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What is Wapiti?
Wapiti is a specialized tool aimed at scanning for security vulnerabilities within web applications. It effectively evaluates the security posture of both websites and web applications without needing to access the source code, conducting "black-box" scans that focus on navigating through the deployed application's web pages to identify potentially vulnerable scripts and forms subject to data injection. By creating a comprehensive list of URLs, forms, and their respective inputs, Wapiti operates like a fuzzer, inserting various payloads to probe for vulnerabilities in scripts and also seeks out files on the server that might present security risks. The tool is adaptable, facilitating attacks through both GET and POST HTTP methods, while also managing multipart forms and allowing for payload injection into uploaded filenames. Alerts are generated when Wapiti identifies unusual occurrences, such as server errors or timeouts, which could indicate a security issue. Furthermore, Wapiti distinguishes between permanent and reflected XSS vulnerabilities, offering users detailed reports on identified vulnerabilities which can be exported in various formats, including HTML, XML, JSON, TXT, and CSV. This extensive functionality makes Wapiti a robust and comprehensive solution for conducting thorough web application security assessments. Additionally, its user-friendly interface allows security professionals to streamline their vulnerability management process effectively.
What is ToothPicker?
ToothPicker is an advanced in-process, coverage-guided fuzzer that is specifically tailored for iOS, with a primary focus on the Bluetooth daemon and a variety of Bluetooth protocols. Built on the FRIDA framework, this tool can be customized to operate on any platform that supports FRIDA. Additionally, the repository includes an over-the-air fuzzer that provides a practical example of fuzzing Apple's MagicPairing protocol via InternalBlue. It also comes with the ReplayCrashFile script, which helps verify any crashes detected by the in-process fuzzer. This straightforward fuzzer works by altering bits and bytes in inactive connections and, while it does not incorporate coverage or injection methods, it effectively demonstrates its functionality in a stateful manner. Only requiring Python and Frida to run, it dispenses with the need for further modules or installations. Since it is based on the frizzer codebase, it is recommended to create a virtual Python environment to ensure optimal performance with frizzer. The introduction of the iPhone XR/Xs has brought about the implementation of the PAC (Pointer Authentication Code) feature, highlighting the importance of continuously evolving fuzzing tools like ToothPicker to align with the changing landscape of iOS security protocols. As technology advances, maintaining and updating such tools becomes crucial for security researchers and developers alike.
Integrations Supported
Drupal
Google Chrome
Google Sheets
HTML
JSON
Microsoft Excel
Mozilla Firefox
Python
SQL
WordPress
Integrations Supported
Drupal
Google Chrome
Google Sheets
HTML
JSON
Microsoft Excel
Mozilla Firefox
Python
SQL
WordPress
API Availability
Has API
API Availability
Has API
Pricing Information
Free
Free Trial Offered?
Free Version
Pricing Information
Free
Free Trial Offered?
Free Version
Supported Platforms
SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux
Supported Platforms
SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Company Facts
Organization Name
Wapiti
Company Website
wapiti-scanner.github.io
Company Facts
Organization Name
Secure Mobile Networking Lab
Company Website
github.com/seemoo-lab/toothpicker