Fake credentials, simulated servers and carefully placed digital assets are becoming increasingly relevant to enterprise cybersecurity. Advanced deception technologies provide security teams with an additional method of detecting attackers who have already gained access to corporate networks and are attempting to move between systems. Rather than relying exclusively on the analysis of network traffic and system logs, organisations can deploy controlled deception environments designed to reveal suspicious activity. Recent guidance from the US Cybersecurity and Infrastructure Security Agency (CISA) reinforces the relevance of this approach, while industry case studies suggest that targeted deception may also offer economic advantages over expanding conventional security monitoring infrastructure.

Detecting attackers after an initial compromise remains a major challenge for Security Operations Centres (SOCs). Although firewalls, endpoint protection and identity management systems can prevent or identify many threats, attackers increasingly exploit legitimate credentials and administrative tools to operate within corporate environments. Such living-off-the-land techniques make malicious activity difficult to distinguish from normal system operations, particularly in large organisations with complex networks, cloud infrastructure and distributed workforces.

Advanced deception addresses this visibility problem by introducing digital resources that appear legitimate but are specifically designed to identify unauthorised interaction. These resources may include simulated application servers, database services, administrative accounts or strategically placed credentials. Unlike conventional monitoring systems, which analyse large volumes of operational data to identify suspicious patterns, deception technologies generate alerts when users or processes interact with assets that have no legitimate business purpose.

From passive monitoring to targeted attacker detection

At the centre of advanced deception are two complementary techniques: decoys and honeytokens. Decoys simulate systems, services or network resources that might attract an intruder conducting reconnaissance. Honeytokens, by contrast, are individual digital objects such as credentials, documents or database entries that can reveal suspicious activity when accessed or used. Both are intended to create additional detection opportunities within the corporate environment without exposing genuine business-critical assets.

For example, an attacker who discovers apparently valid administrator credentials may attempt to use them to access a privileged system. If those credentials were deliberately placed as a honeytoken, the attempt can trigger an alert and provide information about the source and nature of the activity. Similarly, an interaction with a simulated database server can indicate that a user or automated process is exploring resources outside normal operational requirements.

The strategic value lies in the ability to detect behaviours associated with reconnaissance, credential misuse, privilege escalation and lateral movement. These activities can be difficult to recognise through conventional monitoring when attackers rely on authorised tools or compromised accounts. Deception does not eliminate the need for log analysis or endpoint detection, but it can provide additional evidence that helps analysts prioritise investigations.

The approach gained further institutional recognition in September 2026, when CISA published its guidance Using Cyber Decoys to Strengthen Detection and Response. The agency identified cyber decoys as a way to detect post-compromise activity, support threat intelligence collection and improve the relevance of security alerts. Its recommendations incorporate the MITRE ATT&CK and MITRE Engage frameworks, encouraging organisations to design deception environments around realistic adversary behaviour and integrate them into existing Zero Trust and incident-response strategies.

Logistics case study: Detecting activity beyond expected targets

A practical example comes from a case study published by cybersecurity technology provider LABYRINTH involving a freight audit and logistics visibility company. The organisation deployed deception assets across several network segments, including publicly accessible services, development environments and internal workstations. The objective was to improve the detection of suspicious activity both at the network perimeter and within systems that could be reached through remote access.

According to the vendor’s documentation, the resulting observations challenged the security team’s initial assumptions about which information attackers were most interested in. While the organisation had expected particular attention to its customer database, the recorded activity indicated greater interest in information relating to unfinished transactions. This prompted a more focused security review of the relevant applications and their handling of incoming data.

The deception infrastructure also identified unusual network scans originating from a software developer’s workstation connected through a corporate VPN. Further observations reportedly included brute-force attempts and activity associated with exploitation and privilege escalation. The affected workstation was subsequently isolated for forensic examination.

The case illustrates how deception technologies can provide additional visibility into suspicious behaviour that might otherwise be difficult to interpret within broader network traffic. They may also help security teams identify unexpected attack paths rather than concentrating exclusively on assets previously classified as high-value targets. However, the findings come from a vendor-published case study and have not been independently verified. The documented observations should therefore be treated as an example of a reported deployment rather than conclusive evidence of general detection performance.

The economics of detection: Can deception reduce SIEM expansion costs?

Beyond technical capabilities, advanced deception raises an important question about the cost of security monitoring. As organisations expand digital infrastructure, the volume of information collected by Security Information and Event Management (SIEM) systems can increase substantially. More comprehensive monitoring may require additional storage capacity, processing resources, detection engineering and analyst time. Depending on licensing arrangements and infrastructure requirements, these costs can become significant.

