Bare Metal Cyber

When people in cybersecurity talk about “controls,” it can sound like everyone already shares the same picture. In reality, many teams mix up control types, double down on one category, and quietly leave gaps that attackers can walk through. This session is all about making that picture clearer. You are listening to a Tuesday “Insights” feature from Bare Metal Cyber Magazine, developed by Bare Metal Cyber, focused on the different types of security controls and how they really behave in your environment.

A security control is anything that reduces risk by shaping how systems, data, or people behave. That “anything” could be a firewall rule, a secure configuration baseline, a sign-in policy, a training program, or a locked server room door. When we talk about control types, we are really describing when a control does its job: before something bad happens, while it is unfolding, or after it has already caused damage. Thinking in those terms turns a messy list of tools and policies into a more structured view of your defenses.

Security controls live across three broad layers. Administrative controls are things like policies, standards, and procedures that guide how work should be done. Technical controls are implemented in software and hardware, such as authentication systems, access rules, and monitoring tools. Physical controls protect the spaces where equipment and people sit, such as locks, cameras, and access badges. Each of these layers can host preventive, detective, and corrective controls. That means a single policy or tool can belong to more than one category at the same time, depending on how you use it.

It is also important to be clear about what a control is not. Buying a new product does not magically create a control if nobody configures it, owns it, or checks that it works. Writing a policy and parking it on a shared drive does not create a meaningful control if people do not know about it or follow it. A real control has intent, implementation, and evidence that it is active in day-to-day work. That evidence might be logs, tickets, approvals, or other artifacts that show the control is doing its job, not just sitting on a slide deck.

There is another common source of confusion: frameworks versus control types. A control framework is a catalog of things you might implement, often aligned with regulations or industry expectations. Control types are labels like preventive, detective, corrective, directive, deterrent, and compensating. These labels describe how any particular control in that catalog behaves. Keeping those ideas separate helps you see that the same framework requirement can be met with different mixes of control types, tuned to your environment and risk appetite instead of blindly copied from a checklist.

Now let us walk through the main categories. Preventive controls aim to stop unwanted activity before it happens, like multi-factor authentication, network segmentation, or strict change-approval workflows. Detective controls help you notice suspicious or malicious activity that gets past prevention, such as log analytics, intrusion alerts, and user-reported phishing. Corrective controls help you recover and restore normal operations after something goes wrong, including incident response procedures, backup and restore steps, and account reset processes. Directive controls give guidance up front, deterrent controls make people think twice before misbehaving, and compensating controls cover gaps when the ideal control is not possible. In a healthy environment, these types form a chain instead of isolated islands.

Imagine a user trying to sign in from an unusual location. Preventive controls are the ones that step in first: strong authentication, device compliance checks, and conditional access policies that may block or challenge that login based on risk. If the login is allowed but looks strange, detective controls kick in next. Monitoring rules and identity alerts flag the activity as suspicious and send it to a queue for review. If an analyst decides the activity is malicious or the account is compromised, corrective controls take over by resetting credentials, revoking active sessions, isolating endpoints, and restoring any affected data from backup.

That simple scenario hides several big assumptions. Preventive controls depend on good identity data, accurate information about devices, and clear access rules. Without those, any policy you write will be inconsistent or overly permissive. Detective controls depend on complete logging, centralized visibility, and tuned alert logic. If key systems are not sending logs or alerts are not prioritized, important signals get lost. Corrective controls depend on rehearsed playbooks, empowered responders, and recovery procedures that have been tested under realistic conditions. If those are weak, the organization stumbles when it most needs to move quickly.

When you look around most environments, you will find all of these control types, even if nobody uses the labels out loud. Preventive controls show up as password policies, multi-factor authentication, secure configuration baselines, and rules that limit who can change critical systems. Detective controls include security information and event management alerts, endpoint detection notifications, file-integrity monitoring, and people reporting suspicious messages or activity. Corrective controls include rebuild procedures for compromised devices, backup and restore playbooks, and post-incident reviews where teams examine what happened and adjust their approach.

For smaller or stretched teams, some of the best opportunities are simple “quick wins” that fill obvious gaps in the mix. An organization that has invested in prevention, such as firewalls and antivirus, may have very thin detection and response. By forwarding logs from key systems to a central place, enabling built-in alerts for administrative changes, and agreeing on a basic triage checklist, they can dramatically improve their ability to spot and act on trouble. These adjustments do not require a large new platform or a complete reorganization. They add teeth to the controls that are already in place.

