Sibyl | A Miasm2 based function divination

by cea-sec Python Version: v0.2 License: GPL-3.0

X-Ray Key Features Code Snippets Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | Sibyl Summary

Sibyl is a Python library. Sibyl has no bugs, it has no vulnerabilities, it has build file available, it has a Strong Copyleft License and it has low support. You can download it from GitHub.

A Miasm2 based function divination.

Support

Quality

Security

License

Reuse

Support

Sibyl has a low active ecosystem.

It has 451 star(s) with 50 fork(s). There are 38 watchers for this library.

It had no major release in the last 12 months.

There are 4 open issues and 19 have been closed. On average issues are closed in 99 days. There are 3 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of Sibyl is v0.2

Quality

Sibyl has 0 bugs and 0 code smells.

Security

Sibyl has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

Sibyl code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

Sibyl is licensed under the GPL-3.0 License. This license is Strong Copyleft.

Strong Copyleft licenses enforce sharing, and you can use them when creating open source projects.

Reuse

Sibyl releases are available to install and integrate.

Build file is available. You can build the component from source.

Installation instructions are not available. Examples and code snippets are available.

Top functions reviewed by kandi - BETA

kandi has reviewed Sibyl and discovered the below as its top functions. This is intended to give you an instant insight into Sibyl implemented functionality, and help decide if they suit your requirements.

Start tracing
Add a memory page
Push an unsigned integer value onto the CPU
Generate test code
Generate check function
Sanitize memory access
Begin execution of functions
Ends the function
Create a test object
Clean the trace
Create a test object from the trace
Return a dict of testcases
Return a mapping of function_prologs to vaddr
Calculate votes for the heuristic
Restores memory and memory
Return the path to the ids file
Return the path to ghidra
Prepare call stack
Mark a function as executed
Restore snapshot
Write a write callback
Callback for read callback
List of stubs
Sets the return address
The pin tracer
Run the pin command

Get all kandi verified functions for this library.

Sibyl Key Features

No Key Features are available at this moment for Sibyl.

Sibyl Examples and Code Snippets

No Code Snippets are available at this moment for Sibyl.

Community Discussions

Trending Discussions on Sibyl

react native FlatList re-renders when elements have been added to the array state

QUESTION

react native FlatList re-renders when elements have been added to the array state

Asked 2021-Oct-23 at 21:25

When I want to change the array state all of the elements in the FlatList gets re-rendered. I have checked other questions with the same problem but nope I wasn't able to solve it. First, the issue was in my main project but because I wasn't able to solve it I created a clear project with the example I gave below but still, the issue persists. On the main project, KeyExtractor was returning a unique id.

...

ANSWER

Answered 2021-Oct-23 at 19:52

A render call will always try to re-render the children of a component.

You can utilize React.memo https://reactjs.org/docs/react-api.html#reactmemo to prevent the re-render of the child component if you are using functional components

Or shouldComponentUpdate for the old school class components https://reactjs.org/docs/react-component.html#shouldcomponentupdate

Source https://stackoverflow.com/questions/69691467

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install Sibyl

You can download it from GitHub.
You can use Sibyl like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.