoint: middlebrick scan https://api.example.com. The dashboard will show an Authentication risk score and related findings if responses do not differentiate user existence or enforce granular rate limits. For applications using the Pro plan, continuous monitoring can alert you when changes to the auth flow weaken protections, while the GitHub Action can fail a build if the risk score drops below your configured threshold.

Remediation focuses on making the server’s behavior independent of password validity by standardizing responses and enforcing per-user throttling. Always return the same HTTP status and timing for signature verification failures, unknown users, and locked accounts. Implement rate limiting keyed by user ID or API key, not just by endpoint, and ensure that Hmac verification does not leak information about which part of the canonical string is incorrect.

Example secure Echo Go handler using Hmac Signatures:

// canonicalForm: userId + timestamp + nonce
func computeSignature(secret, userId string, ts int64, nonce string) string {
    h := hmac.New(sha256.New, []byte(secret))
    h.Write([]byte(userId + strconv.FormatInt(ts, 10) + nonce))
    return hex.EncodeToString(h.Sum(nil))
}

func verifySignature(secret, userId string, ts int64, nonce, receivedSig string) bool {
    expected := computeSignature(secret, userId, ts, nonce)
    return subtle.ConstantTimeCompare([]byte(expected), []byte(receivedSig)) == 1
}

func AuthHandler(c echo.Context) error {
    userId := c.Request().Header.Get("X-User-ID")
    sig := c.Request().Header.Get("X-API-Signature")
    tsStr := c.Request().Header.Get("X-Timestamp")
    nonce := c.Request().Header.Get("X-Nonce")

    ts, err := strconv.ParseInt(tsStr, 10, 64)
    if err != nil {
        return echo.NewHTTPError(http.StatusUnauthorized, "invalid request")
    }
    // Reject old timestamps to prevent replay
    if time.Since(time.Unix(ts, 0)) > 5*time.Minute {
        return echo.NewHTTPError(http.StatusUnauthorized, "invalid request")
    }

    // Placeholder: fetch user secret from secure store; if missing, use a dummy secret to avoid timing leaks
    userSecret, ok := userSecretStore[userId]
    if !ok {
        userSecret = dummySecret
    }

    if !verifySignature(userSecret, userId, ts, nonce, sig) {
        // Always return the same generic error and status
        return echo.NewHTTPError(http.StatusUnauthorized, "invalid request")
    }

    // Proceed only if signature is valid and user exists and is not locked
    if !userExists(userId) || isLocked(userId) {
        return echo.NewHTTPError(http.StatusForbidden, "access denied")
    }

    return c.JSON(http.StatusOK, map[string]string{"status": "ok"})
}

On the infrastructure side, pair this with per-user rate limiting (e.g., using a token bucket keyed by userId) and ensure that authentication failure logging does not reveal whether a signature was structurally valid. middleBrick’s scans can validate that your deployment includes these controls; the MCP server lets you run checks directly from IDEs, and the GitHub Action can gate merges if the authentication risk remains above your chosen level.