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Average Ratings 0 Ratings
Description
Unicorn Hunt was established a few years back to address a significant gap: the job platforms available to the UK startup ecosystem were inadequate, leaving companies with limited options for sourcing new talent online. While one could opt to list a job on a broad, generic board and hope it reaches a suitable candidate, this approach has its drawbacks. Firstly, working at a startup requires a specific mindset, and not everyone is suited to this fast-paced atmosphere, making it difficult to target the appropriate audience through a vast job listing site. Secondly, the costs associated with these platforms can be astronomical. A common struggle in the startup world is financial constraints, which is inherently linked to the term "startup," as many cannot afford to post on an expansive job board or, heaven forbid, engage a recruitment agency. Consequently, Unicorn Hunt was conceived to fulfill the needs of this neglected startup community, all while embracing the whimsical spirit of innovation. By creating a niche platform tailored for startups, it aims to connect the right talent with the right opportunities effectively.
Description
AFL-Unicorn provides the capability to fuzz any binary that can be emulated using the Unicorn Engine, allowing you to target specific code segments for testing. If you can emulate the desired code with the Unicorn Engine, you can effectively use AFL-Unicorn for fuzzing purposes. The Unicorn Mode incorporates block-edge instrumentation similar to what AFL's QEMU mode employs, enabling AFL to gather block coverage information from the emulated code snippets to drive its input generation process. The key to this functionality lies in the careful setup of a Unicorn-based test harness, which is responsible for loading the target code, initializing the state, and incorporating data mutated by AFL from its disk storage. After establishing these parameters, the test harness emulates the binary code of the target, and upon encountering a crash or error, triggers a signal to indicate the issue. While this framework has primarily been tested on Ubuntu 16.04 LTS, it is designed to be compatible with any operating system that can run both AFL and Unicorn without issues. With this setup, developers can enhance their fuzzing efforts and improve their binary analysis workflows significantly.
API Access
Has API
No
API Access
Has API
No
Integrations
No details available.
Integrations
No details available.
Pricing Details
$119.94 per month
Free Trial
No
Free Version
No
Pricing Details
Free
Free Trial
No
Free Version
Yes
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
No
On-Premises
No
iPhone App
No
iPad App
No
Android App
Yes
Windows
Yes
Mac
Yes
Linux
Yes
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
No
Webinars
No
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
Unicorn Hunt
Country
United Kingdom
Website
unicornhunt.io
Vendor Details
Company Name
Battelle
Website
github.com/Battelle/afl-unicorn