More mature or strategic uses of control types come from mapping them across entire processes instead of thinking tool by tool. For example, in a cloud migration, you might define preventive controls around identity and permissions, detective controls around cloud activity monitoring and anomaly detection, and corrective controls around automated rollback and infrastructure-as-code changes. After a few incidents, you can track which controls actually triggered and where steps were missing or slow. That process view helps you refine the mix in a focused way rather than reacting to the latest product trend.

The real payoff of understanding control types is a shift in how you measure your security posture. Instead of counting tools and features, you ask how your defenses behave across the life of an incident. Teams can explain how they try to stop bad events, how they detect what gets through, and how they recover and learn. That shared mental model makes communication between security, IT, and leadership simpler. It moves conversations away from brand names and toward risk, coverage, and outcomes.

Of course, there are trade-offs. Preventive controls that are too strict can slow down the business, frustrate users, and lead them to find workarounds. Getting them right requires design, testing, and sometimes training. Detective controls bring visibility and learning, but they generate noise if they are not tuned or if nobody has time to review alerts. Corrective controls can reduce downtime and damage, but they require investment in backups, automation, and cross-team exercises. Many small organizations lean heavily on one category, usually prevention, because they do not feel ready to staff detection and response.

There are also hard limits to what each type can achieve. Preventive controls will never be perfect because attackers change techniques and environments evolve. Detective controls will always miss some activity and raise some false alarms. Corrective controls can help you recover systems and data, but they cannot undo lost trust or public reputation damage. The goal is not to eliminate risk or to find a magic combination of controls that makes you “done.” The goal is a deliberate mix that matches your environment, resources, and tolerance for disruption.

When you look at the mix through this lens, some patterns stand out. Preventive controls offer strong risk reduction when designed well, but they demand good identity and asset data and careful attention to user experience. Detective controls offer richer visibility and insights into how attacks really unfold, but only if alerts are prioritized and investigated, not just collected. Corrective controls offer resilience when things go wrong, but only if backups are reliable, recovery steps are documented, and teams have actually walked through them. Saying these things out loud makes it easier to justify where you spend effort and where you accept limitations.

It is also useful to recognize classic failure modes. One is over-investment in prevention without enough detection or response. In these environments, organizations buy firewalls, email filters, and endpoint agents, but have little insight into how well they work or what happens when they fail. Another failure mode is the “alert museum.” Logs and security tools generate large volumes of alerts, but there is no clear process or ownership for handling them. Tickets pile up, dashboards look impressive, and yet incidents still slip through because nobody closes the loop.

Shallow adoption can be just as dangerous. An organization might enable multi-factor authentication for some users but not for privileged accounts. They might configure logging on servers but never send those logs to a central system. They might publish a policy about access reviews but never schedule or document the reviews. On paper, many controls exist. In practice, attackers encounter inconsistent enforcement, blind spots, and recovery plans that have never been tested under stress.

Healthy environments look and feel different. Teams can point to a simple map of a key process, like user onboarding or change management, and show which preventive, detective, and corrective controls apply at each step. They review alerts and incidents not just to close cases, but to ask whether the right controls triggered at the right time. They schedule tests of backups, access revocation, and containment steps, and treat those tests as learning opportunities rather than one-time compliance exercises. Metrics such as time to detect, time to contain, and time to recover become part of regular reporting, right alongside uptime and project status.

You can also spot health in the way change is handled. When a new application or service is introduced, part of the discussion is which controls will protect it and how those controls align with existing patterns. When a major incident occurs, the post-incident review results in specific, trackable changes to controls, not just general reminders to “be more careful.” Over time, this loop helps build a culture where people naturally talk about control types as part of design and planning, not just as exam vocabulary.

At its heart, the idea of security control types is about understanding how your defenses behave before, during, and after events, instead of viewing security as a random pile of tools and documents. When you use simple labels like preventive, detective, corrective, directive, deterrent, and compensating, you gain a shared language for explaining how risk is managed in your environment. That language makes it easier to see imbalances, challenge assumptions, and communicate clearly with people who may not live in security every day.

As you look at your own environment through this lens, you may notice strong perimeter prevention but little internal detection, or solid monitoring with weak, untested recovery, or carefully written policies with no concrete controls attached. Those observations are not a verdict on your program. They are a starting point for focused improvement. From there, you can decide where to strengthen, where to simplify, and where to accept risk with a clearer view of the trade-offs. That is the real value of understanding security control types: it turns a vague sense of “we have some security” into a more honest picture of how your defenses actually work when it matters most.