Token Leakage in Gorilla Mux with Dynamodb

Token leakage occurs when authentication tokens, session cookies, or API keys are exposed in logs, URLs, referrer headers, or error messages. The combination of Gorilla Mux (a popular HTTP request router for Go) and DynamoDB backend services can unintentionally expose tokens through misconfigured routing, logging, or error handling patterns.

Gorilla Mux routes requests based on path variables and headers. If route definitions capture tokens as path parameters (for example, /users/{token}/data) or pass them in query strings without sanitization, tokens can be exposed in server logs or access logs. DynamoDB, when used as a data store for session or token metadata, may return items that include sensitive attributes. If application code returns entire DynamoDB items—including token fields—without filtering, tokens can be leaked in API responses.

Another leakage vector arises from error messages. When a request routed by Gorilla Mux triggers a DynamoDB operation (such as GetItem or Query), panics or returned errors that include request parameters can expose tokens in stack traces or error payloads. For example, logging the entire HTTP request URL before forwarding to DynamoDB might print a token-bearing path. Similarly, if a Lambda or service retrieves a token from DynamoDB and includes it in a JSON response (even inadvertently via a debug field), the token is exposed to the client.

Middleware instrumentation in Gorilla Mux can also contribute. If middleware logs headers such as Authorization or custom tokens for observability without redaction, those logs become a sensitive data exposure risk. DynamoDB streams or backup exports that retain token attributes compound the problem by persisting tokens beyond their intended lifecycle.

To assess this risk with middleBrick, scans include checks for data exposure and input validation across authenticated and unauthenticated surfaces, flagging endpoints that return sensitive attributes like tokens in responses or logs. The scanner also reviews OpenAPI specs to detect path or query parameters named token or key that lack proper masking or encryption indicators.

Remediation focuses on preventing tokens from appearing in logs, URLs, and responses, and on ensuring DynamoDB operations do not expose sensitive attributes. Below are concrete Go code examples for a Gorilla Mux service that safely interacts with DynamoDB.

First, avoid capturing tokens in route paths. Use opaque identifiers instead of raw tokens in URLs:

// Good: use an opaque userID, not a token, in the path
r := mux.NewRouter()
r.HandleFunc("/users/{userID}/profile", profileHandler).Methods("GET")

Second, ensure middleware does not log sensitive headers. Redact tokens before logging:

func loggingMiddleware(next http.Handler) http.Handler {
    return http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
        // redact Authorization header from logs
        auth := r.Header.Get("Authorization")
        var logAuth string
        if auth != "" {
            logAuth = "[redacted]"
        }
        // log only non-sensitive parts
        log.Printf("method=%s path=%s auth=%s", r.Method, r.URL.Path, logAuth)
        next.ServeHTTP(w, r)
    })
}

Third, when fetching data from DynamoDB, project only required attributes and exclude token fields. Use the DynamoDB SDK’s expression builder to select safe attributes:

import (
    "context"
    "github.com/aws/aws-sdk-go-v2/service/dynamodb"
    "github.com/aws/aws-sdk-go-v2/service/dynamodb/types"
    "github.com/aws/aws-sdk-go-v2/feature/dynamodb/attributevalue"
)

type UserProfile struct {
    UserID    string `json:"userId"`
    Email     string `json:"email"`
    // do not include Token field here
}

func getUserProfile(ctx context.Context, client *dynamodb.Client, userID string) (*UserProfile, error) {
    out, err := client.GetItem(ctx, &dynamodb.GetItemInput{
        TableName: aws.String("Users"),
        Key: map[string]types.AttributeValue{
            "userID": &types.AttributeValueMemberS{Value: userID},
        },
        // ExpressionAttributeNames can exclude sensitive attributes if needed
    })
    if err != nil {
        return nil, err
    }
    var profile UserProfile
    err = attributevalue.UnmarshalMap(out.Item, &profile)
    if err != nil {
        return nil, err
    }
    return &profile, nil
}

Fourth, never return DynamoDB items directly in HTTP responses. Filter fields server-side:

func profileHandler(w http.ResponseWriter, r *http.Request) {
    userID := mux.Vars(r)["userID"]
    profile, err := getUserProfile(r.Context(), dynamoClient, userID)
    if err != nil {
        http.Error(w, "unable to load profile", http.StatusInternalServerError)
        return
    }
    // Only encode safe fields
    if err := json.NewEncoder(w).Encode(profile); err != nil {
        http.Error(w, "failed to encode response", http.StatusInternalServerError)
    }
}

Fifth, enforce strict error handling that does not surface tokens or internal details:

func safeError(w http.ResponseWriter, err error) {
    // Generic message; do not include user input or internal errors
    http.Error(w, "internal server error", http.StatusInternalServerError)
    // Log the actual error server-side for investigation, without exposing to client
    log.Printf("error: %v", err)
}

These practices reduce token leakage by ensuring tokens are not part of route definitions, are redacted in logs, are never returned in responses, and DynamoDB operations project only safe attributes. middleBrick scans can validate these controls by checking for tokens in responses and inspecting logging practices described in the OpenAPI spec.