Command Injection in Nestjs with Dynamodb

Command Injection occurs when untrusted input is passed to system-level commands without proper validation or sanitization. In a NestJS application interacting with DynamoDB, the risk typically arises not from the DynamoDB client itself, but from how developers construct shell commands or external process invocations using data that may include user-controlled values.

Consider a scenario where an endpoint accepts a table name or a key attribute value and uses it to build a shell command, for example to invoke an AWS CLI wrapper or a custom script. If the input is concatenated directly into the command string, an attacker can inject additional shell commands. A vulnerable implementation might look like this:

import { Controller, Get, Query } from '@nestjs/common';
import { exec } from 'child_process';

@Controller('users')
export class UsersController {
  @Get()
  getUsers(@Query('name') name: string) {
    // Dangerous: direct string concatenation
    exec(`aws dynamodb scan --table-name Users --filter-expression "Name=username,Value=${name},EQ"`, (error, stdout) => {
      // handle output
    });
  }
}

In this example, the name query parameter is interpolated directly into the AWS CLI command. An attacker could provide a value such as admin; cat /etc/passwd, leading to unintended command execution. Although DynamoDB is a managed NoSQL database and does not execute shell commands, the vulnerability lies in the unsafe handling of input before it reaches the AWS CLI or any subprocess. The DynamoDB-specific surface here is limited to operations that involve dynamic construction of CLI arguments, such as table names or attribute values used in filters.

Even when using the official AWS SDK for JavaScript within NestJS, developers might mistakenly believe that all DynamoDB interactions are safe, while introducing command injection via auxiliary tooling. The combination of NestJS's controller-driven architecture and DynamoDB's flexible data model can inadvertently encourage passing raw input into shell utilities for tasks like exporting or transforming data, increasing exposure.

Another vector involves environment variables or configuration values that are influenced by user input. If an attacker can control an environment variable that affects how a DynamoDB-related command is constructed, they may leverage command injection to alter execution flow. This highlights the importance of validating and sanitizing any data that participates in command assembly, regardless of whether it directly touches the database.

To prevent Command Injection when working with DynamoDB in NestJS, avoid constructing shell commands with user input entirely. Prefer using the AWS SDK directly for all DynamoDB operations, which eliminates shell injection risks and is more efficient.

If you must invoke external processes, rigorously validate and sanitize inputs, and use parameterized commands or an exec library that supports argument arrays. Below is a secure approach using the AWS SDK for JavaScript (v3) within a NestJS service:

import { Injectable } from '@nestjs/common';
import { DynamoDBClient, ScanCommand, ScanCommandInput } from '@aws-sdk/client-dynamodb';

@Injectable()
export class DynamoService {
  private readonly client = new DynamoDBClient({ region: 'us-east-1' });

  async scanTable(tableName: string, filterValue: string) {
    const params: ScanCommandInput = {
      TableName: tableName,
      FilterExpression: 'username = :val',
      ExpressionAttributeValues: {
        ':val': { S: filterValue },
      },
    };

    const command = new ScanCommand(params);
    return this.client.send(command);
  }
}

This approach ensures that user input is passed as data to the DynamoDB API, not as part of a shell command. The table name should still be validated against a whitelist or strict pattern to prevent NoSQL injection or other logic flaws, but this eliminates command injection.

For scenarios requiring shell interaction, such as invoking legacy scripts, use strict allowlisting and avoid string interpolation:

import { execFile } from 'child_process';

const allowedTables = ['users', 'orders', 'products'];

function safeExec(tableName: string, filterValue: string) {
  if (!allowedTables.includes(tableName)) {
    throw new Error('Invalid table name');
  }

  execFile('aws', ['dynamodb', 'scan', '--table-name', tableName, '--filter-expression', `username=${filterValue}`], (error, stdout) => {
    // handle output
  });
}

Here, execFile is used with an argument array, and the table name is restricted to a predefined list. Even with this safeguard, prefer SDK-based interactions to minimize risk and complexity.