Pros of SecLists

• Comprehensive collection of wordlists for various security testing scenarios
• Regularly updated with community contributions
• Well-organized directory structure for easy navigation

Cons of SecLists

• Primarily static data, lacking active scanning or exploitation tools
• May require additional tools or scripts to utilize the wordlists effectively
• Large repository size can be overwhelming for beginners

Code Comparison

SecLists is primarily a collection of wordlists and doesn't contain executable code. pentest-tools, on the other hand, includes various Python scripts for penetration testing. Here's an example from pentest-tools:

def testURL( url ):
    time.sleep( 0.01 )
    sys.stdout.write( 'progress: %d/%d\r' %  (t_multiproc['n_current'],t_multiproc['n_total']) )
    t_multiproc['n_current'] = t_multiproc['n_current'] + 1

    try:
        r = requests.get( url, timeout=2, verify=False )
        return url
    except Exception as e:
        sys.stdout.write( "%s[-] error occurred: %s%s\n" % (fg('red'),e,attr(0)) )
        return None

This code snippet demonstrates a function for testing URLs, which is not present in SecLists as it focuses on providing data rather than functionality.

Pros of PayloadsAllTheThings

• More comprehensive collection of payloads and techniques for various attack vectors
• Better organized with clear categorization of different security topics
• Regularly updated with contributions from the security community

Cons of PayloadsAllTheThings

• Lacks specific tools or scripts for direct use in penetration testing
• May be overwhelming for beginners due to the vast amount of information

Code Comparison

PayloadsAllTheThings (SQL Injection example):

' OR '1'='1
' OR 1 -- -
' OR '1'='1' #

pentest-tools (SQL Injection script excerpt):

def inject(url, data, headers):
    for payload in payloads:
        r = requests.post(url, data=data.replace("INJECT", payload), headers=headers)
        if "error in your SQL syntax" in r.text:
            print("Possible SQL Injection found!")

PayloadsAllTheThings focuses on providing a wide range of payload examples, while pentest-tools offers more practical scripts for active testing. PayloadsAllTheThings is better suited for reference and learning, whereas pentest-tools provides ready-to-use tools for penetration testers.

Pros of PEASS-ng

• More comprehensive and actively maintained privilege escalation toolkit
• Supports multiple operating systems (Windows, Linux, macOS)
• Includes automated enumeration scripts for faster reconnaissance

Cons of PEASS-ng

• Larger codebase, potentially more complex to use or modify
• May generate more noise during scans, increasing detection risk
• Requires more setup and dependencies compared to simpler scripts

Code Comparison

PEASS-ng (LinPEAS example):

if [ "$MACPEAS" ]; then
    print_2title "System Info"
    system_info
else
    print_2title "Operative system"
    printf $ITALIC" Ubuntu\n"$NC
    (cat /proc/version || uname -a ) 2>/dev/null | sed -E "s,$kernelDCW_Ubuntu_Precise_1,${C}[1;31;103m&${C}[0m," | sed -E "s,$kernelDCW_Ubuntu_Precise_2,${C}[1;31;103m&${C}[0m," | sed -E "s,$kernelDCW_Ubuntu_Trusty_1,${C}[1;31;103m&${C}[0m," | sed -E "s,$kernelDCW_Ubuntu_Trusty_2,${C}[1;31;103m&${C}[0m," | sed -E "s,$kernelDCW_Ubuntu_Xenial,${C}[1;31;103m&${C}[0m," | sed -E "s,$kernelDCW_Ubuntu_Bionic,${C}[1;31;103m&${C}[0m," | sed -E "s,$kernelDCW_Ubuntu_Focal,${C}[1;31;103m&${C}[0m," | sed -E "s,$kernelDCW_Ubuntu_Focal2,${C}[1;31;103m&${C}[0m,"
fi

pentest-tools (subdomain_finder.py example):

def get_subdomains(domain):
    url = 'https://crt.sh/?q=%.{d}&output=json'.format(d=domain)
    response = requests.get(url)
    content = response.content.decode('utf-8')
    data = json.loads(content)
    return set([name_value['name_value'] for name_value in data])

The PEASS-ng code snippet shows a more complex system information gathering process, while the pentest-tools example demonstrates a simpler subdomain enumeration function.

