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Implementing Automated Secrets Detection for Application Security

Dev & Ops teams from large organizations use thousands of secrets like API keys and other credentials in order to interconnect the building blocks of their applications. As a result, they now have access to more sensitive information than companies can keep track of. The risk is that these secrets are now spreading everywhere.

In this white paper, we look at the implications of secret sprawl, and present solutions for Application Security to further secure the SDLC by implementing automated secrets detection in their DevOps pipeline.

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What you will learn in this white paper

Understanding the benefits of mitigating secrets sprawl

  • What are the threats associated with secrets sprawl?
  • A focus on secrets in source code: why are they so bad?

Challenges associated with secrets sprawl

  1. The git history makes it more complicated than first thought
  2. Enforcing good security practices at the organization level is hard
  3. Homegrown tools and scripts are hard to build, maintain and keep up-to-date

How to implement automated secrets detection

  • Where in the SDLC to implement automated secrets detection?
  • Why is it hard to detect secrets?
  • Remediating exposed secrets

GitGuardian helps these companies bring Dev. Sec. and Ops. together

#1 Security app on GitHub marketplace

Here’s how we are helping developers to secure their code

GitGuardian is a great tool to improve security starting from the development. I greatly appreciated the pre-commit integration that allows developers to very easily prevent accidental commits.

What I like the most about GitGuardian is the ability to automatically scan source code and detect leaked secrets. It has enabled us to add additional security control to our CI/CD pipeline, and enabled us to shift further left in the SDLC by implementing pre-commit hooks for developers to test their code before it is committed.

The perfect GitHub companion! It helps you track any sensitive data you may have shared in the repos, either public or private. Its algorithm is pretty advanced and I've never had any false positives.

We have definitely seen a return on investment when it finds things that are real. We have caught a couple of things before they made it to production, and had they made it to production, that would have been dangerous. For example, AWS secrets, if that ever got leaked, would have allowed people full access to our environment. Just catching two or three of those a year is our return on investment.

Overall, GitGuardian has also helped us develop a security-minded culture. We're serious about shift-left and getting better about code security. I think a lot of people in the organization are getting more mindful about what a hardcoded secret is.

Time to remediation is now in minutes or hours, whereas it used to take days or weeks previously. That's the biggest improvement. Because it is automated and visible to the author, someone from the security team doesn't have to remind them or recheck it. That means the slowdown in the deployment process has definitely been improved by an order of magnitude. There is easily a 30-hour improvement on time to remediation, which is about an 85 percent decrease.

The solution has reduced our mean time to remediation. We are down to less than a day. In the past, without context, knowing who made the commit, or kind of secret it was, sometimes it was taking us a lot longer to determine the impact and what actions needed to be taken.

I can say that tracking down a hardcoded secret, getting it migrated out of source code, getting the secret rotated, and cleaning the Git history took much longer from commit until the full resolution before GitGuardian. We weren't notified until it was too late, but with GitGuardian, we know almost instantly.