Pros of Sherlock

• Broader scope: Searches for usernames across 300+ websites
• Active community with frequent updates and contributions
• Supports command-line arguments for customization

Cons of Sherlock

• Less focused on specific platforms (e.g., Google services)
• May produce false positives due to the large number of sites checked
• Requires more setup and dependencies

Code Comparison

Sherlock (Python):

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

GHunt (Python):

def ghunt(email):
    gaia_id = get_gaia_id(email)
    if gaia_id:
        profile = get_google_profile(gaia_id)
        print(f"Google Profile: {profile}")

Key Differences

• Sherlock focuses on username searches across multiple platforms
• GHunt specializes in Google account information retrieval
• Sherlock is more suitable for general OSINT, while GHunt is tailored for Google-specific investigations
• GHunt provides more detailed information about Google accounts, including profile data and linked services
• Sherlock's results are typically limited to account existence, while GHunt can extract additional user details

Pros of EagleEye

• Supports multiple social media platforms (Facebook, Instagram, Twitter, etc.)
• Provides facial recognition capabilities for cross-platform searching
• Offers a more comprehensive approach to social media OSINT

Cons of EagleEye

• Less focused on Google-specific data extraction
• May require more setup and dependencies due to its broader scope
• Potentially slower processing time due to multi-platform analysis

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

GHunt:

def get_google_account_info(email):
    account_info = {}
    account_info['name'] = get_name(email)
    account_info['profile_pic'] = get_profile_pic(email)
    account_info['last_seen'] = get_last_seen(email)
    return account_info

EagleEye offers a broader approach to social media intelligence gathering, supporting multiple platforms and utilizing facial recognition. However, it may be less efficient for Google-specific data extraction compared to GHunt. GHunt focuses specifically on Google account information, potentially providing more detailed and targeted results for Google-related OSINT. The code comparison illustrates EagleEye's multi-platform approach versus GHunt's Google-centric functionality.

Pros of Maigret

• Supports a wider range of platforms and services (500+) for OSINT
• Offers more detailed output and reporting options
• Actively maintained with frequent updates

Cons of Maigret

• May require more setup and dependencies
• Can be slower due to the large number of services it checks
• Less focused on Google-specific information

Code Comparison

GHunt (Python):

def get_gaia_id(email):
    res = requests.get(f"https://people-pa.googleapis.com/_/lookup/lookup?email={email}")
    data = json.loads(res.text.replace(")]}'\n\n", ""))
    return data[0][0][2]

Maigret (Python):

async def check_username(username, site):
    url = site['check_uri'].format(username=username)
    response = await self.request(url=url, method=site.get('method', 'GET'))
    return self.check_response_valid(response, site)

Both projects use Python for their core functionality, but GHunt focuses on Google-specific APIs, while Maigret implements a more generic approach for checking usernames across various platforms.

Pros of social-analyzer

• Supports a wider range of social media platforms (300+)
• Provides a web interface for easier use
• Offers both CLI and API options for integration

Cons of social-analyzer

• Less focused on Google-specific data
• May require more setup and dependencies
• Potentially slower due to broader scope

Code Comparison

social-analyzer:

def check_user(username, sites='all', output='pretty', filter='all', timeout=10, method='all'):
    # Implementation for checking user across multiple platforms

GHunt:

def hunt(email):
    # Implementation for gathering Google account information

Key Differences

GHunt focuses specifically on Google account information, while social-analyzer covers a broader range of social media platforms. GHunt is more specialized and potentially more in-depth for Google-related data, whereas social-analyzer offers a wider scope but may sacrifice some depth for breadth.

GHunt is primarily a command-line tool, while social-analyzer provides both CLI and web interface options. This makes social-analyzer potentially more accessible to non-technical users.

Both tools serve similar purposes in OSINT (Open Source Intelligence) gathering, but their approaches and target platforms differ significantly. The choice between them would depend on the specific requirements of the investigation and the platforms of interest.

Pros of holehe

• Supports a wider range of websites and services (over 120)
• Faster execution due to asynchronous requests
• Lightweight and easy to install with pip

Cons of holehe

• Limited to email-based searches
• Less detailed information compared to GHunt's comprehensive Google account data
• May trigger security alerts on some services due to rapid requests

Code Comparison

holehe:

async def instagram(email):
    try:
        async with aiohttp.ClientSession() as session:
            async with session.get("https://www.instagram.com/accounts/web_create_ajax/attempt/", timeout=10) as response:
                if response.status == 200:
                    return {"exists": True, "emailrecovery": None, "phoneNumber": None, "others": None}
    except Exception:
        pass
    return False

GHunt:

def get_account_info(gaiaID):
    url = f"https://people-pa.googleapis.com/v2/people/{gaiaID}?personFields=metadata,photos,names,emailAddresses,phoneNumbers,addresses,birthdays,genders,occupations"
    headers = {"X-Goog-Api-Key": API_KEY}
    req = requests.get(url, headers=headers)
    data = json.loads(req.text)
    return data

The code snippets show different approaches: holehe focuses on individual service checks, while GHunt leverages Google's API for comprehensive account information.

Pros of snoop

• Supports a wider range of social networks and websites (400+)
• Provides more detailed search results, including geolocation data
• Offers a user-friendly GUI in addition to CLI

Cons of snoop

• Primarily focused on Russian-language platforms and users
• Less specialized in Google account investigations
• May require more setup and dependencies

Code Comparison

snoop:

def start(self, username, site):
    self.username = username
    self.site = site
    self.url = self.site['url'].format(username=self.username)
    self.error_type = "message"
    self.error_code = "status_code"

GHunt:

def get_account_info(email):
    gaia_id = get_gaia_id(email)
    if gaia_id:
        return get_user_data(gaia_id)
    return None

Key Differences

• snoop is more versatile for general OSINT across multiple platforms
• GHunt specializes in Google account investigations
• snoop offers a GUI, while GHunt is CLI-only
• GHunt focuses on email-based searches, while snoop uses usernames
• snoop has a larger community and more frequent updates

Both tools are valuable for OSINT, but their focus and use cases differ. Choose based on your specific investigation needs and target platforms.