Trust is hard to earn but necessary for any successful relationship. As organizations build the systems to support Zero Trust, they find themselves balancing security and functionality across their operations. Incident Response and Network Operations in particular can be full of traumatic experiences, and as we sink into those moments the typical responses are freeze, flight, or fight.

If you’ve been following our series on the PEAK threat hunting framework, you might already know that the purpose of threat hunting isn’t just to find security incidents your automated detection systems missed. Finding incidents is more like a helpful side effect. The real reason to hunt is to drive improvement to your security posture over time.

The recent Trustwave SpiderLabs report, Cybersecurity in the Healthcare Industry: Actionable Intelligence for an Active Threat Landscape, offers a detailed look at the typical attack flow used in a variety of cyberattacks. The attack flow discussed in the report focused on what a healthcare organization might face, but for the most part, attack flows stay the same regardless of the vertical being attacked.

The rise of remote work and the move to the cloud, as well as the rising rate and increased complexity of cyber attacks, have fundamentally changed the security landscape. Set-it-and-forget it tools are no longer enough. To truly protect yourself from modern cyber threats you need 24×7 monitoring, detection and response. However, even that doesn’t look the same anymore.

In terms of unencrypted traffic, several highly used protocols lend themselves to logging and can significantly reduce the burden of packet capture without lowering the fidelity of information or the capabilities of analysts.

Like many concepts at the intersection of software engineering and cybersecurity, threat detection has emerged as a recent candidate to adopt the ‘as-code’ discipline to detection. This is driven by two key factors: Detection as Code is a new paradigm that brings a structured, systematic and flexible methodology for threat detection inspired by the as-code best practice of software engineering, commonly adopted in DevOps and Agile software development frameworks.