ChainGuard, a new open-source security project, is hoping to improve the quality of Software Bill-of-Materials (SBOM)s by training models to detect known software vulnerabilities. SBOMs provide valuable information about the components and dependencies used by a particular piece of software, which can be used to recognize potential risks and security gaps. However, the quality of SBOMs is often poor, leaving software vulnerable to attack.
ChainGuard is a project developed by researchers at the University of Illinois at Urbana-Champaign and the University of Maryland. The project uses machine learning algorithms to generate training models that detect known software vulnerabilities in SBOMs. By providing better coverage and better accuracy, ChainGuard can help software developers create secure software more quickly and easily.
The project is still in its early stages, but the researchers are hopeful that it will have a significant impact on software security. ChainGuard aims to make it easier for developers to create secure software, while also making it easier for organizations to recognize potential vulnerabilities in their software. By improving the quality of SBOMs, software applications will be less susceptible to attack.
ChainGuard is an important step toward improving the security of software applications. By training models to detect known vulnerabilities, organizations can better protect their software from cyber attackers. As the project matures, it could prove to be an invaluable resource for software developers and organizations alike.
This Cyber News was published on www.securityweek.com. Publication date: Sun, 22 Jan 2023 10:48:00 +0000