Stack Overflow in Gin with Hmac Signatures

When an API built with the Go web framework Gin uses Hmac Signatures for request authentication, a classic Stack Overflow pattern can intersect with signature verification in a risky way. If user-controlled input such as a query parameter, header, or JSON field is directly reflected into error messages, logs, or HTTP redirects, an attacker can provide extremely large or deeply nested data designed to trigger a stack overflow during parsing or signature computation. Because Hmac Signatures rely on deterministic input to produce a consistent signature, an oversized payload can cause the runtime to consume excessive stack memory during hashing or JSON unmarshaling before the signature is even checked, leading to process instability or crashes.

In Gin, this often manifests when developers bind request data into structs using c.ShouldBind (JSON/Query/Header) and then immediately compute an HMAC over a subset of the bound fields without validating size or structure first. For example, an attacker might send a JSON body with a deeply nested object or a very large string in a field that is included in the signed payload. The Gin application may attempt to process this data to derive the signed string, causing high memory usage or stack exhaustion before the signature verification step, effectively bypassing authentication through resource exhaustion rather than cryptographic failure.

Another specific vector involves query parameters or URL paths that are concatenated into the signed string. If an attacker controls a parameter that is reflected in a redirect or error page, and that parameter is used in the Hmac computation, they can craft input that leads to excessive allocations or deep recursion in helper libraries used for canonicalization. Because the scan tests for BOLA/IDOR and Input Validation alongside authentication checks, it can identify cases where large or maliciously shaped data causes the application to behave incorrectly before signature validation completes.

Because middleBrick scans the unauthenticated attack surface and runs multiple checks in parallel, it can detect indications of resource abuse during authentication testing. While the tool does not attempt to trigger crashes, it correlates findings such as missing size constraints on input fields, missing rate limiting, and weak authentication schemes to highlight scenarios where Stack Overflow-like conditions could be leveraged in combination with Hmac Signature logic to undermine security.

To secure Gin applications using Hmac Signatures, you should validate and constrain all inputs before they are included in the signed payload, and ensure that signature verification occurs before any expensive processing of user data. Below are concrete, working examples that demonstrate a safe approach.

1. Canonicalization and Signature Verification Before Binding

Compute the signature from the raw request body or selected headers/query parameters before performing any binding. This avoids processing attacker-controlled data during struct unmarshaling.

// Compute HMAC from raw query parameters in a canonical order
func computeSignature(secret, message string) string {
    h := hmac.New(sha256.New, []byte(secret))
    h.Write([]byte(message))
    return hex.EncodeToString(h.Sum(nil))
}

func VerifySignatureMiddleware(secret string) gin.HandlerFunc {
    return func(c *gin.Context) {
        // Example: signature provided in header, message is sorted query string
        receivedSig := c.GetHeader("X-API-Signature")
        rawQuery := c.Request.URL.RawQuery // already URL-encoded, not parsed into struct
        expectedSig := computeSignature(secret, rawQuery)
        if !hmac.Equal([]byte(receivedSig), []byte(expectedSig)) {
            c.AbortWithStatusJSON(401, gin.H{"error": "invalid signature"})
            return
        }
        c.Next()
    }
}

2. Bounded Struct Binding with Explicit Field Control

When you must bind JSON, explicitly list fields and avoid embedding large or nested user input into the signed string. Validate length and structure before use.

type SignedRequest struct {
    Action  string `json:"action" binding:"required,max=100"`
    Payload string `json:"payload" binding:"required,max=4096"`
    // Do NOT include unbounded user data in signed fields
}

func Handler(c *gin.Context) {
    var req SignedRequest
    if err := c.ShouldBindJSON(&req); err != nil {
        c.JSON(400, gin.H{"error": err.Error()})
        return
    }
    // Build canonical string only from controlled fields
    message := req.Action + ":" + req.Payload
    // Verify using middleware or inline; here we assume middleware already ran
    c.JSON(200, gin.H{"status": "ok"})
}

3. Signature Over Large or Nested Data

If your use case requires signing data that could be large, stream or limit the size before hashing, and avoid including user-controlled keys in the canonical form that could lead to deep recursion.

func ComputeLimitedSignature(secret string, limit int64) gin.HandlerFunc {
    return func(c *gin.Context) {
        // Limit the size of the request body read for signing
        limitedReader := io.LimitReader(c.Request.Body, limit)
        bodyBytes, err := io.ReadAll(limitedReader)
        if err != nil {
            c.AbortWithStatusJSON(400, gin.H{"error": "unable to read body"})
            return
        }
        // Restore body for binding if needed
        c.Request.Body = io.NopCloser(bytes.NewBuffer(bodyBytes))

        sig := computeSignature(secret, string(bodyBytes))
        // Compare with provided header...
        c.Set("computed_sig", sig)
        c.Next()
    }
}

By combining middleware that verifies Hmac Signatures early, constraining input sizes, and avoiding the inclusion of unbounded user data in the signed payload, you reduce the risk of stack-related abuse while maintaining a clear, verifiable authentication flow in Gin.