Episode 70 — Essential Terms: Plain-Language Glossary for Fast Review
In Episode Seventy, Essential Terms: Plain-Language Glossary for Fast Review, the goal is to turn key ideas into short, clean definitions you can actually say out loud under exam pressure. Instead of long academic explanations, you want phrases that fit in a single breath and still capture the heart of the concept. For an exam candidate, these terms keep showing up in scenarios, decision questions, and “best next step” choices. Having them in muscle memory makes it much easier to work through tricky wording without getting stuck on vocabulary. Think of this as a final polish pass on the language you will lean on when the clock is running and the questions are dense.
Defense in depth describes how you protect important assets with several different layers of safeguards, not just one impressive control. The idea is that if an attacker breaks through a single layer, such as a firewall or web gateway, they still run into additional protections like strong authentication, network segmentation, and application checks. Each layer should be as independent as possible, so a failure or misconfiguration in one does not automatically destroy the value of another. In a payment environment, you might see defense in depth in the form of network zones, encrypted storage, strict access reviews, and monitoring all watching the same data from different angles. When you are choosing between “one big control” and “several smaller, independent controls,” defense in depth usually prefers the second.
Threat modeling is a structured way of thinking about what could go wrong before you build or change a system. You identify assets that matter, such as cardholder data or payment authorization services, then think through who might target them and how. You rate the impact and likelihood of different attack paths, focusing on those that are both plausible and damaging. From there, you design or adjust controls to either block those attacks, detect them early, or limit their impact if they succeed. When a question mentions designing a new service or connection, threat modeling is often the step that turns vague concern into a prioritized list of risks and countermeasures.
Risk treatment is the name for your choices once a risk has been identified and analyzed. In simple terms, you can avoid a risk by not doing the risky activity, reduce it by adding controls, transfer it by using contracts or insurance, or accept it with a documented reason. Avoiding might mean refusing to store certain data at all, while reducing could involve implementing stronger authentication and monitoring. Transferring might be done through carefully written supplier agreements, though you still keep ultimate accountability for cardholder data. Accepting risk is not “doing nothing”; it is recording why the remaining risk is tolerable and who agreed to that decision. On exam scenarios, the best answer often reflects a clear and documented choice among these treatment options.
Secure defaults describe an approach where systems start in a safe, locked-down state and require deliberate action to loosen restrictions. The shorthand is “deny by default,” which means access, features, and integrations are not allowed until someone intentionally enables them. Secure defaults might show up as strong password requirements already set, logging enabled out of the box, or new network rules starting from “block” rather than “allow.” This reduces the chance that a busy team forgets to tighten something after deployment, because the system is never wide open in the first place. When comparing options, the design that begins restrictive and requires explicit, reviewed changes to open up is usually the secure defaults choice.
Idempotency is a term that often comes from software and APIs, but it has clear security implications as well. An idempotent operation is one where making the same request multiple times leads to the same result, without unwanted duplicates or extra side effects. For example, if a payment confirmation endpoint is idempotent, accidentally resending the request does not double-charge the customer. This behavior helps prevent both accidental damage and certain abuse patterns, because repeating a safe action does not escalate its impact. When you see design choices about how services handle retries or network glitches, idempotency is the principle that keeps “try again” from becoming “do it twice.”
Provenance is the verified story of where something came from and how it got to you, especially in a software supply chain. For components, it answers questions like which source repository they came from, who built them, and what checks they passed along the way. A strong provenance trail can prove that an artifact was not quietly replaced with a malicious version or altered by an unknown party. This becomes critical when you rely heavily on open-source libraries, container images, or upstream services, because you need to trust their path into your environment. On the exam, provenance is the concept that connects origin, integrity, and traceability for software you did not write yourself.
Attestation is closely related, but focuses on presenting cryptographic proof about a system’s state, identity, or configuration. A system might generate an attestation that says, “I am running this version of code, with these security settings, on this hardware,” and sign it so others can verify it has not been forged. Remote attestation lets one system check that another meets certain security conditions before sharing data or granting access. This is especially important in high-trust environments, where you want strong assurance that you are talking to a genuine, well-configured counterpart, not a weakened or spoofed one. When a question describes proof about a current configuration being sent and validated, attestation is usually the underlying word.
A compensating control is an alternate safeguard you use when the primary or recommended control cannot be implemented as written. The key is that the compensating control still meets the intent and strength of the original requirement, even if it looks different in practice. For example, if a legacy system cannot support modern encryption methods, you might place it behind a tightly controlled, monitored gateway that encrypts traffic on its behalf. Compensating controls must be carefully justified, documented, and usually reviewed more often to ensure they remain effective over time.
At this point, a short mini-review can help lock in the terms that still feel slippery. You might mentally cycle through least privilege, defense in depth, separation of duties, and threat modeling, testing whether you can describe each in a single clear sentence. Then you can jump to the more specialized words like nonrepudiation, idempotency, provenance, and attestation, seeing if you can attach a quick example to each. If a definition feels fuzzy, imagine a small scenario where it obviously applies or fails, and adjust your wording. The more these phrases feel like ordinary language rather than exam jargon, the easier they will be to recall when you are tired or under time pressure.
Bringing this glossary to life is less about memorizing paragraphs and more about picking a small set of terms to sharpen each day. Those short definitions then become anchors for longer reasoning in scenario questions, where you can lean on them without hesitation. As you repeat this process and work through timed practice, the glossary shifts from a reading exercise into part of your thinking voice. With that in place, you walk into the exam carrying not just facts, but a fluent language for explaining the decisions the exam expects you to make.
