Tamior's Portfolio

🎯 Introduction

The guide demonstrates how to use various tools to analyze API patterns and behaviors. By the end, you will understand how to examine API endpoints, analyze request/response patterns, and implement proper testing methodologies.

🛠️ Required Tools

•Postman
•Python & Requests Library

🔍 Analysis Techniques

1. Basic Request Analysis 📡

Let's start by examining a simple API request:

import requests

# Basic request analyzer
def analyze_request(url):
    print(f"Analyzing: {url}")
    response = requests.get(url)
    
    print(f"Status: {response.status_code}")
    print(f"Headers: {dict(response.headers)}")
    print(f"Content Type: {response.headers.get('content-type')}")

# Try with a public API
analyze_request("https://api.github.com/zen")

Video Tutorial: Using Postman

Video demonstration of basic API request analysis using Postman

2. Pattern Recognition 🎯

We'll create a simple pattern analyzer:

class PatternAnalyzer:
    def __init__(self):
        self.patterns = {}
        
    def analyze_endpoint(self, url, method="GET"):
        # Store endpoint patterns
        key = f"{method} {url}"
        self.patterns[key] = self.patterns.get(key, 0) + 1
        
    def show_patterns(self):
        for endpoint, count in self.patterns.items():
            print(f"Endpoint: {endpoint}, Calls: {count}")

3. Response Analysis 📊

Examining API response patterns:

def analyze_response(response):
    print("Status Code:", response.status_code)
    
    if response.headers.get('x-ratelimit-limit'):
        print("Rate Limit:", response.headers['x-ratelimit-limit'])
    
    if 'json' in response.headers.get('content-type', ''):
        data = response.json()
        print("Response Structure:", list(data.keys()))

💡 Practical Examples

1. GitHub API Example

Let's analyze GitHub's API with our tools:

# Analyze GitHub API
def check_github_api():
    # Basic user info request
    url = "https://api.github.com/users/octocat"
    
    # First, analyze the request
    analyze_request(url)
    
    # Then check response patterns
    response = requests.get(url)
    analyze_response(response)
    
    print("
Trying another endpoint...")
    
    # Try the repos endpoint
    repos_url = "https://api.github.com/users/octocat/repos"
    analyze_request(repos_url)

check_github_api()

🎥 Watch it in Action

Demo: Running the GitHub API analysis script and examining the results

2. Weather API Example

Analyzing weather data patterns:

# Weather API analysis
def check_weather_api():
    base_url = "https://api.openweathermap.org/data/2.5/weather"
    
    # Check weather for different cities
    cities = ["London", "Tokyo", "New York", "Vienna"]
    
    for city in cities:
        print(f"Checking weather in {city}...")
        url = f"{base_url}?q={city}&appid=your_api_key"
        
        # Analyze the request
        analyze_request(url)
        
        # Check the response
        response = requests.get(url)
        analyze_response(response)

check_weather_api()

📚 Best Practices

API Analysis Guidelines

• Always check API documentation first
• Respect rate limits and terms of service
• Use appropriate authentication methods
• Document your findings systematically
• Test in a controlled environment

🎯 Next Steps

After mastering these basics, you can:

•Build more sophisticated analysis tools
•Contribute to API security research
•Develop automated testing frameworks