Formula Injection in Aspnet with Dynamodb

Formula Injection occurs when user-controlled data is interpreted as part of a query or expression language rather than treated as plain data. In an ASP.NET application that uses Amazon DynamoDB as its persistence layer, the risk emerges when untrusted input is used to construct query expressions, filter logic, or conditional constructs that are evaluated by a downstream system. Although DynamoDB itself does not support server-side expression languages like some SQL or NoSQL query APIs, an ASP.NET backend can build query parameters or conditional logic in a way that allows injected content to affect behavior, especially when input is concatenated into strings used for query construction or passed to services that evaluate expressions.

With DynamoDB, a common pattern is to use the AWS SDK to build query or scan requests based on incoming request parameters. If an ASP.NET controller or service directly interpolates user input into key names, attribute values, or filter-like strings that are later used in SDK calls, an attacker can supply values that change the intended semantics. For example, an input field expected to be a simple string identifier might include additional characters or structured text that causes the constructed query to match unintended items or expose sensitive data. In a black-box scan, middleBrick tests such scenarios by submitting payloads designed to detect whether input is reflected in query construction or influences the response in a way that indicates interpretation beyond safe data binding.

Because middleBrick scans the unauthenticated attack surface of an endpoint using 12 parallel security checks, it can identify whether an API endpoint reflects user input into DynamoDB-related logic in a way that suggests Formula Injection risk. The scan does not rely on internal implementation details but observes behavior: whether injected patterns appear in responses, whether they change the set of returned items, or whether they trigger validation or error messages that indicate parsing. For an ASP.NET endpoint backed by DynamoDB, this often involves submitting strings that include special characters, structured text, or reserved patterns and checking whether the resulting request to DynamoDB behaves differently than a benign input would. The detection capability in the LLM/AI Security category further supports identifying whether any response content reveals system prompt leakage or other sensitive information through injected query influences.

To mitigate Formula Injection risks in an ASP.NET application using DynamoDB, ensure that all user input is treated strictly as data and never as part of the query structure. Use the AWS SDK for .NET with strongly typed request objects and avoid string concatenation or interpolation when building query parameters. Instead of constructing filter expressions by appending user input, define explicit attribute names and use condition expressions with placeholder values that are bound safely by the SDK.

Below are concrete code examples for safe DynamoDB interactions in ASP.NET.

• Safe query using key condition expressions with explicit attribute names and placeholder values:

using Amazon.DynamoDBv2; 
using Amazon.DynamoDBv2.Model; 
using System.Threading.Tasks;

public class ProductService
{
    private readonly IAmazonDynamoDB _ddb;
    public ProductService(IAmazonDynamoDB ddb) => _ddb = ddb;

    public async Task<SearchResponse> GetProductsByCategoryAsync(string categoryId)
    {
        var request = new QueryRequest
        {
            TableName = "Products",
            KeyConditionExpression = "CategoryId = :cid",
            ExpressionAttributeValues = new Dictionary<string, AttributeValue>
            {
                { ":cid", new AttributeValue { S = categoryId } }
            }
        };
        return await _ddb.QueryAsync(request);
    }
}

• Safe scan or filter using explicit expression attribute names and values:

using Amazon.DynamoDBv2; 
using Amazon.DynamoDBv2.Model; 
using System.Collections.Generic;
using System.Threading.Tasks;

public class InventoryService
{
    private readonly IAmazonDynamoDB _ddb;
    public InventoryService(IAmazonDynamoDB ddb) => _ddb = ddb;

    public async Task<Dictionary<string, AttributeValue>[]> SearchItemsAsync(string ownerId, string status)
    {
        var request = new ScanRequest
        {
            TableName = "Inventory",
            FilterExpression = "OwnerId = :oid AND Status = :st",
            ExpressionAttributeNames = new Dictionary<string, string>
            {
                { "#o", "OwnerId" },
                { "#s", "Status" }
            },
            ExpressionAttributeValues = new Dictionary<string, AttributeValue>
            {
                { ":oid", new AttributeValue { S = ownerId } },
                { ":st", new AttributeValue { S = status } }
            }
        };
        var response = await _ddb.ScanAsync(request);
        return response.Items.ToArray();
    }
}

• Validate and normalize input before using it in queries:

using System;
using System.Text.RegularExpressions;

public static class InputValidation
{
    private static readonly Regex SafeIdPattern = new Regex("^[a-zA-Z0-9_-]{1,64}$", RegexOptions.Compiled);

    public static string NormalizeCategoryId(string raw)
    {
        if (string.IsNullOrWhiteSpace(raw))
            throw new ArgumentException("Category ID is required.");
        var trimmed = raw.Trim();
        if (!SafeIdPattern.IsMatch(trimmed))
            throw new ArgumentException("Invalid category ID format.");
        return trimmed;
    }
}

By combining explicit expression templates, placeholder binding, and strict input validation, an ASP.NET service can avoid interpreting user-controlled values as part of query logic. This approach aligns with secure coding practices for DynamoDB and reduces the likelihood that injected content changes the intended query semantics.