Cyber deception at UK scale: what the NCSC trials tell us — and what they still don’t

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The NCSC’s cyber deception trials mark a shift from theory to evidence, testing whether deception can deliver real defensive value at scale. This article examines what those trials show — and what they leave unresolved. It argues that cyber deception is best understood as an evolution of honeypots, powerful but operationally demanding, and highly dependent on organisational maturity. While effective in well-instrumented environments, deception is not an SME-level control and risks being over-sold. Without clear metrics, safety discipline, and honest maturity gating, its promise remains conditional.

Executive Summary (TL;DR)

The NCSC’s cyber deception trials provide the strongest real-world evidence to date that deception can deliver defensive value — but only under specific conditions. Across 121 organisations and multiple environments, the trials show that deception can generate high-confidence detection, surface hidden compromises, and impose friction on attackers. However, they also expose a harder truth: cyber deception is not a plug-and-play product, but an operational programme that depends heavily on organisational maturity, safety discipline, and measurement.

Modern cyber deception is best understood as the evolution of honeypots — extending the same interaction-based logic across identities, cloud, data, and workflows — while inheriting the same risks if deployed poorly. Effectiveness is constrained by inconsistent market language, a lack of outcome-based metrics, and unclear guidance on safe deployment and signalling. Most organisations choose to keep deception covert, revealing an unresolved strategic tension between secrecy and deterrence.

Crucially, the trials reinforce that deception is not an SME-level control today. Without strong fundamentals — asset visibility, identity control, monitoring, and response capability — deception does not fail benignly; it introduces risk. In practice, deception currently fits above the basics, delivering disproportionate value in well-instrumented enterprise, cloud-heavy, and critical infrastructure environments.

The national opportunity is real but conditional. If the NCSC can translate trial insights into vendor-neutral metrics, clear taxonomies, safety baselines, and realistic guidance, cyber deception could mature into a credible pillar of layered defence. Without that follow-through, it risks remaining an over-marketed idea: compelling in theory, uneven in practice, and easy to misuse.

Contents

Table of Contents

1. Introduction: Into the Maelstrom

In December 2025 the UK’s National Cyber Security Centre (NCSC) published an update on its “nation-scale evidence base” work to test whether cyber deception technologies actually help in real environments — not just in lab demos and vendor decks. The trial footprint is unusually broad for this kind of defensive research: 121 organisations, 14 commercial providers, and 10 product trials spanning cloud through to operational technology (OT).

The headline is sensible and, frankly, overdue: cyber deception can work, but it isn’t plug-and-play. The more interesting story is why it isn’t plug-and-play, what “work” should mean in measurable terms, and what it would take for deception to become a mainstream, governable security control rather than a niche SOC toy.

This article offers a comprehensive and critical analysis of what the NCSC’s findings imply, what’s missing, and how to translate the promise of deception into repeatable, defensible outcomes.

This article should be read as a practitioner-led response to the evidence-building programme set out by the NCSC in 2024, which sought to establish a national-scale understanding of cyber deception use cases and efficacy in support of Active Cyber Defence 2.0. It engages with that ambition seriously, but critically — examining not just whether cyber deception can work, but under what conditions it is safe, measurable, and operationally justified. Where this analysis is more cautious than policy framing, that caution reflects implementation reality rather than disagreement with intent.

2. What is cyber deception? An overview

At its core, cyber deception is the deliberate use of false digital artefacts and environments to detect, observe, and influence malicious behaviour. Rather than trying to block every attack outright, deception aims to make attackers reveal themselves by interacting with things that legitimate users should never touch.

In practical terms, cyber deception can include:

  • Decoy systems that appear real but exist solely to be attacked
  • Lures and breadcrumbs, such as fake credentials, API keys, files, or database entries
  • Canary artefacts that trigger alerts when accessed
  • Controlled engagement environments that allow defenders to observe attacker behaviour safely

The defining characteristic is not the technology itself, but intent: these assets exist to be interacted with by attackers, not to provide business functionality.

What cyber deception is

Cyber deception is:

  • A high-signal detection mechanism that can convert attacker curiosity into near-certain alerts
  • A way to surface attacker behaviour earlier in the intrusion lifecycle
  • A source of context-rich intelligence, including tools, techniques, and lateral movement paths
  • A method of imposing cost and uncertainty on adversaries by wasting their time and eroding confidence

When done well, deception can dramatically reduce the ambiguity that plagues many modern detection systems. An alert triggered by interaction with a decoy credential or system is rarely accidental.

