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Description
FuzzDB was developed to enhance the chances of identifying security vulnerabilities in applications through dynamic testing methods. As the first and most extensive open repository of fault injection patterns, along with predictable resource locations and regex for server response matching, it serves as an invaluable resource. This comprehensive database includes detailed lists of attack payload primitives aimed at fault injection testing. The patterns are organized by type of attack and, where applicable, by the platform, and they are known to lead to vulnerabilities such as OS command injection, directory listings, directory traversals, source code exposure, file upload bypass, authentication bypass, cross-site scripting (XSS), HTTP header CRLF injections, SQL injection, NoSQL injection, and several others. For instance, FuzzDB identifies 56 patterns that might be interpreted as a null byte, in addition to offering lists of frequently used methods and name-value pairs that can activate debugging modes. Furthermore, the resource continuously evolves as it incorporates new findings and community contributions to stay relevant against emerging threats.
Description
ToothPicker serves as an innovative in-process, coverage-guided fuzzer specifically designed for iOS, focusing on the Bluetooth daemon and various Bluetooth protocols. Utilizing FRIDA as its foundation, this tool can be tailored to function on any platform compatible with FRIDA. The repository also features an over-the-air fuzzer that showcases an example implementation for fuzzing Apple's MagicPairing protocol through InternalBlue. Furthermore, it includes the ReplayCrashFile script, which aids in confirming any crashes identified by the in-process fuzzer. This simple fuzzer operates by flipping bits and bytes in inactive connections, lacking coverage or injection, yet it serves effectively as a demonstration and is stateful. It requires only Python and Frida to operate, eliminating the need for additional modules or installations. Built upon the frizzer codebase, it's advisable to establish a virtual Python environment for optimal performance with frizzer. Notably, with the introduction of the iPhone XR/Xs, the PAC (Pointer Authentication Code) feature has been implemented. This advancement underscores the necessity for continuous adaptation of fuzzing tools like ToothPicker to keep pace with evolving iOS security measures.
API Access
Has API
API Access
Has API
Pricing Details
Free
Free Trial
Free Version
Pricing Details
Free
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
FuzzDB
Website
github.com/fuzzdb-project/fuzzdb
Vendor Details
Company Name
Secure Mobile Networking Lab
Website
github.com/seemoo-lab/toothpicker