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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.

What is FuzzDB?

FuzzDB was created to improve the likelihood of discovering security vulnerabilities in applications by utilizing dynamic testing techniques. Recognized as the first and largest open repository for fault injection patterns, along with reliable resource locations and regex for matching server responses, it is an essential tool in the field. This extensive database contains comprehensive lists of attack payload primitives specifically designed for fault injection testing. The patterns are categorized by the type of attack and, when applicable, by the specific platform, often revealing vulnerabilities such as OS command injection, directory traversals, source code exposure, file upload bypass, cross-site scripting (XSS), and SQL injections, among others. Notably, FuzzDB highlights 56 patterns that could be interpreted as a null byte and also provides extensive lists of commonly used methods and name-value pairs that may trigger debugging modes. In addition, FuzzDB is continually updated as it integrates new discoveries and contributions from the community to effectively address emerging security threats. This ongoing evolution ensures that users benefit from the latest advancements in vulnerability detection and testing methodologies.

Media

Media

Integrations Supported

BlackArch Linux
NoSQL
OWASP ZAP
Python

Integrations Supported

BlackArch Linux
NoSQL
OWASP ZAP
Python

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

Secure Mobile Networking Lab

Company Website

github.com/seemoo-lab/toothpicker

Company Facts

Organization Name

FuzzDB

Company Website

github.com/fuzzdb-project/fuzzdb

Categories and Features

Categories and Features

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