Pros of gau

• Supports multiple sources (Wayback Machine, AlienVault's OTX, Common Crawl)
• Offers concurrent fetching for faster results
• Provides filtering options (e.g., by status code, content-length)

Cons of gau

• May produce more noise due to multiple sources
• Requires more configuration to fine-tune results
• Potentially higher resource usage due to concurrent fetching

Code Comparison

waybackurls:

resp, err := http.Get(fmt.Sprintf("http://web.archive.org/cdx/search/cdx?url=%s/*&output=json&fl=original&collapse=urlkey", url))

gau:

urls, err := gau.FromDomains([]string{domain}, gau.WithThreads(threads), gau.WithProviders(providers...))
for url := range urls {
    fmt.Println(url)
}

Both tools aim to retrieve historical URLs, but gau offers more flexibility and sources at the cost of potential complexity. waybackurls is simpler and focuses solely on the Wayback Machine, making it easier to use for basic tasks. The choice between them depends on the specific requirements of your project and the depth of URL discovery needed.

Pros of hakrawler

• Crawls websites in real-time, potentially discovering new or dynamic content
• Supports custom headers and cookies for authenticated crawling
• Offers various output formats (JSON, URLs only, etc.)

Cons of hakrawler

• May be slower for large-scale reconnaissance compared to waybackurls
• Requires active crawling, which can be more intrusive and detectable
• Potentially less comprehensive for historical data compared to Wayback Machine

Code comparison

waybackurls:

resp, err := http.Get(fetchURL)
if err != nil {
    return
}
defer resp.Body.Close()

hakrawler:

c := colly.NewCollector(
    colly.UserAgent("hakrawler"),
    colly.MaxDepth(depth),
)
c.OnHTML("a[href]", func(e *colly.HTMLElement) {
    link := e.Attr("href")
    // Process link
})

hakrawler uses the Colly framework for crawling, while waybackurls focuses on fetching data from the Wayback Machine API. hakrawler's approach allows for more flexible and interactive crawling, but waybackurls is more efficient for retrieving historical URL data from a single source.

Pros of Katana

• More comprehensive crawling capabilities, including JavaScript rendering
• Faster performance due to concurrent crawling
• Supports multiple output formats (JSON, HTML, etc.)

Cons of Katana

• More complex setup and usage compared to Waybackurls
• Requires more system resources due to its advanced features
• May produce more noise in results, requiring additional filtering

Code Comparison

Waybackurls:

echo "example.com" | waybackurls

Katana:

katana -u https://example.com

Feature Comparison

Waybackurls:

• Simple and straightforward URL extraction from Wayback Machine
• Lightweight and easy to integrate into scripts
• Focuses solely on historical URL data

Katana:

• Active web crawling with customizable depth and scope
• Ability to handle modern web applications and single-page apps
• Includes additional features like screenshot capture and custom headers

Use Case Scenarios

Waybackurls is ideal for:

• Quick historical URL discovery
• Integration into simple recon workflows
• Low-resource environments

Katana is better suited for:

• Comprehensive web application mapping
• Discovering dynamically generated content
• Advanced reconnaissance with detailed output

Both tools have their place in a security researcher's toolkit, with Waybackurls offering simplicity and Katana providing more advanced crawling capabilities.

Pros of gospider

• More comprehensive crawling capabilities, including JavaScript rendering
• Supports multiple output formats (JSON, Markdown, CSV)
• Offers additional features like form submission and custom headers

Cons of gospider

• More complex to use due to additional features and options
• Potentially slower execution for simple URL extraction tasks
• Requires more system resources for full functionality

Code comparison

waybackurls:

func getWaybackURLs(domain string, results chan<- string) {
    resp, err := http.Get(fmt.Sprintf("http://web.archive.org/cdx/search/cdx?url=%s/*&output=json&fl=original&collapse=urlkey", domain))
    if err != nil {
        return
    }
    defer resp.Body.Close()
    // ... (processing and sending results)
}

gospider:

func (s *Spider) Start() error {
    for _, site := range s.C.Sites {
        go func(site string) {
            s.crawl(site)
        }(site)
    }
    s.wait()
    return nil
}

The code snippets highlight the different approaches: waybackurls focuses on retrieving URLs from the Wayback Machine, while gospider implements a more complex crawling mechanism with concurrent processing.

Pros of Amass

• More comprehensive subdomain enumeration, using multiple data sources and techniques
• Actively maintained with regular updates and new features
• Supports advanced features like DNS resolution and certificate transparency checks

Cons of Amass

• Steeper learning curve due to more complex functionality
• Requires more system resources and may be slower for simple tasks
• Can be overkill for basic URL discovery needs

Code Comparison

Waybackurls (simple usage):

echo example.com | waybackurls

Amass (basic subdomain enumeration):

amass enum -d example.com

Summary

Waybackurls is a lightweight tool focused on retrieving URLs from the Wayback Machine, making it ideal for quick and simple URL discovery tasks. Amass, on the other hand, is a more powerful and comprehensive tool for subdomain enumeration and asset discovery, offering a wide range of features and data sources. While Amass provides more thorough results, it comes with increased complexity and resource requirements. The choice between the two depends on the specific needs of the user and the scope of the project.