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Description
EditApp AI is a cutting-edge mobile application designed for photo editing that harnesses the power of artificial intelligence to elevate standard images into stunning works of art. It presents three main modes for user engagement. With this app, users can incorporate whimsical elements into their pictures, like adding a unicorn to their backyard or placing historical figures in contemporary scenes. The application offers extensive customization options, allowing individuals to modify hairstyles, clothing, or facial features to create their ideal appearances. The background mode makes it easy to swap out photo backdrops, enabling users to transport their subjects to a variety of settings, whether tranquil landscapes or advanced futuristic environments. Furthermore, EditApp AI includes functionalities such as AI-created avatars, enhancements for selfies, and the capability to inject surprising elements into photos, like animals or objects, simply by articulating their descriptions. Users can also enlarge their images by zooming out, with the AI smartly filling in the newly created space to ensure a cohesive look. This application truly opens up a world of creative possibilities for anyone looking to elevate their photographic endeavors.
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
Free
Free Trial
No
Free Version
Yes
Pricing Details
Free
Free Trial
No
Free Version
Yes
Deployment
Web-Based
No
On-Premises
No
iPhone App
Yes
iPad App
Yes
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
Yes
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
AI Research Group Limited
Country
United States
Website
editapp.ai/
Vendor Details
Company Name
Battelle
Website
github.com/Battelle/afl-unicorn