Helped to decrease the overall false positive rate.

We use the solution to detect any secret exposure.

The overall breadth of the solution is good. It's been able to detect most of the secrets that we have.

The accuracy of the solution is generally good, but we have had a number of false positives. For example, sometimes we would commit a test secret, and it would not follow the action of a secret. This is because the secret contained a prefix that is commonly used in passwords, such as "password". We have been able to take action to suppress these false positives moving forward.

The solution helps to quickly prioritize remediation. When we go back to the historical scan, it can tell us not only what vulnerabilities were exposed, but also the general risk level of each vulnerability. This allows us to prioritize remediation efforts and focus on the more critical vulnerabilities first.

The solution helped to decrease the overall false positive rate. We have been able to decrease the number of false positives by about seven percent. When we receive alerts now, they are usually general alerts. We do not receive alerts that are specific to a door without the pull being put in place when we investigate.

The solution increased our secret detection rate by around 80 percent.

We detected a security issue, and we were able to fix it in the system within half a day. This was possible because we reduced the number of follow-up steps required. The solution saved our security team about 25 percent of their time. This means that we probably removed about a week's worth of incident management work. This is a significant improvement in security, and it saved our team a lot of time.

The solution also helped reduce our mean time to remediation.

At the start, historical scanning was very useful because it was the first time we had done it. It allowed us to see how many secrets we had exposed. If we had only focused on current secrets, we would have missed all the secrets that had been committed in the past. So, initially, the historical scan was really useful.

Presently, we find the pre-commit hooks more useful. These hooks allow us to set up a local development environment where we can scan for secrets before we commit them to the repository. This saved us a lot of time.

It took us a while to get new patterns introduced into the pattern reporting process. If there is a way to automate this process so that we can include our own patterns in our repositories, that would be very useful.

The authentication process could be improved. A single sign-on system would be very helpful.

I have been using GitGuardian Internal Monitoring for one and a half years.

The solution is stable.

The solution is scalable, so we can create instances for each scan that we run. This means that we will never have any issues with load or performance. We have 100 end users the utilize the solution.

The technical support has been very helpful. The system is also pretty intuitive, so we haven't had to contact them very often.

We have seen a 10 percent return on investment. Resource-wise, creating a secret once it has been detected is a significant undertaking. Early detection has saved a lot of time, and I think there would be various penalties. Theoretically, if we continued to explore secrets, we could also save and compromise.

I compared the solution to a couple of other solutions, and I think it is very competitively priced.

I give GitGuardian Internal Monitoring a seven out of ten. The solution is really good, but the false positives that we had to work with lower the solution's overall score.

When we first started using the solution, we had to address some areas quickly. We had pushed through some public-facing features because we wanted to start working in the open. However, this prompted us to realize that we weren't quite ready to do that. So we had to make all of our clusters private again, or as private as possible. The thought of working in the open had to be reviewed at the start.

The solution does not require maintenance. It is used extensively and is part of our security check pipeline. It is included as part of the pipeline in any repository that is created. It is also included in the repository itself. Each project is included as a pre-commit process. Additionally, it is included in our deployment pipeline because it is well integrated into our productivity tools. 

Secret detection is a very important part of a security program for application development. It gives us the confidence to commit our work to a shared environment, especially if we want to make it public. Secret detection helps to ensure that confidential information is not exposed.

For those using an open-source tool, I would suggest pointing out what sort of support they might need. If they're comfortable using it on their own, then that's fine. But if they need support, it would be helpful to have a support package available.

People should do a proof of concept first because the way it will be configured for them might be different. I don't know if we can figure it out for sales for another organization. So, having a proof of concept to fully understand how it will work best for them is useful.