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Security scans generate hundreds of findings. Security teams manually triage each one while developers wait for approval to deploy. Most findings are false positives or low-risk issues, but identifying the real threats requires expertise and time. AI can prioritize findings by actual exploitability and auto-remediate common vulnerabilities, allowing security teams to focus on the threats that matter.

The goal of the exercise was to observe how a new employee would react to the demands of the CEO. From the perspective of an adversary, the goal was to compromise GitLab.com by impersonating the CEO, and then demand that an employee with privileged access install an authorization key, controlled by the Red Team, to production servers. The expected value of this basic exercise was to identify areas of improvement and level set on our current security stance. It's a starting point to allow us to iterate and build upon. Ideally, we hoped our chosen target would report the incident to the Security

From my perspective, I expected Target0 and Target1 to report the issue and Security Operations to respond to the incident. The Red Team’s goal should be about empowering people to champion cybersecurity challenges and solutions. We may do that through adversarial means to highlight problems, but it should always be for the benefit of the employees, customer, and company. I feel like some of us in the industry forget that from time to time. Outside of the exercise, I learned the importance of iteration and a strategic concept GitLab employs called Breadth over Depth. The idea is to iterate as