After spending years consulting on legacy NestJS projects, I've seen a pattern that keeps me up at night. It's not the complex business logic or the tangled dependencies that worry me most - it's something far simpler: validation. Unlike a broken feature that screams for attention, poor validation quietly accumulates until one day, you're staring at a SQL injection attack or a crashed server, wondering how it happened. Why Your First Line of Defense Matters More Than You Think Picture your typical NestJS application. Data flows like water through pipes: HTTP request → Controller → App Service → Database HTTP request → Controller → App Service → Database When you validate at the entry point—right at those Request DTOs—you're essentially installing a filter at the source. Skip this step, and contaminated data flows through your entire system. The Validation Mistakes I See Over and Over Let me share what I've discovered lurking in production codebases. 1. The "It's a String, Ship It!" Syndrome This is the classic: export class CreateUserDto {
  @IsString()
  name: string;
  
  @IsString() 
  description: string;
} export class CreateUserDto {
  @IsString()
  name: string;
  
  @IsString() 
  description: string;
} Sure, you've confirmed it's a string. But what about: That user who submits a 10MB "name"?
The clever hacker testing DROP?
Someone pasting xss script in the description? That user who submits a 10MB "name"? The clever hacker testing DROP? Someone pasting xss script in the description? 2. The Wild West of Numbers I've lost count of how many times I've seen: @IsNumber()
quantity: number;  // What could go wrong? @IsNumber()
quantity: number;  // What could go wrong? Well, let me tell you what goes wrong: Negative quantities in shopping carts (free money, anyone?)
Page numbers like 999999999 that bring your database to its knees
Array generation based on user input that eats all your RAM Negative quantities in shopping carts (free money, anyone?) Page numbers like 999999999 that bring your database to its knees Array generation based on user input that eats all your RAM 3. The String That Ate Production This one keeps me awake: @IsString()
token: string;  // Living dangerously @IsString()
token: string;  // Living dangerously Without content validation, you're inviting: SQL injection attempts
JavaScript payloads trying to access your environment variables
Path traversal attacks reaching for etc passwd
XSS attacks waiting to pounce on your users SQL injection attempts JavaScript payloads trying to access your environment variables Path traversal attacks reaching for etc passwd XSS attacks waiting to pounce on your users How We Got Here: A Brief History The class-validator Revolution (2020-Present) NestJS and class-validator changed the game, but here's the catch: most developers stop at @IsString() and call it a day. The tools are there, but using them properly requires knowledge that's often buried in documentation or learned through painful experience. @IsString() The AI Era (2023-Present) Now we have Cursor, Claude, and other AI assistants. They're game-changers, but they're not magic: They analyze one file at a time, missing the big picture
The output quality depends entirely on how you prompt them They analyze one file at a time, missing the big picture The output quality depends entirely on how you prompt them What Good Validation Actually Looks Like Let me show you the difference AI-assisted development can make. The Old Way: @IsString()
username: string;

@IsString()
@MaxLength(1000)
content: string; @IsString()
username: string;

@IsString()
@MaxLength(1000)
content: string; The More Secure Way: // User input fields
@IsString()
@MaxLength(255)
@Matches(/^[a-zA-Z0-9\s\-_]+$/, {
  message: 'Only alphanumeric characters, spaces, hyphens, and underscores allowed'
})
@Transform(({ value }) => value?.trim())
username: string;

// Fields that might contain HTML
@IsString()
@MaxLength(10000)
@Transform(({ value }) => sanitizeHtml(value, { allowedTags: [] }))
content: string; // User input fields
@IsString()
@MaxLength(255)
@Matches(/^[a-zA-Z0-9\s\-_]+$/, {
  message: 'Only alphanumeric characters, spaces, hyphens, and underscores allowed'
})
@Transform(({ value }) => value?.trim())
username: string;

// Fields that might contain HTML
@IsString()
@MaxLength(10000)
@Transform(({ value }) => sanitizeHtml(value, { allowedTags: [] }))
content: string; The difference? The second approach actually thinks about what could go wrong. The True Cost of Cutting Corners Here's what poor validation really costs you: Security breaches - Not if, but when. SQL injection and XSS are still alive and well in 2025. Security breaches Data corruption - Once bad data enters your database, good luck cleaning it up. Data corruption Performance nightmares - innocent-looking unbounded query? It's a ticking time bomb. Performance nightmares Business logic failures - Negative prices, impossible dates, calculations that make no sense. Business logic failures Developer suffering - Hours spent debugging issues that proper validation would have prevented. Developer suffering Scaling the Solution For large legacy projects, updating validation is really hard. That's why I ended up building class-validator-security-enhancer, an AI-powered tool that can analyze and fix validation across entire codebases. But whether you use automation or not, the principle remains the same: treat validation as seriously as you treat your core business logic. class-validator-security-enhancer The Bottom Line Here's what I want you to remember: Validation is your moat - It stops attacks before they can do damage
Type checking is just the beginning - Real security comes from content validation
Legacy code needs love too - Systematic approaches beat ad-hoc fixes
AI is a powerful ally - But it needs your expertise to guide it
Consistency is king - One weak link can compromise everything Validation is your moat - It stops attacks before they can do damage Validation is your moat Type checking is just the beginning - Real security comes from content validation Type checking is just the beginning Legacy code needs love too - Systematic approaches beat ad-hoc fixes Legacy code needs love too AI is a powerful ally - But it needs your expertise to guide it AI is a powerful ally Consistency is king - One weak link can compromise everything Consistency is king We're living in an era where AI can help us write secure validation code in seconds. The tools are there, the patterns are established, and the knowledge is available. If your DTOs still look like they're from 2019, it's time for an upgrade.

The code in this story is for educational purposes. The readers are solely responsible for whatever they build with it.

Bad Validation Is Breeding Security Nightmares in NestJS

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