Bare Metal Cyber

Threat-informed defense starts with a very simple observation: most of us are drowning in alerts, dashboards, and reports, yet we still get surprised by attacks we feel we should have seen coming. The missing piece is usually not another tool. It is a weak connection between how real adversaries operate and what our environment actually sees, blocks, and responds to. Threat-informed defense is the practice of closing that gap on purpose, using concrete attacker behaviors as the backbone of planning and improvement work.

You are listening to a piece developed from the Tuesday “Insights” feature in Bare Metal Cyber Magazine, focused on threat-informed defense using the MITRE Adversarial Tactics, Techniques, and Common Knowledge (A T T ampersand C K) framework. The goal is to turn what can feel like yet another diagram into something that guides real decisions about logging, detection, and response. Instead of generic best practices, we will talk about specific attacker techniques, how they show up in real environments, and how you can use them to plan the next set of improvements that actually matter.

Threat-informed defense is best understood as a way of organizing your security work, not as a product you can buy. At the center is the A T T ampersand C K framework, which is simply a structured way of describing what adversaries do at each stage of an attack. Threat-informed defense takes that catalog of tactics and techniques and connects it to your own assets, logs, controls, and incident history. It sits across people, process, and technology, touching threat intelligence, detection engineering, incident response, and security architecture all at once.

At a leadership level, threat-informed defense helps risk owners decide which attacker behaviors matter most for the business they are protecting. That might be techniques related to phishing and credential theft for a service company, or lateral movement and data exfiltration for a manufacturer with sensitive designs. Architects and engineers then map those behaviors to telemetry sources and control points across identity, endpoints, networks, cloud platforms, and software as a service. Analysts and responders use the same language to follow attacks as they unfold, step by step, instead of hopping from one tool’s alert format to another.

It is equally important to be clear about what threat-informed defense is not. It is not just relabeling your existing rules with A T T ampersand C K identifiers. It is not printing a colorful matrix for an executive slide deck and then going back to business as usual. It is also not a replacement for broader risk and governance work. Instead, it is a way to prioritize and connect that work so that risk decisions, architecture changes, and day-to-day detection efforts all point at the same attacker behaviors rather than at vague maturity targets.

In day-to-day practice, threat-informed defense runs as a recurring cycle. A team begins by defining a small set of realistic threat scenarios, each described in terms of tactics and techniques from the A T T ampersand C K framework. Those techniques represent how an attacker might gain a foothold, move laterally, and reach a specific high value asset or business process. The team writes these down clearly, so that everyone can see the path an attacker would actually try to follow in this particular environment.

From there, engineers and analysts map each chosen technique to current coverage. They ask which logs can see the behavior, which detections might catch it, and which preventative or containment controls could slow it down. Very often, this exercise reveals surprises. Some techniques turn out to be well covered by existing detection rules and playbooks. Others are functionally invisible because the necessary telemetry is not collected or the alerts are buried in noise. Instead of guessing, the team now has an honest picture of where they are strong, weak, or blind for that specific threat path.

With that picture in hand, the team chooses a manageable set of techniques to improve in the next sprint or quarter. For each one, they define what better looks like. It might be new or refined detection logic in the security information and event management tool, stronger access controls in identity systems, additional logging on key servers, or a clearer response playbook for analysts. The work is still the familiar work of tuning tools and processes, but it is anchored in named attacker behaviors. The question becomes whether the environment can see and shape those behaviors, not whether another generic rule has been added.

This cycle is completed with testing. Sometimes that means using simple, safe test tools that simulate a specific technique and checking whether logging and alerts behave as expected. In more advanced settings, it might involve a purple-team exercise, where offensive specialists execute the technique while defensive staff watch, respond, and refine. A concrete example could be focusing on one lateral movement method, enabling the right operating system logs, tuning endpoint detections, and then running a controlled test to confirm that analysts can spot the move and take meaningful action in time.

Once teams adopt this way of working, the A T T ampersand C K framework shows up in many everyday tasks. Security operations centers use it to organize their detection backlogs, grouping rules and ideas by technique and then planning sprints around strengthening specific tactics such as initial access, persistence, or command and control. Incident responders use techniques as a backbone for their timelines, describing an intrusion as a sequence of behaviors rather than a scattered list of alerts. That makes it easier to compare incidents and see repeating patterns over time.

