HIGH token leakageecho godynamodb

Token Leakage in Echo Go with Dynamodb

Token Leakage in Echo Go with Dynamodb — how this specific combination creates or exposes the vulnerability

Token leakage occurs when authentication tokens, API keys, or session identifiers are unintentionally exposed in logs, error messages, or responses. The combination of an Echo Go web framework and DynamoDB as a backend data store can create conditions that facilitate token leakage if request handling and data access patterns are not carefully managed.

Echo Go applications often process HTTP requests that include bearer tokens or session cookies for authentication. If the application logs incoming requests—including headers, query parameters, or request bodies—without redacting sensitive values, tokens can be written to application or system logs. In a DynamoDB-driven backend, developers sometimes include authorization tokens or user identifiers as part of query parameters or as attributes in items stored in tables. When logs capture these values and DynamoDB operations expose them through error messages or misconfigured debugging output, the tokens become accessible to unauthorized parties.

DynamoDB-specific configurations can inadvertently contribute to exposure. For example, using AWS SDK calls with incomplete error handling may surface internal validation messages or raw request payloads that contain token values. If an application retrieves an item from DynamoDB using a key that includes a user identifier derived from a token, and that token is also echoed in logs, an attacker who gains access to logs or error traces can correlate the token with specific data access patterns. Additionally, long-lived or improperly scoped tokens stored as item attributes in DynamoDB increase the window for exposure if those items are inadvertently shared or logged during operations like scans or queries.

The risk is compounded when applications do not enforce strict separation between control-plane operations and data-plane access. In Echo Go, middleware that attaches DynamoDB clients to request contexts can propagate token values across service calls if context values are not cleared after use. Without explicit cleanup, tokens may persist in memory or be serialized into downstream logging instrumentation. This becomes particularly dangerous when DynamoDB streams or event-based triggers are used, as token values embedded in payloads can be replayed or inspected in related event metadata.

Using middleBrick to scan an API that relies on Echo Go and DynamoDB can surface these risks by correlating authentication mechanisms with data access patterns. The scanner’s authentication and data exposure checks help identify whether tokens are reflected in responses or logged during unauthenticated endpoint probing. Its LLM/AI Security checks specifically look for system prompt leakage and output patterns that may inadvertently expose sensitive values, including tokens that could be embedded in structured responses or error payloads.

Remediation focuses on strict token handling, output sanitization, and careful DynamoDB usage. Ensure that tokens are never included in logs, query parameters, or item attributes. Use middleware to strip or mask sensitive headers before logging and validate that DynamoDB operations do not return sensitive metadata. Implement short-lived tokens with scoped permissions and rotate credentials regularly. MiddleBrick’s continuous monitoring and GitHub Action integrations can help enforce these practices by failing builds when findings related to token handling are detected.

Dynamodb-Specific Remediation in Echo Go — concrete code fixes

Remediation for token leakage with Echo Go and DynamoDB centers on secure request handling, safe data access patterns, and explicit token management. The following code examples demonstrate how to structure Echo Go handlers and DynamoDB interactions to reduce exposure risks.

1. Secure Echo Go middleware to sanitize headers and avoid logging tokens

Use middleware to remove or mask authorization headers before logging requests. This prevents tokens from being written to logs during normal operation.

import (
    "github.com/labstack/echo/v4"
    "github.com/labstack/echo/v4/middleware"
    "net/http"
)

func secureMiddleware(next echo.HandlerFunc) echo.HandlerFunc {
    return func(c echo.Context) error {
        // Copy request headers and remove authorization header before logging
        req := c.Request()
        cleanHeader := req.Header.Clone()
        cleanHeader.Del("Authorization")

        // Log only non-sensitive headers
        c.Logger().Infof("Request: %s %s Headers: %v", req.Method, req.URL.Path, cleanHeader)
        return next(c)
    }
}

func main() {
    e := echo.New()
    e.Use(middleware.LoggerWithConfig(middleware.LoggerConfig{
        Format: "${time} ${status} ${method} ${uri} - ${error} ${latency_human} ${header_X-Request-ID}",
    }))
    e.Use(secureMiddleware)
    e.GET("/data", getDataHandler)
    e.Start(":8080")
}

2. Safe DynamoDB client usage with scoped operations and error handling

Initialize the DynamoDB client with minimal permissions and ensure that error handling does not expose token values. Use condition expressions to avoid returning sensitive attributes.