What cyber deception is not

Cyber deception is often misunderstood, and those misunderstandings are one reason it has struggled to achieve mainstream adoption.

Cyber deception is not:

  • A replacement for endpoint detection, identity security, or network controls
  • A silver bullet that “tricks hackers” without planning or maintenance
  • An excuse to weaken baseline security or hygiene
  • A purely offensive or “hack back” capability
  • A static deployment that can be set once and forgotten

Deception does not work in isolation. Without good asset management, identity controls, and response capability, it simply becomes another source of alerts — or worse, another misconfigured system.

Why deception feels different from traditional controls

Most security controls are preventative or probabilistic. They block known bad things, or they infer malicious behaviour from patterns and heuristics. Deception is different: it is interaction-based.

If an attacker touches something that should not exist, the ambiguity collapses. This is what gives deception its appeal — and also what makes poor deployments so visible and unforgiving.

3. Is cyber deception just the evolution of honeypots?

Cyber deception is best understood as an evolution of the honeypot concept, rather than a simple rebranding of it.

Classic honeypots were typically single systems or services deliberately exposed to attract attackers. Their primary value lay in observing exploitation attempts and tooling in a controlled environment. They were useful, but narrow in scope, operationally fragile, and often isolated from day-to-day security operations.

Modern cyber deception keeps the core idea of the honeypot — enticing attackers into revealing themselves — but extends it across identity, cloud, endpoints, networks, applications, and data, and integrates it directly into detection and response workflows.

What honeypots got right

Honeypots established several enduring principles:

  • If an attacker interacts with something that should not exist, intent is clear
  • High-confidence alerts reduce analyst ambiguity
  • Observation of real attacker behaviour is more valuable than synthetic testing
  • Attackers can be slowed, distracted, or studied without engaging production systems

These principles still underpin cyber deception today.

Where traditional honeypots fell short

Despite their conceptual elegance, classic honeypots struggled because they:

  • Were static and easily fingerprinted
  • Sat outside normal environments, making interaction suspicious
  • Required specialist expertise to deploy and maintain
  • Rarely integrated cleanly with SOC tooling
  • Were often treated as research projects rather than operational controls

As attackers became more automation-driven and more aware of honeypots, the signal-to-noise ratio declined.

How cyber deception moves beyond honeypots

Modern cyber deception expands the model in three important ways:

  1. From systems to surfaces
    Deception now operates at the level of credentials, identities, APIs, files, cloud resources, and workflows — not just exposed services.
  2. From traps to ecosystems
    Rather than a single honeypot, deception can involve multiple artefacts that reinforce each other and adapt as environments change.
  3. From observation to influence
    The goal is no longer just to watch attackers, but to shape their behaviour — slowing them down, misdirecting them, and increasing uncertainty.

A fake service that exists only on the internet edge is easy to suspect. A fake credential buried in a realistic workflow is much harder to distinguish from the real thing.

Why this distinction matters

Calling modern cyber deception “just honeypots” understates both its power and its risk.

  • It undersells the operational discipline required to deploy it safely
  • It overlooks new failure modes, particularly around identity and cloud misconfiguration
  • It misleads buyers into expecting simple deployments with guaranteed value

Cyber deception inherits the strengths of honeypots — clarity of intent and high-confidence signal — but also inherits their weaknesses if deployed carelessly.

The bottom line

Honeypots were the first expression of a deeper defensive idea: that attackers can be detected by interacting with things that should not exist.

Cyber deception is the generalisation of that idea across modern digital environments.

If honeypots were the proof of concept, cyber deception is the attempt to turn that concept into a scalable, operational control. Whether it succeeds depends less on technology, and more on strategy, safety, and measurement.

4. What the NCSC actually tested (and why it matters)

The NCSC framed three core assumptions:

  1. cyber deception can uncover hidden compromises already inside networks
  2. cyber deception can detect new attacks as they happen
  3. cyber deception can change attacker behaviour if attackers think deception is in play

These are the right three assumptions to test. They map cleanly onto three fundamental defensive objectives:

  • Retrospective discovery: finding “unknown knowns” already present in an environment
  • Real-time detection: turning attacker interaction into high-confidence signal
  • Adversary cost-imposition: adding friction, uncertainty, and wasted effort to attacker operations

Importantly, the NCSC treated deception not as a single product category (“honeypots”) but as a broader defensive capability spanning multiple environments, including OT. That breadth matters. The value of deception depends heavily on what can realistically be instrumented without disrupting operations or introducing unacceptable risk.

