social-analyzer

Pros of Sherlock

• Larger community and more frequent updates
• Supports a wider range of social media platforms (350+)
• Simpler installation process and fewer dependencies

Cons of Sherlock

• Limited to username searches only
• Less detailed output compared to Social Analyzer
• Lacks advanced features like custom queries and API support

Code Comparison

Social Analyzer:

def check_user(username, site):
    response = requests.get(f"{site['url']}/{username}")
    if response.status_code == 200:
        return {"status": "found", "url": response.url}
    return {"status": "not found"}

Sherlock:

def sherlock(username):
    for site in sites:
        url = site['url'].format(username=username)
        response = requests.get(url)
        if response.status_code == 200:
            print(f"[+] {site['name']}: {url}")

Both projects aim to search for usernames across various social media platforms, but they differ in their approach and features. Social Analyzer offers more comprehensive analysis and flexibility, while Sherlock focuses on simplicity and broad platform coverage. The code snippets demonstrate that both use similar methods for checking username availability, but Social Analyzer's implementation allows for more detailed output and customization.

Pros of maigret

• More extensive site coverage (1000+ sites compared to 300+ for social-analyzer)
• Supports custom site addition through YAML files
• Includes additional features like report generation and recursive search

Cons of maigret

• Slower execution due to more comprehensive checks
• May produce more false positives in some cases
• Requires more setup and dependencies

Code comparison

maigret:

async def main():
    queries = [
        QueryTask(username, site)
        for username in args.username
        for site in sites
    ]
    results = await run_queries(queries)

social-analyzer:

def find_username_normal(req):
    for site in sites:
        response = requests.get(site['url'].format(req['string']))
        if response.status_code == 200:
            return True
    return False

Both projects aim to search for usernames across multiple platforms, but maigret uses asynchronous programming for improved performance when dealing with a larger number of sites. social-analyzer uses a simpler synchronous approach, which may be more straightforward but potentially slower for extensive searches.

Pros of EagleEye

• Focuses specifically on facial recognition across social media platforms
• Utilizes machine learning for improved accuracy in image matching
• Provides detailed output including potential social media profiles and image matches

Cons of EagleEye

• Less comprehensive in terms of overall social media analysis
• May require more setup and dependencies due to its machine learning components
• Limited to image-based searches, not as versatile for text-based queries

Code Comparison

EagleEye:

def get_social_media_profiles(name):
    profiles = []
    for platform in SUPPORTED_PLATFORMS:
        profile = platform.search(name)
        if profile:
            profiles.append(profile)
    return profiles

Social-analyzer:

def get_profile(username, site):
    try:
        response = requests.get(f"{site['url']}/{username}")
        if response.status_code == 200:
            return {"username": username, "url": response.url, "found": True}
    except:
        pass
    return {"username": username, "url": None, "found": False}

EagleEye focuses on facial recognition and image matching across platforms, while Social-analyzer provides a broader approach to social media profile analysis. EagleEye may offer more accurate results for image-based searches, but Social-analyzer is more versatile for general social media investigations. The code snippets illustrate the different approaches: EagleEye's emphasis on platform-specific searches and Social-analyzer's more generic profile retrieval method.

Pros of WhatsMyName

• Larger database of sites and platforms (over 1000)
• Community-driven updates and contributions
• Simpler setup and usage for quick checks

Cons of WhatsMyName

• Less comprehensive analysis capabilities
• Limited automation features
• Fewer output format options

Code Comparison

WhatsMyName:

def check_site(site, username):
    url = site['uri'].format(account=username)
    response = requests.get(url, headers=headers)
    if response.status_code == 200:
        print(f"[+] {site['name']}: {url}")

Social Analyzer:

def find_username_normal(username, site):
    url = site['url'].format(username=username)
    response = networking.request(url, headers=headers)
    if response and response.status_code == 200:
        return [{"status": "good", "url": url}]

Both projects use similar approaches for checking username availability on different platforms. However, Social Analyzer offers more advanced features and analysis capabilities beyond simple username checks.

WhatsMyName focuses on a broad range of platforms and relies on community contributions to maintain its extensive database. Social Analyzer provides a more comprehensive toolkit for social media analysis, including profile picture matching and metadata extraction.

While WhatsMyName is easier to set up and use for quick checks, Social Analyzer offers more in-depth analysis and automation options, making it suitable for more complex investigations and larger-scale projects.

Pros of Snoop

• Written in Python, making it more accessible for many developers
• Supports a wider range of social networks and websites (300+)
• Includes a graphical user interface (GUI) for easier use

Cons of Snoop

• Less frequently updated compared to Social-Analyzer
• Documentation is primarily in Russian, which may be a barrier for non-Russian speakers
• Lacks some of the advanced features found in Social-Analyzer, such as custom search engines

Code Comparison

Social-Analyzer (JavaScript):

async function find_username_normal(req) {
  let results = [];
  for (let site of sites_arr) {
    let temp = await find_username_site(req.body.string, site, req.body.option);
    results.push(temp);
  }
  return results;
}

Snoop (Python):

def start(self):
    for site in self.sites:
        self.submit_site(site)
    self.completed_lock.acquire()
    while self.counter > 0:
        self.completed_lock.wait()
    self.completed_lock.release()

Both repositories aim to analyze and gather information from social media profiles, but they differ in implementation and features. Social-Analyzer offers more frequent updates and advanced features, while Snoop provides a wider range of supported platforms and a GUI. The choice between them depends on specific requirements and user preferences.

Pros of GHunt

• Focused specifically on Google account OSINT, providing in-depth information
• Offers a command-line interface for efficient usage
• Includes features like Google Photos metadata extraction

Cons of GHunt

• Limited to Google accounts, while Social Analyzer covers multiple platforms
• Requires more setup and dependencies compared to Social Analyzer
• May require frequent updates due to changes in Google's systems

Code Comparison

GHunt (Python):

def check_and_gen_values(self, client, source):
    body = {"action_type": 1, "min_days_since_confirm": 0}
    headers = {"X-Goog-Spatula": "ChlBb0xNMGNRTDZJRVY4OWNKZzZKTTNSUmRUEhlBb0xNMGNRTDZJRVY4OWNKZzZKTTNSUmRUGAYiAA=="}
    req = client.post(f"{source}/accounts/recovery", json=body, headers=headers)

Social Analyzer (JavaScript):

async function find_username_normal(username) {
  var options = {
    method: "GET",
    url: "https://api.github.com/users/" + username,
    headers: {
      "User-Agent": "request"
    }
  };

Summary

GHunt excels in Google account OSINT but is limited to that platform. Social Analyzer offers broader coverage across multiple social networks. GHunt provides more detailed information for Google accounts, while Social Analyzer is easier to set up and use for general social media reconnaissance.