As AI becomes increasingly utilized throughout the security space, it's important to consider how it should be used most effectively. We've all seen companies adding AI into every offering and function they perform, often as much as possible.

In security operations, this creates a divide between two types of companies:

1. Companies that rely primarily on AI to do the work
2. Companies that enable their operators to become higher performers through the use of AI

Both types address a clear problem: volume. Anyone who has worked in a SOC knows that alert volume results in burnout, limits the number of customers you can support, and takes time away from more important tasks. Using AI to accelerate triage of high-volume, lower-complexity alerts is a practical and effective strategy. It frees analysts to focus on the ambiguous cases that require human judgment. With the right context and data, AI can meaningfully assist in distinguishing malicious from benign activity — but "most of the time" isn't good enough when a miss means a breach. AI augments the analyst; it doesn't replace their judgment.

That said, keeping a human in the loop is critical for the fringe cases: AI hallucination, highly complex technical investigations, and even situations where attackers attempt to fool the models with injection or evasion techniques.

Let's talk about some ways you can be the second type of company: the one that enables operators rather than replaces them.

AI for Triage Enhancement

Utilizing AI for enhancement of the triage process is something all security operation centers should be doing right now. While AI may occasionally be wrong or may hallucinate, anyone not taking advantage of it to work across the huge amount of data that SOCs process will fall behind their competitors.

I'm not suggesting that an AI model should be constantly closing alerts. Instead, consider this: Could an AI elevate alerts that would otherwise not have been investigated?

All SOCs process swathes of low-fidelity or low-severity alerts that are usually suppressed, deduplicated, or closed out through automation. What if you could use an AI model to review these alerts that would've been closed anyway and elevate those requiring human response to higher priorities? The worst-case scenario—a false negative—isn't applicable here. These alerts wouldn't have received much attention anyway. In the ideal scenario, you could intelligently review alerts your analysts wouldn't have looked at otherwise, escalating truly concerning activity for a human to look at.

AI for Quality Assurance

Another clear use case for AI in SOCs is quality assurance. Many QA checks on investigations are random, but what if you could curate a set of prompts that tasks AI with looking for common mistakes within your investigations and notifies a human to review them?

The AI could highlight the causes for concern, providing a starting point for the human analyst. It could even offer suggestions to both the reviewer and the analyst, making note of possible improvements. The higher quality the QA prompts, the better the feedback.

AI for Validation

Similar to the first use case mentioned, AI could validate analyst investigations and look for logical gaps or potential blind spots. Effectively, it could be used to provide top cover for analysts, giving them more space to triage quicker without chasing down every lead, knowing that the model (ideally trained on past cases!) is fact-checking and logically validating their investigation, freeing them to confidently triage without second-guessing themselves.

Human Augmentation

While AI excels at handling repetitive high-volume tasks, human expertise remains essential for complex investigations, fringe cases, and maintaining accountability. Rather than viewing AI as a cost-cutting tool to reduce headcount (or to take on many more customers with the same headcount), think of it as an investment that multiplies the effectiveness of your existing team. By strategically deploying AI to handle or fact-check routine work, you free your analysts to focus on the sophisticated threats that truly require human judgment and critical thinking.

If you take one thing from this article, I want it to be this:

Using AI to augment your operators may not show the same immediate "return" as replacing them, but, over time, it will increase your service quality tenfold.

Imagine you are a soldier on the front lines, moving through hostile terrain with only your training, tools, and instincts. That's what threat hunting in cybersecurity feels like. You're not waiting in a bunker for alarms to sound; you leave the wire, patrol the area of operations, and look for signs of the enemy before they strike.

A traditional SOC analyst is a watchtower guard: when an alarm goes off, you investigate, confirm, and respond. A threat hunter is the scout team. Your mission begins when everything appears quiet. You assume the adversary is already inside the wire, moving carefully to avoid detection, and your job is to search the terrain, uncover indicators of intrusion, and expose what automated systems miss.

The Ten Battlefield Principles of Threat Hunting

1. If you were the enemy, where would you hide? Every hunt begins by adopting the minset of the adversary—considering their objectives, prioritized systems, likely blind spots, and possible routes for remaining unseen.

2. Your job is tracking. Threat hunters scrutinize logs, processes, authentication paths, and network flows like scouts reading disturbed ground or broken vegetation. You're searching for what's out of place or subtly altered.

3. You create a hypothesis. A hypothesis defines what you expect to see if an adversary is present, giving the hunt direction and preventing aimless data trawling.

4. You move through the environment tactically. You progress methodically through hosts, logs, and authentication records, validating your hypothesis step by step, and carefully documenting your findings.

5. Intelligence guides the hunt. Threat intelligence, prior incidents, and known TTPs (tactic, techniques, and procedures) shape your approach, just as scouts rely on maps, reconnaissance, and mission briefs.

6. Your tools are your weapon systems. SIEM queries, EDR telemetry, packet captures, forensic utilities, and scripting tools are your rifles, optics, and radios. Mastery of them determines how effectively you can uncover hidden activity.

7. You respect the enemy. Adversaries are adaptive and quiet, hiding in normal traffic and shifting tactics quickly. Respect for their capability keeps you vigilant and prevents complacency.

8. When you find something, you call it in. Threat hunters identify, analyze, and escalate findings. Once hostile activity is uncovered, incident response then takes over, just as scouts report contact so their unit can quickly act.

9. The battlefield changes, and you must adapt. Technology shifts, environments evolve, and infrastructures change. Adversaries adjust accordingly, and so must you, by continuously refining techniques, revising hypotheses, and ever tuning your approach.

10. Above all, threat hunting demands a warrior mindset. Patience, curiosity, discipline, and resilience are essential. You operate in uncertainty, seek the subtle, and work where visibility is low and risk is high.

Threat hunting is not a passive role. It requires intent, stealth, and a willingness to move beyond alerts into uncertainty. By taking on the mindset of the adversary, reading the terrain, and acting with discipline, threat hunters find what the automated systems cannot.

The Pyramid of Pain: Knowing and Exploiting Your Adversary's Weak Points

The Pyramid of Pain analogy shows the hierarchy of difficulty an attacker faces when changing certain indicators and how forcing them to do so is likely to disrupt their operations.

Hash Values These are the most easily modified indicators for an adversary. A file hash changes in seconds. Hunting for hashes is like searching for footprints in loose sand.

IP Addresses Attackers replace IPs frequently because they're disposable and easily rotated. Burning an IP, in practice, disrupts nothing beyond temporary infrastructure.

Domain Names Domains require more effort to rebuild, but adversaries often maintain many of them. Forcing a domain change creates friction but doesn't significantly impair strategy.

Network and Host Artifacts These unusual processes, persistence mechanisms, registry changes, and lateral movement patterns reveal the enemy's hands-on work. Replacing them requires careful planning and technical effort, creating real operational pressure.

Tools Adversary tools like Cobalt Strike, Sliver, Impacket, and custom malware represent major investment. Exposing or disrupting them forces adversaries to retool, redesign workflows, and rebuild capabilities.

Tactics, Techniques, and Procedures TTPs are the enemy's doctrine and operational style. Disrupting TTPs applies serious pressure on them to rethink strategy, retrain operators, and redesign campaigns.

While this battlefield may be digital, the mission is the same: detect the enemy early, deny them freedom of movement, communicate new intelligence, and protect what matters before the first alarm ever sounds.

by Dan “Haircutfish” Rearden | haircutfish.com | Guest Author Working in the SOC can be a grind. Whether triaging alerts, escalating to clients, or just trying to understand why users […]

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