Pros of gobuster

• Focused tool for directory/file, DNS, and vhost bruteforcing
• Written in Go, offering better performance and cross-platform compatibility
• Active development with regular updates and community support

Cons of gobuster

• Limited to specific bruteforcing tasks, less versatile than pentest-tools
• Requires Go runtime environment for compilation and execution
• Steeper learning curve for users unfamiliar with Go-based tools

Code comparison

pentest-tools (Python):

def bruteforce_dir(url, wordlist):
    for word in wordlist:
        full_url = f"{url}/{word}"
        response = requests.get(full_url)
        if response.status_code == 200:
            print(f"Found: {full_url}")

gobuster (Go):

func bruteforceDir(url string, wordlist []string) {
    for _, word := range wordlist {
        fullURL := fmt.Sprintf("%s/%s", url, word)
        resp, err := http.Get(fullURL)
        if err == nil && resp.StatusCode == 200 {
            fmt.Printf("Found: %s\n", fullURL)
        }
    }
}

Both repositories offer valuable tools for penetration testing, but they cater to different needs. pentest-tools provides a diverse set of Python scripts for various pentesting tasks, while gobuster focuses on efficient bruteforcing operations implemented in Go. The choice between them depends on the specific requirements of the penetration testing project and the user's familiarity with the respective programming languages and ecosystems.

Pros of ffuf

• Focused tool for web fuzzing with high performance
• Written in Go, offering cross-platform compatibility and easy installation
• Actively maintained with frequent updates and improvements

Cons of ffuf

• Limited to web fuzzing, unlike pentest-tools' broader scope
• Steeper learning curve for users new to fuzzing tools
• Less variety in functionality compared to pentest-tools' diverse script collection

Code Comparison

ffuf (main fuzzing functionality):

for scanner.Scan() {
    if err := ffuf.NewJob(scanner.Text()).RunJob(); err != nil {
        errs <- err
    }
}

pentest-tools (example script):

def scan_port(ip, port):
    sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
    result = sock.connect_ex((ip, port))
    sock.close()
    return result == 0

Summary

ffuf is a specialized, high-performance web fuzzing tool written in Go, while pentest-tools is a collection of various penetration testing scripts in Python. ffuf excels in its specific domain but has a narrower focus, whereas pentest-tools offers a broader range of functionalities for different penetration testing tasks. The choice between them depends on the specific needs of the penetration tester and the scope of the assessment.

Pros of Nuclei

• More comprehensive and actively maintained vulnerability scanner
• Extensive template library for various security checks
• Supports multiple protocols (HTTP, DNS, TCP, etc.)

Cons of Nuclei

• Steeper learning curve due to its more complex architecture
• Requires writing custom templates for specific use cases

Code Comparison

Nuclei (YAML-based template):

id: example-template
info:
  name: Example Template
  severity: info
requests:
  - method: GET
    path:
      - "{{BaseURL}}/example"

pentest-tools (Python script):

import requests

def check_vulnerability(url):
    response = requests.get(url + "/example")
    if "vulnerable" in response.text:
        print("Vulnerability found!")

Key Differences

• Nuclei uses a template-based approach, while pentest-tools consists of individual Python scripts
• Nuclei offers more flexibility and extensibility for various security checks
• pentest-tools provides simpler, standalone tools for specific pentesting tasks

Use Cases

Nuclei:

• Comprehensive vulnerability scanning
• Automated security assessments
• Custom security checks using templates

pentest-tools:

• Quick, targeted pentesting tasks
• Simple script-based approach for specific security checks
• Easier integration into existing Python-based workflows