Architects and risk owners can use the same structure to plan larger changes. When a business unit is moving a critical service to the cloud, they can ask which A T T ampersand C K techniques become easier or harder for an attacker, and what telemetry and controls will be needed in that new model. Threat hunters can choose hunts based on high priority techniques that the organization still struggles to detect. A common quick win is to pick a small set of techniques that have appeared in past incidents and build a focused, time boxed improvement effort around them, rather than trying to cover the entire matrix at once.

More mature organizations use threat-informed defense to build broad roadmaps. They might define a multi quarter plan to strengthen detection and response for a family of techniques that matter most for their industry, such as those used by a known ransomware group. In that model, detection engineering, hunting, red teaming, and security awareness all draw from the same set of priority techniques. The A T T ampersand C K framework becomes a living map that guides where they spend effort, rather than a reference that only appears in reports.

When threat-informed defense is done well, it delivers several important benefits. The first is clarity. Instead of arguing about abstract goals like being more proactive, teams can point to specific techniques and show how well or poorly they can see and stop them. That shared picture improves conversations between security, operations, and leadership, because everyone is looking at the same set of behaviors. It also makes progress visible. You can document how coverage for a set of techniques improves over time, which is easier to understand than a vague statement about maturity.

A second benefit is focus. Most teams do not have the time or budget to chase every possible detection idea or tool feature. By mapping techniques to existing controls and telemetry, threat-informed defense highlights where a small amount of work will make a meaningful difference. That might be enabling one more log source, tightening a particular type of access, or writing a handful of targeted rules. Because those changes are tied to realistic threat scenarios, they are easier to justify to leadership and to auditors, and they tend to matter more when an actual attack occurs.

There are trade-offs. Building and maintaining an A T T ampersand C K informed view of your environment requires cross team coordination and care. Someone needs to own the mapping between techniques, logs, and controls, and that mapping has to be kept up to date as systems and threats evolve. If this work stays on a whiteboard or in a forgotten spreadsheet, it quickly loses value. There is also a risk of becoming so focused on techniques that you lose sight of basic hygiene issues or broader business risks that do not fit neatly into the framework.

Like any structured approach, threat-informed defense has common failure modes. One of the most visible is what many people call matrix theater. In those situations, teams produce attractive heat maps of the A T T ampersand C K framework, colored by claimed coverage levels, but nothing meaningful changes in logging, detections, or workflows. Another failure mode is treating technique tags as decorative labels on existing rules, rather than as drivers for new coverage or better response playbooks. In both cases, the language looks sophisticated, but incident outcomes remain unchanged.

You can also spot shallow adoption when only a few specialists ever interact with the framework. If threat intelligence analysts and red teamers mention A T T ampersand C K, but detection engineers, incident responders, and architects rarely use the same language, the approach will not shape daily decisions. A separate warning sign is when every technique is treated as equally important. That often leads to overloaded backlogs and a sense that threat-informed work is just extra overhead layered on top of normal tasks.

Healthy signs look different. In organizations where threat-informed defense is working, you see teams choosing a small, realistic set of techniques to focus on at any given time. They document current coverage honestly, define specific improvements, and track whether those improvements actually changed what the environment can see or do. Analysts refer to technique identifiers naturally in tickets and post incident reviews. Detection engineers use those identifiers when they talk about tuning rules, handling false positives, and designing new use cases. Leaders receive short summaries that show how coverage has improved for the techniques that matter to them, and those summaries influence where they invest next.

At its heart, threat-informed defense using the A T T ampersand C K framework is about grounding your security work in concrete attacker behaviors and then improving coverage against those behaviors on purpose. It gives you a common map that connects threat intelligence, logging, detections, and response in a way that mirrors how adversaries actually move. When that map shapes planning cycles, it turns matrices and charts into better telemetry, clearer alerts, and faster, more focused action when attacks occur.

The most practical way to begin is modest. Choose one or two realistic attack paths that truly concern you, describe them in terms of tactics and techniques, and ask where your environment can see and shape those behaviors today. Use that picture to plan a handful of targeted improvements, test them, and record what changed. That small, honest loop is the core of threat-informed defense. As you repeat it over time, you build a program that learns from real adversaries and steadily raises the bar, one technique and one decision at a time.