5. “Cyber deception can work” — but the trials surface the hard truth: it’s a programme, not a product

The NCSC’s first key finding should be mandatory reading for anyone considering deception: effectiveness depends on data, context, and strategy, and without a plan organisations risk deploying tools that generate noise rather than insight.

This aligns with how more mature frameworks describe adversary engagement. Deception is not a fire-and-forget technology stack; it is an ongoing process that requires planning, placement, learning, and adjustment.

Why “not plug-and-play” is structural, not incidental

Cyber deception is inherently socio-technical:

  • You are deliberately creating assets intended to be touched by adversaries.
  • You must decide where they sit, what they look like, and what happens when they are touched.
  • You must keep them consistent with a changing environment — identity, endpoints, cloud resources, networks, and OT constraints.

A deception deployment without a response concept is just theatre. A deception deployment without strong operational hygiene can become an attack surface in its own right.

The NCSC explicitly notes that outcome-based metrics were not readily available and require development. This is not a footnote; it is the central problem. Without outcome metrics, organisations cannot compare providers, justify investment, or scale deception safely.

6. The “language barrier” finding is a quiet indictment of the market

The NCSC highlights widespread confusion and inconsistent terminology across the cyber deception industry and commits to standardising its vocabulary.

This is more significant than it sounds. When a market cannot agree on what things are called, buyers cannot:

  • write clear procurement requirements,
  • compare products meaningfully,
  • define success criteria, or
  • avoid category errors (confusing deception with EDR, sandboxes, or generic telemetry).

What a useful taxonomy would separate

A practical vocabulary should distinguish between:

  • Decoys: systems or services designed to be attacked
  • Lures / breadcrumbs / honeytokens: artefacts such as fake credentials, canary files, or tokens
  • Instrumentation: the telemetry generated and how it is validated
  • Engagement behaviours: redirection, delay, adaptive content, or containment
  • Operational model: SOC-owned versus platform-owned, centralised versus distributed
  • Safety controls: isolation, segmentation, access control, and blast-radius limitation

Without this clarity, “cyber deception” risks remaining a marketing umbrella rather than a governable control category.

7. Covert vs overt deception: a strategic tension the trials make explicit

One of the most interesting findings is that 90% of trial participants would not publicly announce their use of cyber deception, for fear of tipping off attackers.

This instinct is understandable. However, it sits in tension with academic research suggesting that when attackers believe deception is present, their confidence drops, their pace slows, and their costs increase.

A critical interpretation: this is not a binary choice

The framing of covert versus overt deception is too simplistic. In practice, organisations can — and arguably should — separate:

  • Technical implementation, which remains covert, from
  • Strategic signalling, which can be selectively overt.

Selective overt signalling might appear in legal language, incident response communications, supplier security requirements, or public security posture statements, without disclosing technical details.

The real strategic objective is attacker uncertainty, not disclosure. The unanswered question — and one the NCSC is uniquely placed to study — is which forms of overt signalling impose attacker cost without accelerating attacker adaptation.

8. The gap in guidance: where the NCSC can add real value — and where it must be careful

Organisations told the NCSC they want impartial advice, real-world case studies, and reassurance that tools are effective and safe. They also reported difficulty navigating a crowded and uneven market.

This is exactly the kind of problem a national cyber authority should help solve. But it must do so carefully. Guidance should not drift into implicit vendor endorsement or become a proxy certification scheme.

What “good guidance” would actually look like

High-value outputs would include:

  • Use-case-driven playbooks (credential misuse, lateral movement detection, insider threat guardrails, OT ingress monitoring)
  • Minimum safety baselines (segmentation, isolation, egress controls, identity boundaries)
  • Evaluation methodologies (how to test signal quality, false positives, and operational overhead)
  • Outcome metrics that can be applied consistently
  • Failure modes and anti-patterns, not just success stories

Because this work sits within Active Cyber Defence experimentation, the NCSC is already signalling that evidence should translate into service design. The challenge is ensuring that translation remains evidence-led rather than enthusiasm-led.

9. Risks: the trials correctly warn about false confidence — but the risk surface is broader

The NCSC warns that misconfiguration can introduce vulnerabilities, create blind spots, or foster false confidence, and that deception requires ongoing maintenance as environments evolve.

