Insecure Design in Echo Go with Dynamodb

Insecure design in an Echo Go service that uses DynamoDB often stems from modeling data and access patterns that do not enforce authorization boundaries at the database layer. When application logic decides which DynamoDB item a user can access after retrieving a broad result set or using a shared partition key, the design pushes authorization checks into the application instead of into the data access layer. This creates a BOLA/IDOR surface where attackers can manipulate identifiers in requests to access other users' records.

Echo Go APIs frequently define routes like /users/:userID/resource/:resourceID and then perform a GetItem or Query on a DynamoDB table using userID from the URL as a key condition. If the developer does not validate that the authenticated subject matches the userID used in the DynamoDB request, an attacker can change :userID to another user’s ID and read or modify data they should not see. Because DynamoDB is a fast key-value store, the lack of server-side authorization means there is no safety net once the application issues the request.

Additionally, an insecure design may rely on client-provided sort keys or secondary indexes without re-verifying ownership on the server. For example, a client might send a sort key or filter expression that the application directly forwards to DynamoDB. An attacker can inject expressions that return other users’ items or consume excessive read capacity, leading to information exposure or a denial of condition. The combination of Echo Go’s flexible routing and DynamoDB’s low-level API encourages shortcuts where authorization is assumed rather than enforced, which maps to common weaknesses in the OWASP API Top 10 and can be surfaced by a scan from middleBrick, which compares runtime behavior against OpenAPI definitions and highlights missing authorization checks.

Remediation centers on enforcing authorization at the point of data access and designing DynamoDB access patterns that align with the principle of least privilege. In Echo Go, this means deriving the partition key from the authenticated subject and never trusting client-supplied identifiers for cross-user access.

First, always compute the partition key from the authenticated user identity rather than accepting it from the request. For example, use a context key to carry the user ID after authentication and construct DynamoDB key expressions from that trusted value.

// Echo Go handler: derive partition key from authenticated subject
func GetUserResource(c echo.Context) error {
    userID := c.Get("userID").(string) // from auth middleware, not from URL
    resourceID := c.Param("resourceID")
    svc := dynamodb.NewFromConfig(cfg)
    out, err := svc.GetItem(c.RequestContext(), &dynamodb.GetItemInput{
        TableName: aws.String("Resources"),
        Key: map[string]types.AttributeValue{
            "PK": &types.AttributeValueMemberS{Value: userID},
            "SK": &types.AttributeValueMemberS{Value: "RESOURCE#" + resourceID},
        },
    })
    if err != nil {
        return echo.NewHTTPError(http.StatusInternalServerError, err.Error())
    }
    if out.Item == nil {
        return echo.NewHTTPError(http.StatusNotFound)
    }
    return c.JSON(out.Item)
}

This pattern ensures that even if an attacker changes resourceID, they cannot alter the partition key used to locate data, because the partition key is derived from the authenticated identity. The design assumes that the resource ID is namespaced under the user, which is enforced by the key construction.

Second, avoid using client-provided expressions directly with DynamoDB. Instead, build expression attribute values locally and validate field names against a whitelist. This prevents injection-style manipulation of filter expressions that could expose other users’ items.

// Safe query construction in Echo Go
func ListMyResources(c echo.Context) error {
    userID := c.Get("userID").(string)
    filter := c.QueryParam("filter") // e.g., status=active
    // Validate filter format before use; do not forward raw input to DynamoDB
    allowedStatus := map[string]bool{"active": true, "archived": true}
    if filter != "" && !allowedStatus[filter] {
        return echo.NewHTTPError(http.StatusBadRequest, "invalid filter")
    }
    svc := dynamodb.NewFromConfig(cfg)
    expr := "#status = :status"
    av := map[string]types.AttributeValue{
        ":status": &types.AttributeValueMemberS{Value: filter},
    }
    out, err := svc.Query(c.RequestContext(), &dynamodb.QueryInput{
        TableName:              aws.String("Resources"),
        KeyConditionExpression: aws.String("PK = :user"),
        ExpressionAttributeNames: map[string]string{
            "#status": "status",
        },
        ExpressionAttributeValues: av,
    })
    // handle error and response
}

For continuous assurance, integrate middleBrick into your workflow. Use the CLI to scan from the terminal with middlebrick scan <url>, add the GitHub Action to perform API security checks in your CI/CD pipeline, or run scans directly from your IDE via the MCP Server. These integrations help catch insecure design patterns before deployment, ensuring that authorization logic is verified alongside functionality.