Security | News, how-tos, features, reviews, and videos
Yes, having the support of a foundation helps, but more important is a solid technological solution to a recognized problem.
Between the rapid release of open source software, and modern OSes preloaded with packages, enterprises are vulnerable to attacks they aren’t even aware of.
The impacts of large language models and AI on cybersecurity range from the good to the bad to the ugly. Here’s what to watch out for, and how to prepare.
Generative AI is already proving helpful across many relatively basic use cases, but how does it hold up when tasked with more technical guidance?
JFrog unveiled a number of new platform capabilities including static application security testing and anti-tampering and compliance checks for software releases.
By allowing the use of AI tools proven to be safe, but requiring them to be used within explicit guidelines, you can alleviate both employee frustration and organizational risk.
Cloud security is largely siloed by cloud provider. Enterprises are demanding strategic approaches for complex distributed multicloud deployments.
AI-driven coding is now in wide use, but we may not know all the risks of using it until the damage has been done. Think security problems and code that wastes resources.
From package signing to SBOMs to new developer toolchains, the pieces for securing the software supply chain are starting to come together.
DevSecOps system validates incoming software packages against JFrog’s security research library to establish a repository of trustworthy components for software developers to use.