This warning is well-founded, but incomplete. A robust risk assessment for cyber deception should explicitly consider:

  1. Containment and breakout risk
    Decoys must be isolated so attacker tooling cannot pivot into production. This is a foundational safety property, not a design preference.
  2. Telemetry pollution
    Poorly tagged or integrated decoys can contaminate asset inventories, vulnerability data, and monitoring baselines.
  3. Operational drag
    Low-quality deployments generate noise from scanners, misconfigurations, or legitimate administrative activity.
  4. Legal and ethical boundaries
    Most organisations are not law enforcement. Active engagement beyond observation raises questions about proportionality, third-party impact, privacy, and consent.
  5. Adversary learning effects
    Obvious or poorly maintained deception teaches attackers what to ignore, potentially reducing future detection effectiveness.

Ignoring these risks does not make deception safer; it simply makes failures harder to detect.

10. Is this just another tool for the “big boys”?

A common perception is that cyber deception is only viable for large enterprises with mature SOCs, dedicated threat hunters, and spare engineering capacity. Historically, that perception was justified. Early deception platforms were complex, infrastructure-heavy, and operationally demanding.

That is no longer universally true — but the scaling question still matters.

Why deception has traditionally favoured large organisations

Deception has typically required:

  • Well-mapped environments
  • Clear separation between production and non-production systems
  • Dedicated monitoring and response capability
  • The ability to safely host and isolate decoys

Large enterprises are more likely to have these foundations in place, making deception easier to deploy without introducing risk.

How deception can scale down into SME environments

For small and medium-sized organisations, deception only becomes viable when it is simpler, narrower, and safer.

In SME contexts, effective deception tends to focus on:

  • Identity-centric lures, such as fake admin accounts or API tokens
  • High-value breadcrumbs, placed where attackers commonly probe (cloud consoles, file shares, backups)
  • Managed or hosted deception, where isolation and maintenance are handled by a provider
  • Clear, low-volume alerting, integrated directly into existing tooling rather than requiring a SOC

The goal is not full attacker engagement, but early, unambiguous warning that something is wrong. One high-confidence alert that triggers rapid containment can be far more valuable to an SME than dozens of low-confidence detections.

In this sense, deception can act as a force multiplier, compensating for limited monitoring resources rather than adding to the burden.

What about citizens and consumers?

At the individual level, cyber deception looks very different — and far more limited.

Most consumers are not deploying decoys or engagement environments. However, deception concepts already appear implicitly in:

  • Canary email addresses used to detect data breaches or misuse
  • Decoy payment or identity details monitored for fraudulent activity
  • Platform-level deception, where service providers plant traps to detect account takeover, bot activity, or fraud

For citizens, deception is not something they deploy themselves; it is something that platforms and service providers deploy on their behalf. The challenge here is transparency and trust: users benefit from deception without necessarily knowing it exists, while providers must ensure it is used proportionately and safely.

The real scaling question

The critical question is not whether deception can scale technically, but whether it can scale operationally and ethically.

  • Can it be deployed without increasing risk?
  • Can it be maintained without specialist teams?
  • Can it deliver value without overwhelming response capacity?
  • Can it be used responsibly when deployed at population scale?

If the answer to those questions is yes, deception becomes a broadly useful defensive capability. If not, it remains confined to the upper tiers of organisational maturity.

11. A reality check: cyber deception is not an SME-level control (yet)

At this point, it’s worth being brutally honest about where cyber deception fits — and where it doesn’t.

There is a temptation, whenever a new defensive capability shows promise, to argue that it can be “scaled down” to small and medium-sized enterprises. In the case of cyber deception, that argument currently fails a basic reality test.

By most credible estimates, a large majority of UK organisations still operate with minimal or no formal cyber security capability at all. Many lack even basic asset visibility, centralised logging, or defined incident response processes. In that context, cyber deception is not an entry-level control — it is a maturity-dependent capability.

Deception assumes several prerequisites that most SMEs simply do not have:

  • A clear understanding of what systems, identities, and data actually exist
  • Baseline security hygiene (patching, identity controls, segmentation)
  • Some ability to monitor and respond to alerts
  • Confidence that new systems will not introduce additional risk

Without those foundations, deception does not fail gracefully — it fails dangerously. A misconfigured decoy in a poorly understood environment is not a clever trap; it is just another unmanaged system.

Why this matters for national strategy

Over-selling deception as an SME solution risks repeating a familiar policy mistake: promoting advanced controls before basic ones are in place.

For organisations with no meaningful cyber capability, the priority is still:

  • knowing what they own,
  • controlling who can access it,
  • patching it, and
  • backing it up.

Deception does not compensate for the absence of these fundamentals. It amplifies capability where it exists; it does not create it from nothing.

