Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Everyone talks about it, now one knows how others do it. Until now. Read on…

Every pipeline shift introduces a new blind spot. SAST catches coding flaws, and SCA catches dependency risks; however, as delivery moves to CI/CD, new risks have emerged, not in the code itself, but in how it is executed. From broken access controls and authentication drift to logic flaws behind feature flags, these threats show up in production. Continuous DAST in CI/CD pipelines isn’t just “another layer” but a runtime check that’s most likely to catch what gets exploited.

As generative AI tools like ChatGPT, Claude, and others become increasingly integrated into enterprise workflows, a new security imperative has emerged: system prompt hardening. A system prompt is a set of instructions given to an AI model that defines its role, behavior, tone, and constraints for a session. It sets the foundation for how the model responds to user input and remains active throughout the conversation.

In 2020, a DevOps team at a mid-sized fintech startup almost lost its entire source code. A failed container update caused a cascading failure in their self-hosted GitLab instance. The backup was… somewhere. No one checked it in weeks. The recovery process took three days. The cost was around $70,000 in downtime and customer compensation. The event wasn’t a matter of not having a backup strategy. It was a matter of assuming someone, somewhere, had run the proper function at the right time.