Input Validator Pattern — Sanitize User Input

In this tutorial, you'll learn how the Input Validator pattern validates and sanitizes all user input to prevent injection attacks.

What You'll Learn

how the Input Validator pattern validates and sanitizes all user input to prevent injection attacks.

Why It Matters

Unvalidated input is the root cause of SQL injection, XSS, and command injection vulnerabilities.

Real-World Use

OWASP validation libraries, joi schema validation, and Django form validation.

The Input Validator Pattern

The Input Validator pattern addresses a specific recurring design problem by providing a reusable solution structure. Understanding when and how to apply it is essential for writing maintainable, scalable code.

Key Concepts

• Authentication: Verifying identity of request originators.
• Authorization: Determining what authenticated entities can access.
• Validation: Ensuring data conforms to expected formats.
• Audit: Logging security-relevant events for analysis.

Structure

The following diagram shows the structure of this pattern:

flowchart LR
    Request --> InputValidator
    InputValidator -->|pass| Handler
    InputValidator -->|block| Reject

Implementation

from typing import Optional
from dataclasses import dataclass
import re

@dataclass
class Request:
    path: str
    headers: dict
    body: str

class InputValidator:
    def __init__(self):
        self._blocked_patterns = [
            re.compile(r"<script>", re.I),
            re.compile(r"DROP TABLE", re.I),
            re.compile(r"../../etc/passwd"),
        ]

    def validate(self, request: Request) -> bool:
        for pattern in self._blocked_patterns:
            if pattern.search(request.body or ""):
                print(f"Blocked: malicious content in {request.path}")
                return False
            if pattern.search(str(request.headers)):
                print(f"Blocked: malicious headers in {request.path}")
                return False
        print(f"Passed: {request.path}")
        return True

validator = InputValidator()
reqs = [
    Request("/login", {}, "username=admin&password=1234"),
    Request("/search", {}, "q=<script>alert(1)</script>"),
    Request("/update", {"X-Forwarded-Host": "../../etc/passwd"}, "data=ok"),
]
for r in reqs:
    validator.validate(r)

Expected output:

Passed: /login
Blocked: malicious content in /search
Blocked: malicious headers in /update

Key Participants

• Client: Code that uses the Input Validator.
• Input Validator: The main abstraction provided by the pattern.
• Implementation: Concrete realization of the pattern.
• Data/State: Information managed by the pattern.

Real-World Examples

• DodaTech uses this pattern internally for consistent cross-cutting concerns.
• Major frameworks and libraries implement this pattern as a core architectural element.
• Production systems at scale depend on this pattern for reliability.

Related Patterns

• Output Escaper

• Intercepting Validator

• Authentication Enforcer

• Design Patterns — the complete patterns catalog.

Pros and Cons

Common Mistakes

1. **Over-engineering: Applying Input Validator where a simpler solution suffices, adding unnecessary complexity.

2. **Wrong granularity: Implementing Input Validator at the wrong level of abstraction.

3. **Thread Safety ignored: Using Input Validator in concurrent context without proper synchronization.

4. **Tight coupling: Violating the pattern intent by creating hidden dependencies.

5. **Premature optimization: Introducing Input Validator before there is evidence it is needed.

Practice Questions

1. What problem does the Input Validator pattern solve? Describe a real-world scenario where using it improves code quality.

2. How does Input Validator differ from alternative approaches? What are the trade-offs?

3. What testing Strategy would you use for code that implements Input Validator?

4. How would you refactor legacy code to introduce Input Validator?

5. When should you NOT use Input Validator? Describe scenarios where it adds unnecessary complexity.

Challenge

Implement a complete Input Validator example in Python with unit tests. Include error handling, edge cases (empty data, null values, concurrent access), and a performance comparison against a simpler alternative. Document your design decisions.

Real-World Task

Find a section of code in your current project that could benefit from the Input Validator pattern. Refactor it, write tests, and measure the improvement in testability, coupling, and cohesion.

Security Tip: When implementing Input Validator, ensure proper input validation, avoid exposing internal state, and follow Least Privilege. At DodaTech, all implementations undergo security review.

Built by the developers of Doda Browser, DodaZIP, and Durga Antivirus Pro.