Information Disclosure in Echo Go with Dynamodb

Information disclosure in an Echo Go service that uses DynamoDB often occurs when application responses unintentionally expose data structures, error details, or metadata that should remain private. In Echo Go, HTTP handlers typically marshal DynamoDB attribute value objects (e.g., from GetItem or Query) directly into JSON responses. If the handler does not explicitly filter fields, the raw DynamoDB map format—including type descriptors such as S, N, and BOOL—can be sent to clients, revealing internal schema details.

Additionally, errors from the DynamoDB SDK, such as conditional check failures or provisioned throughput issues, may be returned to the client in verbose form. These messages can include table names, key schema details, or stack traces, aiding an attacker in reconnaissance. For example, a failed UpdateItem with a ConditionalCheckFailedException might be propagated as-is, disclosing that a specific condition on an attribute was expected.

The combination of Echo Go’s flexible routing and middleware with DynamoDB’s attribute-centric data format increases risk if developers treat the database response as the final API payload without normalization. Without an explicit mapping to a clean domain model, sensitive attributes like internal IDs, version numbers, or state flags can be exposed. This aligns with OWASP API Top 10’s A01:2023 broken object level authorization, where excessive data exposure complements authorization flaws such as BOLA/IDOR.

Consider an endpoint that retrieves a user profile using a DynamoDB GetItem call. If the handler directly returns the DynamoDB item without redaction, the client receives type-wrapped attributes. An attacker can leverage this to infer data types, presence of optional fields, or even guess at naming conventions used for sensitive data like password salts or session tokens.

Moreover, unauthenticated LLM endpoints—should they be exposed in the same service—can compound disclosure if model outputs or tool-calling patterns reference DynamoDB table structures or attribute names. Regular security scans using a platform like middleBrick can surface such information leakage by correlating OpenAPI specs with runtime behavior, flagging endpoints that return raw DynamoDB representations without sanitization.

Remediation focuses on strict separation between DynamoDB’s data representation and the API contract. Always map DynamoDB attribute values to a domain struct that contains only the intended fields, and ensure error handling does not surface internal details.

1. Use a domain model and explicit field selection

Define a struct that represents the public shape of your resource, and copy only the necessary fields from the DynamoDB item.

// Domain model
 type UserProfile struct {
     UserID   string `json:"userId"`
     Email    string `json:"email"`
     FullName string `json:"fullName"`
 }

 // DynamoDB attribute value (example)
 func dynamoItemToUserProfile(item map[string]types.AttributeValue) (*UserProfile, error) {
     if item == nil {
         return nil, fmt.Errorf("item not found")
     }
     return &UserProfile{
         UserID:   *item["UserId"].(*types.AttributeValueMemberS).Value,
         Email:    *item["Email"].(*types.AttributeValueMemberS).Value,
         FullName: *item["FullName"].(*types.AttributeValueMemberS).Value,
     }, nil
 }

 // Echo handler
 func getUserProfile(c echo.Context) error {
     userID := c.Param("id")
     item, err := db.GetItem(context.TODO(), &dynamodb.GetItemInput{
         TableName: aws.String("Users"),
         Key: map[string]types.AttributeValue{
             "PK": &types.AttributeValueMemberS{Value: "USER#" + userID},
         },
     })
     if err != nil {
         // Log detailed error internally; return generic message to client
         log.Printf("dynamodb get failed: %v", err)
         return c.JSON(http.StatusInternalServerError, map[string]string{
             "error": "unable to retrieve profile",
         })
     }
     if item.Item == nil {
         return c.NoContent(http.StatusNotFound)
     }
     profile, err := dynamoItemToUserProfile(item.Item)
     if err != nil {
         return c.JSON(http.StatusInternalServerError, map[string]string{
             "error": "unable to process profile data",
         })
     }
     return c.JSON(http.StatusOK, profile)
 }

2. Secure error handling and input validation

Do not forward DynamoDB SDK error messages directly to the client. Instead, log them for internal review and return standardized, minimal error responses. Validate input identifiers to prevent injection attempts that could manipulate error paths.

func safeUpdateUserStatus(c echo.Context) error {
     userID := c.Param("id")
     if !isValidUUID(userID) {
         return c.JSON(http.StatusBadRequest, map[string]string{
             "error": "invalid user identifier",
         })
     }
     _, err := db.UpdateItem(context.TODO(), &dynamodb.UpdateItemInput{
         TableName: aws.String("Users"),
         Key: map[string]types.AttributeValue{
             "PK": &types.AttributeValueMemberS{Value: "USER#" + userID},
         },
         UpdateExpression: aws.String("SET #status = :s"),
         ExpressionAttributeNames: map[string]string{
             "#status": "Status",
         },
         ExpressionAttributeValues: map[string]types.AttributeValue{
             ":s": &types.AttributeValueMemberS{Value: "active"},
         },
         ConditionExpression: aws.String("attribute_exists(PK)"),
     })
     if err != nil {
         var condErr *types.ConditionalCheckFailedException
         if errors.As(err, &condErr) {
             log.Printf("conditional check failed for user %s", userID)
             return c.JSON(http.StatusPreconditionFailed, map[string]string{
                 "error": "precondition failed",
             })
         }
         log.Printf("update failed: %v", err)
         return c.JSON(http.StatusInternalServerError, map[string]string{
             "error": "unable to update status",
         })
     }
     return c.NoContent(http.StatusNoContent)
 }

3. Scan and middleware hygiene

Use Echo middleware to sanitize headers and ensure responses do not include debug information. Combine with middleBrick scans to verify that no endpoint unintentionally returns raw DynamoDB attribute types. Regular scans help detect regressions where new fields are added to domain models but forgotten in the sanitization layer.

For applications with unauthenticated LLM endpoints, ensure model outputs are scanned for accidental references to DynamoDB schema or table structures. MiddleBrick’s LLM security checks can identify such leakage patterns and help refine prompt or response handling logic.