Building proactive threat intelligence

Threat intelligence isn’t new. What’s changed is the volume, speed and economics of attack, and the gap between what organisations know and what they can realistically act on. Marketers often call faster forensics ‘proactive’. It isn’t. True proactive security is pre-emptive: it blocks what’s coming before it starts, so your team isn’t fighting fires at 9 am on Monday.

 

Cybersecurity isn’t facing new threats; it’s facing more of the old ones turned up to eleven. The hard part isn’t novelty, it’s volume. If organisations can’t separate noise from signal, they’ll miss the one light left on at 2 am, which is the one that matters

 

Old threats, amplified

We’ve had machine learning for decades. Large language models (LLMs) don’t invent exotic new attack classes; they recycle known techniques and make it easier for more people to try them. The result? Not smarter attackers, just more of them, trying faster.

 

On any given day, a vulnerability in a popular plugin can be exploited in the morning, packaged and resold by lunchtime, and hammered at scale by evening. The barrier to entry keeps falling, which is why unpatched, poorly monitored systems account for most breaches, not mythical zero-days.

 

A useful mental model is to think of the boiling frog. As the water heats, organisations normalise the alert noise. Pattern-matching brains get tired; real signals hide inside the din.

 

The unpatched and poorly monitored vulnerabilities are the low pickings for those who are motivated either financially or, quite frankly, through boredom to see if they can exploit.  So, whilst proactive security is perceived as nothing new, what has changed is the scale, speed and economic model of cybercrime, and the gap between what organisations know and what they are practically able to act upon. Exacerbated by the fact that an increasing number of marketing teams brand their solution as ‘proactive’ when they really mean ‘faster forensics’. 

 

You’re probably not the main character

Some organisations believe that they are too small to attract attention, whereas others believe that if an attack occurs, it must have been a deliberate or sophisticated campaign against them personally. Yet, in the majority of cases, attackers are opportunistic. Bad actors cast wide nets: mass-scanning exposed services, buying OSINT-driven target lists, and launching ‘drive-by’ exploitation. If you happen to run the vulnerable version or leave a door ajar, you get swept up. You weren’t ‘chosen’; you were available.

 

Imagine a bakery worker using an LLM to learn how to rent cheap infrastructure and run a ready-made script with no idea what they’re really doing. The outcome can still be catastrophic for a small business caught in that blast radius. So doing more of the same won’t materially change your odds. What works is reducing your exposure and removing background noise so the one light left on at 2 am actually gets noticed.

 

The assumed-breach mindset is still reactive

Security Operations Centres (SOC) have become the new defence hub, but rising alert volumes bury analysts in investigations. CISOs burn out. How can we expect them to think strategically and anticipate emerging threats when they’re already overwhelmed with day‑to‑day forensic work?

 

The ‘assumed breach’ mindset centres on the fact that perimeter defences will fail, and that the focus moves to detect and respond to manage and mitigate downtime. Fair to say this mindset was pushed; we have all heard the ‘not if, but when’ marketing strategies. But this approach is reactive and accepts that the adversary will get into the network. It sells the hope that if you can see what it’s doing, you can put measures in place to stop it from coming back later. But true proactive threat intelligence pre-empts the threat so that it doesn’t need to enter the network in the first place.

 

Is threat intelligence a product or a service?

Threat intelligence isn’t the answer itself; it is a clue. Being able to act on this clue with meaningful impact is what makes the difference. Monitoring for indicators such as domains and IP addresses is only valuable when given context. For example, where has this infrastructure been seen before? What tactics and techniques are associated with it?  Does the traffic pattern match anything we’ve seen in our environment before?

 

A truly proactive stance is about understanding a known adversary and behaviour and blocking the attack paths before they are exercised. This involves analysing data sets that are as broad in scope as the scale of the full threat landscape. 

 

Relying on a single vendor feed is like watching two pixels on a 4K screen and trying to call the score. Individual feeds overlap by a tiny percentage; they also conflict and often aren’t tuned to your sector. Aggregation, plus adjudication, plus action is what turns clues into true protection.

 

The more diverse and high quality the data, the stronger the predictive value. When analysing this data, patterns begin to emerge and correlations can be drawn between seemingly unrelated events. For example, requests from specific geographies, unusual authentication attempts, or data flows that don’t fit historical patterns can be prioritised intelligently. By doing this, we can see things before they can become destructive, for example, the MoveIT and Log4j vulnerabilities were seen as far out as 90 days before they became a problem for some. 

 

From clue to coverage: the AAA of intelligence

Historically, only well-funded teams, the military or governments could buy enough feeds to see the whole picture. Even then, normalising and deciding on conflicts in real time demanded supercomputer-like resources, and somewhere to plug the outcome in.

 

Operationalising intelligence at machine speed flips the equation. Now everyone can consume the world’s signals, reconcile them, and enforce the decision at the edge before the knock lands on the door. Less chasing, more shielding.

 

Prepare for what’s coming down the road

Operationalising pre-emptive threat intelligence not only buys organisations time by concealing vulnerabilities from bad actors; it also highlights the signals that most urgently need attention. Reconnaissance is the front door for most campaigns: incessant scanning, credential-stuffing, and low-skill probes. Deny known bad infrastructure pre-emptively, hide what’s exposed, and you immediately cut the background radiation so genuine anomalies stand out.

 

Agentic AI will widen the blast radius. Not because it’s magic, but because it automates experimentation. The defence response isn’t to panic; it’s to make the easy stuff impossible, so you can focus on the truly novel.

 

We need to remember that most incidents aren’t fate or ‘a mastermind coming for you’. They are old doors left open. True proactive intelligence buys you time and turns Monday-morning firefights into Monday-lunchtime summaries.

 

It will take brave leadership to reset definitions and benchmarks. But once you experience a week where attempted compromises are quietly blocked upstream, you won’t want to go back to chasing ghosts.

 

---

 

Chris Handscomb is Director of Solutions at Centripetal 

 

Main image courtesy of iStockPhoto.com and Orhan Turan