
Security News
Open Source CAI Framework Handles Pen Testing Tasks up to 3,600× Faster Than Humans
CAI is a new open source AI framework that automates penetration testing tasks like scanning and exploitation up to 3,600× faster than humans.
evvnt-submission-form-angular-rails
Advanced tools
evvnt-submission-form-angular packaged for Rails assets pipeline.
Add the following to your gemfile:
gem "evvnt-submission-form-angular-rails"
Add the following directive to your Javascript manifest file (application.js):
//= require evvnt-submission-form-angular
(or, to application.coffee)
#= require evvnt-submission-form-angular
Add the following directive to your stylesheets manifest file (application.css)
*= require evvnt-submission-form
Add the following element to the html file you want the form to appear in at the place you want it to appear:
<evvnt-submission-form/>
git checkout -b my-new-feature
)git commit -am 'Add some feature'
)git push origin my-new-feature
)Changes to the original javascript module can be pulled into this gem repo with the following command:
rake fetch
remember to then commit and push the changes before rebuilding and releasing the new gem version.
FAQs
Unknown package
We found that evvnt-submission-form-angular-rails demonstrated a not healthy version release cadence and project activity because the last version was released a year ago. It has 1 open source maintainer collaborating on the project.
Did you know?
Socket for GitHub automatically highlights issues in each pull request and monitors the health of all your open source dependencies. Discover the contents of your packages and block harmful activity before you install or update your dependencies.
Security News
CAI is a new open source AI framework that automates penetration testing tasks like scanning and exploitation up to 3,600× faster than humans.
Security News
Deno 2.4 brings back bundling, improves dependency updates and telemetry, and makes the runtime more practical for real-world JavaScript projects.
Security News
CVEForecast.org uses machine learning to project a record-breaking surge in vulnerability disclosures in 2025.