Where deception actually fits today

Cyber deception currently makes sense in environments that have already crossed a maturity threshold:

  • large enterprises and critical national infrastructure operators,
  • organisations with SOC or managed detection capability,
  • cloud-heavy environments where identity abuse is a primary risk,
  • OT environments where traditional detection is limited but safety is paramount.

In these contexts, deception can provide disproportionate value by delivering high-confidence signal and earlier detection. Outside them, it is more likely to become shelfware or riskware.

What about citizens and very small organisations?

For individuals and micro-organisations, cyber deception is not something they deploy. It is something that platforms deploy on their behalf.

When banks, cloud providers, email platforms, and identity providers use deception internally, citizens benefit indirectly — through faster fraud detection, reduced account takeover, and improved platform resilience. That is where deception meaningfully touches the general population today.

The honest conclusion

Cyber deception is not a democratising control in the near term. It does not close the gap between organisations with cyber capability and those without it. If anything, it risks widening that gap if positioned irresponsibly.

For now, deception belongs above the basics, not instead of them. It is a tool for organisations that already know what “normal” looks like and have the capacity to respond when something abnormal happens.

The real national challenge is not how to get deception into SME environments — it is how to get the fundamentals in place first.

12. The measurement problem: turning intuition into defensible outcomes

The NCSC reports that organisations believe deception offers value, but lack outcome-based metrics.

This is solvable. A practical metrics framework could include:

Detection value

  • Time to first high-confidence alert after compromise
  • Signal precision (how often alerts correspond to genuinely malicious behaviour)
  • Kill-chain coverage mapping

Investigation efficiency

  • Mean time to triage compared to non-deception alerts
  • Investigation yield: how often deception interaction produces actionable intelligence

Adversary cost-imposition

  • Dwell time inflation within engagement zones
  • Behavioural deflection away from crown-jewel assets
  • Abandonment or hesitation proxies (used cautiously and contextually)

Safety and maintainability

  • Configuration drift rates and remediation time
  • Evidence of blast-radius containment
  • Operational coupling between production change and deception upkeep

Without metrics like these, claims about “cost imposition” and “early warning” remain aspirational rather than operational.

13. Strategic implications: why this matters for national resilience — if executed well

The NCSC argues that cyber deception can deliver early warning, high-quality intelligence, and adversary cost-imposition, contributing to national cyber resilience.

That argument holds — but only if three conditions are met:

  1. deployments are safe by design,
  2. signals are integrated into operational response, and
  3. outcomes are measurable and comparable.

If those conditions are satisfied, deception becomes one of the few controls capable of generating consistently high-confidence attacker interaction in an era of alert fatigue. If they are not, deception risks becoming another overpromised, under-governed capability.

14. What should come next from the NCSC

To realise the ambition implied by “nation-scale,” future NCSC outputs should include:

  1. a standard vocabulary and reference model for cyber deception,
  2. transparency on trial methodology and evaluation criteria (even if anonymised),
  3. a vendor-neutral metrics framework,
  4. explicit deployment safety patterns and “do not” guidance,
  5. realistic case studies including effort and operating cost,
  6. a clear ethical and proportionality position for defensive deception in UK organisations, and
  7. publish anonymised trial outcome summaries (even at coarse granularity), such as detections by environment type or interaction class, to allow independent assessment of efficacy.

One additional observation: the blog post notes that it was created using generative AI tooling. That does not invalidate the conclusions, but it does increase the importance of publishing underlying evidence and methods, so that narrative smoothness does not mask uncertainty.

15. Practical takeaways for organisations considering deception in 2026

For security leaders evaluating cyber deception:

  • Treat deception as a capability programme, not a bolt-on tool.
  • Start from strategic visibility gaps, not from vendor features.
  • Demand containment and safety evidence as a baseline requirement.
  • Define outcome metrics before procurement.
  • Make a deliberate decision on covert versus overt signalling, rather than defaulting to silence.

16. Bottom line

The NCSC’s cyber deception trials represent a serious attempt to move the conversation from theory and marketing to evidence. The findings are credible precisely because they are cautious: deception can work, but it requires planning; language is inconsistent; most organisations stay covert; guidance is missing; and misconfiguration risk is real.

Whether this work becomes transformational depends on the next phase. If the NCSC can turn these insights into measurable outcomes, safe deployment patterns, and vendor-neutral guidance, cyber deception can mature into a meaningful pillar of layered defence. If not, it risks remaining what it has often been to date: a compelling idea, unevenly executed, difficult to justify, and easy to misuse.

17. References