Input Validation Strategies - Validation And Defensive Programming | OneNoughtOne

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System Design (LLD)Validation and Defensive Programming

Validation and Defensive Programming

LevelIntermediate

Duration60 mins

TopicValidation and Defensive Programming

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Input Validation Strategies

The First Line of Defense

Every catastrophic software failure has a common origin: bad data entering the system. SQL injection attacks, buffer overflows, null pointer exceptions, business logic corruption—all trace back to insufficient input validation. In 2017, the Equifax breach exposed 147 million records partly due to inadequate input validation. In 2021, Log4Shell exploited improper input handling, affecting millions of systems worldwide.

Input validation isn't merely defensive coding—it's the architectural foundation for system integrity, security, and reliability. This page provides a comprehensive examination of input validation strategies that separate amateur code from production-grade systems.

What You Will Learn

By the end of this page, you will understand the taxonomy of validation strategies, where validation should occur in your architecture, how to design validation layers that compose correctly, and the trade-offs between different approaches. You'll be equipped to design validation systems that are both robust and maintainable.

The Taxonomy of Input Validation

Input validation encompasses multiple distinct concerns, each requiring different strategies. Understanding this taxonomy is essential for designing comprehensive validation systems.

Syntactic Validation verifies that input conforms to expected format and structure. This includes type checking, format validation (email patterns, phone numbers), and encoding verification. Syntactic validation answers: Is this input well-formed?

Semantic Validation ensures input values make sense within the domain context. A syntactically valid date like '2024-02-30' fails semantic validation because February never has 30 days. Semantic validation answers: Does this input make sense?

Business Rule Validation confirms input satisfies domain-specific constraints. An order quantity of 1000 might be syntactically and semantically valid but violate business rules limiting orders to 100 units. Business validation answers: Is this input allowed?

Validation Taxonomy Overview
Validation Type	Focus	Examples	Typical Location
Syntactic	Format & Structure	Type checking, regex patterns, JSON schema	API boundary, DTOs
Semantic	Meaning & Coherence	Date validity, range checks, referential integrity	Domain layer, Value Objects
Business Rule	Domain Constraints	Credit limits, inventory availability, authorization	Domain services, Aggregates
Security	Attack Prevention	SQL injection, XSS, path traversal	All layers, especially boundaries

The Validation Gap

Most validation failures occur because developers conflate these categories. Syntactic validation alone provides false security—a perfectly formatted email address can still be invalid, not owned by the user, or associated with a banned account. Comprehensive validation addresses all categories systematically.

Where Validation Should Live

One of the most contentious architectural decisions is where validation logic belongs. The answer isn't singular—different validation types belong at different layers, and some validation must occur at multiple points.

The Boundary Principle: Validate all external input at system boundaries before it enters your domain. This includes API endpoints, message queue consumers, file upload handlers, and configuration loaders. Boundary validation prevents malformed data from propagating into system internals.

The Domain Principle: Business rules and semantic validation belong in the domain layer. Value Objects should enforce their own invariants. Entities should validate state transitions. This ensures domain integrity regardless of how data enters the system.

The Defense-in-Depth Principle: Critical validations should occur at multiple layers. Don't trust that upstream validation occurred correctly. This redundancy protects against bugs, refactoring errors, and security vulnerabilities.

layered-validation.ts
TypeScript
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// BOUNDARY LAYER: API Controller - Syntactic validation
class OrderController {
    async createOrder(request: HttpRequest): Promise<HttpResponse> {
        // Schema validation at the boundary
        const parseResult = CreateOrderSchema.safeParse(request.body);
        if (!parseResult.success) {
            return HttpResponse.badRequest(parseResult.error.issues);
        }
        
        // Validated DTO enters the application layer
        const result = await this.orderService.createOrder(parseResult.data);
        return result.match({
            success: (order) => HttpResponse.created(order),
            failure: (error) => HttpResponse.unprocessableEntity(error)
        });
    }
}
 
// APPLICATION LAYER: Orchestrates domain operations
class OrderService {
    async createOrder(dto: CreateOrderDto): Promise<Result<Order, OrderError>> {
        // Application-level validation (authorization, resource existence)
        const customer = await this.customerRepo.findById(dto.customerId);
        if (!customer) {
            return Result.failure(OrderError.customerNotFound(dto.customerId));
        }
        
        // Delegate to domain for business validation
        return this.orderFactory.create(customer, dto.items);
    }
}
 
// DOMAIN LAYER: Business rule validation in Value Objects
class Money {
    private constructor(
        private readonly amount: number,
        private readonly currency: Currency
    ) {}
    
    static create(amount: number, currency: Currency): Result<Money, ValidationError> {
        // Semantic validation: amounts must be non-negative
        if (amount < 0) {
            return Result.failure(ValidationError.negativeAmount(amount));
        }
        // Semantic validation: precision must match currency
        if (!currency.isValidPrecision(amount)) {
            return Result.failure(ValidationError.invalidPrecision(amount, currency));
        }
        return Result.success(new Money(amount, currency));
    }
}
 
