Pros of Social-Engineer-Toolkit

• Broader range of attack vectors and tools
• More extensive documentation and community support
• Regularly updated with new features and improvements

Cons of Social-Engineer-Toolkit

• Steeper learning curve due to its extensive feature set
• Less focused on specific phishing techniques compared to Evilginx2
• May require more setup and configuration for certain attacks

Code Comparison

Social-Engineer-Toolkit:

# Example of a phishing attack setup
choice = raw_input(setprompt(["1"], "SET vector (website)"))
if choice == "1":
    web_server = True
    # Start web server and clone the target site
    clone_site(website)

Evilginx2:

// Example of a phishing proxy setup
func (p *Phishlet) AddSubFilter(hostname, subdomain, domain, mime, regexp, replace string) error {
    sf := SubFilter{
        Hostname:  hostname,
        Subdomain: subdomain,
        Domain:    domain,
        Mime:      mime,
        Regexp:    regexp,
        Replace:   replace,
    }
    p.subfilters = append(p.subfilters, sf)
    return nil
}

Pros of MITMf

• More versatile with a wider range of attack modules and plugins
• Supports multiple protocols beyond just HTTP/HTTPS
• Offers more customization options for advanced users

Cons of MITMf

• Less focused on phishing specifically, which may reduce effectiveness for that use case
• Requires more setup and configuration compared to Evilginx2's streamlined approach
• Less actively maintained, with the last update being several years ago

Code Comparison

MITMf (Python):

from core.sslstrip.DnsCache import DnsCache
from core.sslstrip.URLMonitor import URLMonitor

dnscache = DnsCache()
urlMonitor = URLMonitor(dnscache)

Evilginx2 (Go):

type Phishlet struct {
    Name        string
    Author      string
    ProxyHosts  []string
    LandingURL  string
    RedirectURL string
}

Both projects aim to facilitate man-in-the-middle attacks, but their implementations and focus areas differ. MITMf provides a broader toolkit for various attack scenarios, while Evilginx2 specializes in advanced phishing campaigns with a more modern and streamlined approach.

Pros of mitmproxy

• More versatile and can be used for a wider range of network analysis tasks
• Offers a command-line interface, web interface, and Python API for greater flexibility
• Actively maintained with regular updates and a larger community

Cons of mitmproxy

• Requires more technical knowledge to set up and use effectively
• Less focused on phishing attacks, which is the primary purpose of evilginx2
• May require additional configuration for specific use cases

Code Comparison

mitmproxy:

from mitmproxy import http

def request(flow: http.HTTPFlow) -> None:
    if flow.request.pretty_url.startswith("https://example.com"):
        flow.request.headers["Custom-Header"] = "Modified"

evilginx2:

func (p *Phishlet) handleRequest(req *http.Request) {
    if strings.HasPrefix(req.URL.Host, "example.com") {
        req.Header.Set("Custom-Header", "Modified")
    }
}

Both examples show how to modify headers for specific requests, but mitmproxy uses Python and offers a more straightforward API, while evilginx2 uses Go and is more focused on phishing-specific functionality.

Pros of Bettercap

• More versatile, supporting a wide range of network attacks and monitoring capabilities
• Active development with frequent updates and community contributions
• Extensive documentation and user-friendly CLI interface

Cons of Bettercap

• Steeper learning curve due to its broader feature set
• May require more setup and configuration for specific attack scenarios
• Less focused on phishing attacks compared to Evilginx2

Code Comparison

Bettercap (JavaScript module):

var targets = []
var start = function() {
    // ... (code to start the attack)
}

Evilginx2 (Go module):

type Phishlet struct {
    Name        string
    Author      string
    ProxyHosts  []string
    // ... (other struct fields)
}

Both projects use different programming languages and architectures. Bettercap is more modular and extensible, while Evilginx2 is more focused on phishing attacks with a streamlined structure.

Bettercap offers a broader range of network security tools, making it suitable for various penetration testing scenarios. Evilginx2, on the other hand, specializes in advanced phishing techniques, providing a more targeted approach for social engineering assessments.

Pros of Responder

• Simpler setup and usage, making it more accessible for beginners
• Broader attack surface, targeting multiple protocols and services
• Active development with frequent updates and community contributions

Cons of Responder

• Less stealthy, potentially easier to detect by security systems
• Limited to local network attacks, unlike Evilginx2's remote phishing capabilities
• Requires more manual intervention for credential harvesting

Code Comparison

Responder (Python):

def start():
    try:
        server = ThreadingUDPServer(('', 137), NBTNSResponder)
        server.serve_forever()
    except:
        print("[!] Error starting NBT-NS responder")

Evilginx2 (Go):

func (p *Phishlet) GetLureURL(path string) (string, error) {
    b64 := base64.URLEncoding.EncodeToString([]byte(path))
    return fmt.Sprintf("%s?%s=%s", p.cfg.BaseURL, p.cfg.ParamName, b64), nil
}

The code snippets demonstrate the different approaches: Responder focuses on network protocol manipulation, while Evilginx2 emphasizes URL manipulation for phishing attacks.

Pros of Photon

• Focused on web reconnaissance and information gathering
• Lightweight and easy to use for quick scans
• Supports multiple output formats for flexibility

Cons of Photon

• Limited to passive information gathering
• Less sophisticated in terms of attack capabilities
• May require additional tools for comprehensive security testing

Code Comparison

Photon (Python):

def photon(url, level, threads, delay, timeout, cook, headers):
    colors.info('Photon Internet Crawler')
    colors.info('Crawling the target')
    # ... (crawling logic)

Evilginx2 (Go):

func (p *Phishlet) GetLureUrls() []string {
    var ret []string
    for _, l := range p.lures {
        ret = append(ret, l.GetUrl())
    }
    return ret
}

Photon is primarily designed for web crawling and information gathering, making it more suitable for reconnaissance tasks. It's written in Python, which can be easier for beginners to understand and modify.

Evilginx2, on the other hand, is a more advanced tool focused on creating and managing phishing campaigns. It's written in Go, which offers better performance but may have a steeper learning curve.

While both tools can be used for security testing, they serve different purposes and have distinct strengths. Photon excels in passive information gathering, while Evilginx2 is more suited for active phishing simulations and advanced security assessments.