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

func newDynamoClient() (*dynamodb.Client, error) {
    cfg, err := config.LoadDefaultConfig(context.TODO(), config.WithRegion("us-west-2"))
    if err != nil {
        return nil, err
    }
    return dynamodb.NewFromConfig(cfg), nil
}

func getItemWithoutToken(ctx context.Context, client *dynamodb.Client, tableName string, key map[string]types.AttributeValue) (map[string]types.AttributeValue, error) {
    input := &dynamodb.GetItemInput{
        TableName: aws.String(tableName),
        Key:       key,
        // Explicitly limit returned attributes to avoid exposing token fields
        ProjectionExpression: aws.String("id,createdAt,status"),
    }
    result, err := client.GetItem(ctx, input)
    if err != nil {
        // Avoid logging raw keys or internal error details that may contain tokens
        return nil, err
    }
    return result.Item, nil
}

3. Avoid storing tokens as item attributes and use short-lived tokens

Do not persist bearer tokens or session identifiers as DynamoDB item attributes. Instead, store references or hashed identifiers, and validate tokens using a dedicated auth service.

import (
    "crypto/sha256"
    "encoding/hex"
)

// Store a hashed reference instead of the raw token
tokenHash := sha256.Sum256([]byte(rawToken))
item := map[string]types.AttributeValue{
    "UserID":              &types.AttributeValueMemberS{Value: userID},
    "TokenHash":           &types.AttributeValueMemberS{Value: hex.EncodeToString(tokenHash[:])},
    "TokenScope":          &types.AttributeValueMemberS{Value: "read-only"},
    "TokenExpiryTimestamp": &types.AttributeValueMemberN{Value: "1704067200"},
}
// Use condition expressions to enforce validity checks on item operations
input := &dynamodb.PutItemInput{
    TableName: aws.String("Tokens"),
    Item:      item,
    ConditionExpression: aws.String("attribute_not_exists(TokenHash)"),
}

4. Context cleanup and scoped DynamoDB operations

Clear sensitive values from request context after DynamoDB operations complete to prevent accidental propagation across middleware or goroutines.

func getDataHandler(c echo.Context) error {
    token := c.Request().Header.Get("Authorization")
    // Validate token with external auth service...
    userID, err := validateToken(token)
    if err != nil {
        return echo.NewHTTPError(http.StatusUnauthorized, "invalid token")
    }

    // Use a scoped context for DynamoDB operations
    ctx, cancel := context.WithTimeout(c.Request().Context(), 5*time.Second)
    defer cancel()

    key := map[string]types.AttributeValue{
        "UserID": &types.AttributeValueMemberS{Value: userID},
    }
    item, err := getItemWithoutToken(ctx, dynamoClient, "UserData", key)
    if err != nil {
        return echo.NewHTTPError(http.StatusInternalServerError, "data unavailable")
    }

    // Explicitly remove token from context if stored
    c.Set("token", nil)

    return c.JSON(http.StatusOK, item)
}

5. Continuous monitoring with automated checks

Integrate middleBrick’s CLI and GitHub Action to automatically scan API endpoints for token leakage indicators. Configure the scanner to fail builds when findings related to authentication exposure or data exposure are detected.

# Example GitHub Action step
- name: Scan API for token leakage
  uses: middlebrick/github-action@v1
  with:
    url: "https://api.example.com/openapi.json"
    threshold: "medium"
    fail-on: "authentication, data-exposure"

Frequently Asked Questions

Can token leakage be detected by scanning OpenAPI specs alone?

OpenAPI analysis helps identify risky patterns, but runtime probing is required to confirm whether tokens are leaked in responses, logs, or error messages. Tools that combine spec review with active testing provide more reliable detection.

Does DynamoDB encryption at rest prevent token leakage from application logs?

Encryption at rest protects stored data, but it does not prevent tokens from being exposed in application logs, error messages, or through improper handling in code. Secure logging and token handling practices remain essential.

Token Leakage in Echo Go with Dynamodb