// DOMAIN LAYER: Business rules in Aggregate
class Order {
    addItem(product: Product, quantity: Quantity): Result<void, OrderError> {
        // Business rule: cannot add items to shipped orders
        if (this.status === OrderStatus.Shipped) {
            return Result.failure(OrderError.cannotModifyShippedOrder());
        }
        // Business rule: maximum items per order
        if (this.items.length >= Order.MAX_ITEMS) {
            return Result.failure(OrderError.maxItemsExceeded());
        }
        // Business rule: inventory availability
        if (!product.hasInventory(quantity)) {
            return Result.failure(OrderError.insufficientInventory(product.id));
        }
        
        this.items.push(new OrderItem(product, quantity));
        return Result.success();
    }
}

Validation Patterns and Techniques

Effective validation requires choosing appropriate patterns for different scenarios. Each pattern has distinct characteristics suited to specific use cases.

Core Validation Patterns

•Schema Validation — Declarative validation using schemas (JSON Schema, Zod, Yup). Excellent for API boundaries where you need clear, documentable contracts. Schemas generate both validation logic and TypeScript types.
•Specification Pattern — Encapsulates business rules as composable objects. Rules can be combined with AND/OR logic, enabling complex validation scenarios. Ideal for configurable business rules.
•Value Objects — Enforce invariants at construction time. An EmailAddress type that can only contain valid emails eliminates scattered validation checks. The type system becomes your validation system.
•Validation Result Pattern — Accumulates all validation errors rather than failing on the first. Essential for user-facing forms where users need complete feedback, not iterative error discovery.
•Pipeline/Chain Validation — Sequences validators, passing results through transformations. Each step can validate and transform, enabling complex multi-stage validation workflows.

validation-patterns.ts
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// PATTERN 1: Schema Validation with Zod
import { z } from 'zod';
 
const CreateUserSchema = z.object({
    email: z.string().email("Invalid email format"),
    password: z.string()
        .min(8, "Password must be at least 8 characters")
        .regex(/[A-Z]/, "Password must contain uppercase letter")
        .regex(/[0-9]/, "Password must contain a number"),
    age: z.number().int().min(18, "Must be 18 or older"),
    role: z.enum(["user", "admin", "moderator"]),
});
 
type CreateUserDto = z.infer<typeof CreateUserSchema>;
 
// PATTERN 2: Specification Pattern for Business Rules
interface Specification<T> {
    isSatisfiedBy(candidate: T): boolean;
    and(other: Specification<T>): Specification<T>;
    or(other: Specification<T>): Specification<T>;
    not(): Specification<T>;
}
 
class OrderValueSpecification implements Specification<Order> {
    constructor(private readonly minValue: Money) {}
    
    isSatisfiedBy(order: Order): boolean {
        return order.totalValue.isGreaterThanOrEqual(this.minValue);
    }
    
    and(other: Specification<Order>): Specification<Order> {
        return new AndSpecification(this, other);
    }
    // ... or, not implementations
}
 
// Compose complex business rules
const eligibleForFreeShipping = new OrderValueSpecification(Money.dollars(50))
    .and(new CustomerTierSpecification(CustomerTier.Gold))
    .or(new PromotionActiveSpecification("FREE_SHIP_2024"));
 
// PATTERN 3: Validation Result Pattern (accumulating errors)
class ValidationResult {
    private constructor(
        private readonly errors: ValidationError[]
    ) {}
    
    static valid(): ValidationResult {
        return new ValidationResult([]);
    }
    
    static invalid(...errors: ValidationError[]): ValidationResult {
        return new ValidationResult(errors);
    }
    
    combine(other: ValidationResult): ValidationResult {
        return new ValidationResult([...this.errors, ...other.errors]);
    }
    
    get isValid(): boolean {
        return this.errors.length === 0;
    }
    
    get allErrors(): ValidationError[] {
        return [...this.errors];
    }
}
 
// Usage: Accumulate all errors for user feedback
function validateUserProfile(data: UserProfileData): ValidationResult {
    return ValidationResult.valid()
        .combine(validateEmail(data.email))
        .combine(validatePhoneNumber(data.phone))
        .combine(validateAddress(data.address))
        .combine(validateDateOfBirth(data.dateOfBirth));
}

Security-Focused Validation

Security validation requires a fundamentally different mindset: assume all input is malicious. Attackers craft inputs specifically designed to bypass validation and exploit system vulnerabilities.

Common Attack Vectors and Defenses
Attack	Description	Validation Defense
SQL Injection	Malicious SQL in user input	Parameterized queries, input sanitization, allowlists
XSS	Script injection in output	Output encoding, Content Security Policy, sanitization
Path Traversal	Access files outside intended directory	Canonical path validation, allowlist directories
Command Injection	OS commands in input	Never construct commands from input, strict allowlists
Integer Overflow	Values exceeding type bounds	Range validation before arithmetic, safe math libraries
Deserialization	Malicious serialized objects	Type allowlists, avoid deserializing untrusted data

The Allowlist Principle

Always validate against allowlists (what IS permitted), never blocklists (what IS NOT permitted). Blocklists inevitably miss attack vectors. If you expect a color, validate against ['red', 'green', 'blue']—don't try to block every possible malicious string.