A second LABYRINTH case study describes a multinational life sciences and pharmaceutical research organisation employing more than 3,000 people. The company already operated an established security infrastructure incorporating SIEM, endpoint detection and response, next-generation firewalls and centralised monitoring. Its challenge was to improve visibility into internal network reconnaissance and attacks targeting Active Directory without substantially increasing the operational cost of its existing systems.

According to the case study, expanding conventional monitoring to achieve the required coverage would have generated more than 100 gigabytes of additional telemetry per day. The proposed approach would also have required the organisation to increase its SIEM capacity by a factor of approximately 2 to 2.5, alongside further detection engineering and maintenance. Instead, the company introduced a specialised detection layer combining deception assets with local analysis of selected identity-related security events.

LABYRINTH reported that the resulting architecture provided the targeted additional detection capabilities at approximately one-fifth of the estimated cost of the alternative SIEM expansion. The vendor also claimed that the organisation avoided a six-figure annual increase in expenditure.

These figures illustrate the potential economic appeal of selective detection strategies, but they require careful interpretation. The reported savings are based on a comparison of specific implementation options within a single organisation and have not been independently audited. Furthermore, the deployment combined decoy-based detection with local analysis of Active Directory activity. Its economic outcome cannot therefore be attributed exclusively to deception technology.

For security managers, the relevant question is whether targeted deception can complement existing monitoring more cost-effectively than expanding centralised telemetry collection for particular detection requirements. A reliable assessment must consider licensing, implementation, integration, maintenance and analyst workload, as well as the actual security coverage achieved. Deception and comprehensive SIEM monitoring fulfil overlapping but not identical functions, making a universal cost comparison inappropriate.

Implementation challenges in distributed enterprise environments

The effectiveness of deception technology depends heavily on the quality of its deployment. Digital decoys need to be sufficiently realistic to attract relevant interactions while remaining isolated from genuine business systems. Their placement should reflect the organisation’s network architecture, privileged access paths and likely attacker behaviour. Poorly configured assets may be recognised and avoided by experienced attackers, while inappropriate integration can introduce unnecessary operational complexity.

False alerts also remain possible. Legitimate vulnerability scanning, automated discovery tools and administrative processes may interact with deception assets, requiring security teams to distinguish authorised activity from suspicious behaviour. An alert generated by a decoy is therefore a strong investigative signal under suitable conditions, but not automatic proof of a malicious intrusion.

Operational integration is equally important. Detection events need to reach the appropriate security monitoring platforms and incident-response teams, where they can be correlated with other evidence and translated into proportionate action. Without defined escalation procedures and sufficient analytical capacity, the additional visibility provided by deception may deliver limited practical benefit.

These considerations are particularly relevant to multinational organisations operating across European, Middle Eastern and African markets. Distributed infrastructures, cloud services, remote access arrangements and different local operating requirements can complicate both the deployment of deception assets and the coordination of investigations. An effective strategy must therefore account for network segmentation, data governance, security responsibilities and the relationships between internal teams and external service providers.

For organisations protecting industrial networks or critical infrastructure, deployment also requires attention to operational safety and system availability. Any interaction with operational technology environments must be designed to avoid disruption, with detection requirements balanced against the reliability of production systems.

Advanced deception as part of a broader cyber resilience strategy

The development of advanced deception reflects a wider change in cybersecurity strategy. Preventing unauthorised access remains essential, but organisations increasingly need capabilities that identify attackers who have already bypassed initial defences. Digital decoys offer one approach to improving this visibility by creating controlled opportunities for suspicious behaviour to become observable.

The technology may be particularly useful where attackers attempt to exploit legitimate credentials, conduct internal reconnaissance or move laterally between systems. At the same time, its contribution depends on realistic deployment, effective alert handling and integration with existing security controls. It cannot guarantee that every attacker will encounter a deception asset, nor can it replace established incident-response capabilities.

The economic argument is similarly conditional. Vendor case studies indicate that targeted detection architectures may reduce the need for additional centralised monitoring in certain scenarios, but broader claims of cost savings require independent evidence and organisation-specific assessment.

For international enterprises, the significance of advanced deception lies in its ability to challenge one of the traditional advantages enjoyed by intruders: the assumption that the resources they discover inside a compromised network are genuine. By turning selected systems, credentials and data into controlled detection points, security teams can gain additional insight into adversary activity while potentially improving the efficiency of their threat detection operations.

Editorial sources: The article draws on the US Cybersecurity and Infrastructure Security Agency’s guidance Using Cyber Decoys to Strengthen Detection and Response, published on 16 September 2026; LABYRINTH’s technical overview Advanced Deception: Transforming Defensive Strategies; and vendor-published case studies covering a freight audit and logistics visibility provider and a multinational life sciences and pharmaceutical research organisation. Additional context is based on information supplied by DAGMA GmbH, which distributes the LABYRINTH platform.