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Application security is no longer an afterthought, but a requirement. Modern applications are often available on various devices and connected to many different networks and to the cloud, which inevitably increases their attack surface and vulnerabilities to threats and security breaches. There is growing pressure and incentive not only to ensure security at the network level, but also within the applications themselves. One of the reasons for this is that hackers are preying on applications today more than ever. Application security testing can reveal weaknesses at the application level, helping to prevent hacker attacks.

Glog project is focused on research and development of a solution that can give remediation advice for security vulnerabilities in software code based on context. What is more, it is capable of automatically fixing those vulnerabilities. We are developing such a solution based on machine learning and AI. Agility in software security is becoming a reality!

It’s estimated that 90 percent of security incidents result from attackers exploiting well-known software security vulnerabilities. Resolving those issues early in development could reduce the security risks that many organizations face today. A number of technologies and tools are available to help catch security flaws before they’re baked into a final software release. These include SAST, SCA, IAST, DAST, VAPT, and RASP.

In practice, however, these solutions require a significant time investment. You develop your software and scan it for security vulnerabilities with static, dynamic, interactive (SAST, IAST, DAST), or other security testing tools. They report many potential vulnerabilities, which your developers need to analyze and fix. Then you re-scan, find some old and some new vulnerabilities, then remediate again. Rinse and repeat. This takes a lot of time, creates friction between teams, and jeopardizes your delivery timelines. If you deliver and deploy vulnerable code that can be breached, the damage could be huge and your reputation ruined.

Sounds familiar, doesn’t it?

Now imagine a solution that can triage issues, flag false positives, and then give remediation advice for real vulnerabilities or even automatically fix the security vulnerabilities in your code without bothering your development teams.

Sounds interesting?

We are developing such a solution based on machine learning and AI. Agility in software security is becoming a reality!

Please contact us at info@glog.ai to learn more about Glog.

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