security-validation.ts
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// SECURE: Allowlist validation for file uploads
const ALLOWED_EXTENSIONS = new Set(['.jpg', '.jpeg', '.png', '.gif', '.webp']);
const ALLOWED_MIME_TYPES = new Set([
    'image/jpeg', 'image/png', 'image/gif', 'image/webp'
]);
 
function validateFileUpload(file: UploadedFile): Result<void, SecurityError> {
    // Validate extension (case-insensitive)
    const ext = path.extname(file.originalName).toLowerCase();
    if (!ALLOWED_EXTENSIONS.has(ext)) {
        return Result.failure(SecurityError.invalidFileType(ext));
    }
    
    // Validate MIME type from actual file content, not headers
    const detectedMime = detectMimeType(file.buffer);
    if (!ALLOWED_MIME_TYPES.has(detectedMime)) {
        return Result.failure(SecurityError.mimeTypeMismatch(detectedMime));
    }
    
    // Validate file size
    if (file.size > MAX_FILE_SIZE) {
        return Result.failure(SecurityError.fileTooLarge(file.size));
    }
    
    // Validate filename doesn't contain path traversal
    if (file.originalName.includes('..') || file.originalName.includes('/')) {
        return Result.failure(SecurityError.pathTraversal());
    }
    
    return Result.success();
}
 
// SECURE: Path validation preventing directory traversal
class SecureFileAccess {
    constructor(private readonly baseDirectory: string) {
        // Ensure base directory is absolute and canonical
        this.baseDirectory = path.resolve(baseDirectory);
    }
    
    getFilePath(userProvidedPath: string): Result<string, SecurityError> {
        // Resolve to absolute path
        const requestedPath = path.resolve(this.baseDirectory, userProvidedPath);
        
        // Verify it's still within base directory (canonical path comparison)
        if (!requestedPath.startsWith(this.baseDirectory + path.sep)) {
            return Result.failure(SecurityError.pathTraversal());
        }
        
        return Result.success(requestedPath);
    }
}

Composable Validation Architecture

Production systems require validation logic that is composable, reusable, and testable. This demands treating validators as first-class architectural components rather than scattered conditionals.

composable-validators.ts
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// Composable Validator Interface
interface Validator<T, E = ValidationError> {
    validate(value: T): Result<T, E[]>;
}
 
// Validator Combinators
class Validators {
    // Combine validators, collecting all errors
    static all<T>(...validators: Validator<T>[]): Validator<T> {
        return {
            validate(value: T): Result<T, ValidationError[]> {
                const errors: ValidationError[] = [];
                for (const validator of validators) {
                    const result = validator.validate(value);
                    if (result.isFailure) {
                        errors.push(...result.error);
                    }
                }
                return errors.length > 0 
                    ? Result.failure(errors)
                    : Result.success(value);
            }
        };
    }
    
    // Chain validators, stopping on first failure
    static chain<T>(...validators: Validator<T>[]): Validator<T> {
        return {
            validate(value: T): Result<T, ValidationError[]> {
                for (const validator of validators) {
                    const result = validator.validate(value);
                    if (result.isFailure) {
                        return result;
                    }
                }
                return Result.success(value);
            }
        };
    }
    
    // Conditional validator
    static when<T>(
        condition: (value: T) => boolean,
        validator: Validator<T>
    ): Validator<T> {
        return {
            validate(value: T): Result<T, ValidationError[]> {
                if (condition(value)) {
                    return validator.validate(value);
                }
                return Result.success(value);
            }
        };
    }
}
 
// Reusable primitive validators
const nonEmpty = (field: string): Validator<string> => ({
    validate: (value) => value.trim().length > 0
        ? Result.success(value)
        : Result.failure([ValidationError.required(field)])
});
 
const maxLength = (max: number, field: string): Validator<string> => ({
    validate: (value) => value.length <= max
        ? Result.success(value)
        : Result.failure([ValidationError.tooLong(field, max)])
});
 
// Compose domain-specific validators from primitives
const usernameValidator = Validators.all(
    nonEmpty("username"),
    maxLength(50, "username"),
    {
        validate: (value: string) => /^[a-zA-Z0-9_]+$/.test(value)
            ? Result.success(value)
            : Result.failure([ValidationError.invalidFormat("username")])
    }
);

Summary: Input Validation Strategies

Key Takeaways

•Validation is multi-dimensional — Syntactic, semantic, business, and security validation each require distinct strategies and belong at different architectural layers.
•Validate at boundaries, enforce in domain — External input validation at system edges, business rules enforced within domain objects and Value Objects.
•Choose appropriate patterns — Schema validation for APIs, Specification pattern for complex rules, Value Objects for domain invariants, Result pattern for user feedback.
•Security requires allowlists — Always validate against what IS permitted, never try to block what IS NOT. Assume all input is potentially malicious.
•Build composable validators — Treat validators as first-class components that can be combined, tested, and reused across the system.

Page Complete

You now understand the comprehensive landscape of input validation strategies. Next, we'll explore guard clauses—a powerful technique for validating preconditions at function entry points that dramatically improves code clarity and correctness.