Cyber Threat Intelligence for UK Organisations – Moving Beyond Generic Feeds

Threat intelligence is often discussed as if it is synonymous with data feeds, automated alerts, or vendor threat summaries.

Many UK organisations believe they have intelligence because they receive reports, dashboards, or notifications, the reality is this is information not intelligence. Intelligence is information that has been interpreted, prioritised, and connected to real-world decision-making.

When intelligence lacks context, even large volumes of data do not create clarity. In fact it has an adverse effect, instead, organisations experience familiar challenges of alert fatigue, difficulty prioritising defensive investments, ongoing uncertainty about which threats are actually relevant.

Effective intelligence is not about more data, it is about collecting the right data and shaping that into a meaningful interpretation aligned to how an organisation operates, where it is exposed, and which adversaries are most likely to target it.

Understanding the UK Threat Landscape

The UK financial and critical infrastructure environment has distinctive characteristics which include

• High interconnectivity between financial institutions and service providers.
• Reliance on outsourced IT, SaaS platforms, and managed services.
• Strong geopolitical alignment, often influencing adversary interest.
• Increasing operational pressure on internal security teams.

These dynamics shape how threats manifest themselves. For example, a supply chain compromise is not just a theoretical scenario it is a very credible vector due to the UK’s dependency model. We’ve actually seen this recently with some notable organisations being in the news. Similarly, ransomware campaigns very often progress through credential abuse rather than initial exploitation of external servers these days.

A threat landscape is not defined by global attack activity but by the specific ways organisations in a region and sector are targeted in practice, and this is where effective intelligence interpretation generally fails.

The Limitations of Generic Threat Feeds

Now I’m not trying to reduce the usefulness of threat feeds, they can be useful for maintaining awareness of broad activity trends. However, they frequently overload and

• Highlight threats that are not relevant to the organisation’s sector or attack surface.
• Provide indicators without context, making prioritisation difficult.
• Focus on threat volume rather than threat likelihood or potential impact.
• Reinforce reactive rather than proactive defensive postures.

This just results in an environment where teams are informed, but not guided. For example, an alert that “a ransomware group is active in Europe” may be technically accurate, but unless it is connected to the organisation’s supplier access model, recent credential exposure, or system dependencies that adversaries typically target, it cannot meaningfully support defensive planning.

Relevance Over Volume

When it comes to building Effective intelligence programmes there needs to be specific priorities. Let’s discuss some of them.

1. Sector-Specific Targeting Analysis

Goes without saying, understanding how adversaries have historically targeted organisations with similar operational models is always a good place to start.

2. Business Value Mapping

Identifying which systems or processes represent concentration of value or leverage, in other words, what’s the stuff threat actors actually want. Sometimes, this isn’t actually what you think!

3. Behavioural Threat Actor Insights

Recognising patterns in adversary operational decision-making.  Now we’re evolving beyond lists of tools and techniques to how and why an adversary chooses a particular actions, their priorities, trade-offs and predictable behaviours.

4. Prioritised Defensive Guidance

We’re now getting into the territory of translating intelligence into practical next steps rather than broad awareness, it suddenly starts to become more meaningful. It shifts from being a monitoring exercise to a decision support function.

Let’s go over an example quickly

During a review of an incident preparedness exercise for a UK mid-sized financial services firm, the organisation believed that external perimeter vulnerabilities represented their primary threat. However, when we analysed sector intrusion trends and internal architecture, a more realistic exposure picture emerged

• One of their operations supplier held administrative access into production systems.
• That supplier was known to support multiple organisations targeted by financially motivated groups.
• Those groups predominantly leveraged credential compromise rather than perimeter exploitation.

Reframing the threat model shifted the defensive priority from perimeter hardening to supplier access monitoring and privilege governance. This adjustment significantly improved resilience, without increasing cost or complexity. This wasn’t to say ignore perimeter security and do X instead. It was a demonstration of a more meaningful and impactful way of thinking about threats. The intelligence did not identify a new threat, it just clarified which threat mattered the most. Why is this important, well, appropriate decisions/risks can be documented and maintained and proper investment can happen.

Human Interpretation still remains critical

Let’s circle back to automation and feeds. These gather and surface information, but they do not evaluate its meaning. They often cannot determine:

• Whether the organisation is likely to be targeted by a particular actor.
• Which intrusion vector aligns with the organisation’s technology stack.
• How threat behaviour interacts with supplier or identity dependencies.
• Which defensive changes would materially reduce real-world risk.

These judgments require analysis. In practice, intelligence becomes valuable at the point where it supports prioritisation and action.

So how do we build intelligence that supports decision making?

A useful approach involves structuring intelligence outputs to align with defensive or strategic choices.

• Start by identifying which threats are most plausible for the organisation’s sector and architecture.
• Highlight the most likely intrusion vectors for credible adversaries.
• Clarify which controls would most meaningfully reduce exposure.
• Provide concise intelligence summaries that support communication to non-technical stakeholders.

The objective is not to make predictions, but to reduce uncertainty. It’s easy to fall into the prediction trap.

Let’s wrap it up

• Threat intelligence is only effective when it supports decision-making.
• UK organisations face distinct exposure patterns shaped by sector structure and supplier models.
• Generic threat feeds provide information but not clarity.
• Intelligence must be contextualised to business value and operational reality.
• The most valuable outcome of intelligence is improved prioritisation and confidence in defensive planning.

ThreatInsights focuses on improving the relevance and realism of the threat intelligence that informs security testing and defensive planning.