GigaOm Radar for Deception Technology v4

Cybersecurity technology, and more specifically deception technology, has become increasingly important in today’s digital landscape. Deception solutions, including baits, lures, and traps, primarily focus on tricking threat actors into interacting with a decoy in order to provide early threat detection and robust intelligence that helps in responding to cyberattacks. Their significance is paramount considering the continuous rise in advanced persistent threats, spear-phishing attacks, and insider threats.

This technology is essential to all individuals and businesses operating digitally, especially large corporations, government institutions, and industries like finance, healthcare, and retail, which are popular targets of cybercriminals. As systems become interconnected and more complex, with the expansion of cloud services and internet of things (IoT) devices, the surface for potential attacks grows. At this critical juncture, the role of cybersecurity technology becomes pivotal.

From a business perspective, strategic deployment of deception technology significantly reduces the risks of data breaches, system intrusions, and resulting downtime. It can also provide comprehensive insights into adversaries’ tactics and an organization’s vulnerabilities, enabling the sculpting of a more resilient defense system.

Yet, for company executives, deception technology’s importance goes beyond securing business infrastructure. In a world where a company’s reputation significantly hinges on its ability to safeguard customer data, executives are under increased pressure to ensure data security. With harsher data protection regulations and hefty penalties for data breaches, this is no longer a contingency plan but a business imperative. Organizations without robust cybersecurity measures risk financial losses and legal repercussions, may erode customer trust, and negatively impact their business reputation.

Deception technology has been evolving, moving beyond basic decoy systems to offer multilayered, adaptive deception techniques across different environments: on-premises, cloud, hybrid, IoT, and operational technology (OT). Driven by AI and machine learning (ML) methodologies, the latest vendors entering the market signify a promising shift towards proactive security instances, with a strong capability to deceive, detect, and defer sophisticated cyber attackers. Thus, for businesses striving to stay ahead in the cybersecurity realm, understanding and implementing these evolving cybersecurity technologies is an inevitable strategic mandate

This is our fourth year evaluating the deception technology space in the context of our Key Criteria and Radar reports. This report builds on our previous analysis and considers how the market has evolved over the last year.

This GigaOm Radar report examines 13 of the top deception technology solutions and compares offerings against the capabilities (table stakes, key features, and emerging features) and nonfunctional requirements (business criteria) outlined in the companion Key Criteria report. Together, these reports provide an overview of the market, identify leading deception technology offerings, and help decision-makers evaluate these solutions so they can make a more informed investment decision.

GIGAOM KEY CRITERIA AND RADAR REPORTS

The GigaOm Key Criteria report provides a detailed decision framework for IT and executive leadership assessing enterprise technologies. Each report defines relevant functional and nonfunctional aspects of solutions in a sector. The Key Criteria report informs the GigaOm Radar report, which provides a forward-looking assessment of vendor solutions in the sector.

To help prospective customers find the best fit for their use case and business requirements, we assess how well deception technology solutions are designed to serve specific target markets and deployment models (Table 1).

For this report, we recognize the following market segments:

• Small-to-medium business (SMB): These deception technology buyers seek solutions that are easy to use and deploy and can be integrated into their existing security infrastructure without significant complexity or resource requirements. They also prioritize managed solutions that can be monitored and maintained by a single provider, reducing the need for in-house expertise. Finally, they look for cost-effective solutions that provide robust protection without breaking the bank.

• Large enterprise: These deception technology buyers seek solutions that can handle large volumes of data and users and provide granular control over deception tactics and techniques. They also value customization capabilities that allow them to tailor the solution to their particular security needs and environment.

• Public sector: These deception technology buyers seek solutions that can help them meet strict security regulations and standards, such as NIST and FISMA, while also providing an easy-to-use interface that requires minimal training or expertise. They value solutions that can integrate with existing security tools and infrastructure and provide robust reporting and analytics capabilities to help them demonstrate compliance and threat detection effectiveness.

In addition, we recognize the following deployment models:

• Physical appliance: A hardware-based deployment model that provides a dedicated, on-premises deception solution.

• Virtual appliance: A software-based deployment model that runs on VMs, providing flexibility and scalability.

• Public cloud image: A cloud-based deployment model that provides a scalable and on-demand deception solution that is accessible via public cloud platforms.

• Software only: A lightweight deployment model that installs deception agents or binaries directly onto endpoints or servers.

• SaaS: A cloud-based deployment model that offers a subscription-based deception solution that is managed and maintained by the provider.

Table 1. Vendor Positioning: Target Market and Deployment Model

Table 1 components are evaluated in a binary yes/no manner and do not factor into a vendor’s designation as a Leader, Challenger, or Entrant on the Radar chart (Figure 1).

“Target market” reflects which use cases each solution is recommended for, not simply whether that group can use it. For example, if an SMB could use a solution but doing so would be cost-prohibitive, that solution would be rated “no” for SMBs.

All solutions included in this Radar report meet the following table stakes—capabilities widely adopted and well implemented in the sector:

• Digital trail monitoring

• Forensic data collection

• Target-specific customization

• High-interaction deception

• Real-time alerting

• Deployment management

Tables 2, 3, and 4 summarize how each vendor in this research performs in the areas we consider differentiating and critical in this sector. The objective is to give the reader a snapshot of the technical capabilities of available solutions, define the perimeter of the relevant market space, and gauge the potential impact on the business.

• Key features differentiate solutions, highlighting the primary criteria to be considered when evaluating a deception technology solution.

• Emerging features show how well each vendor implements capabilities that are not yet mainstream but are expected to become more widespread and compelling within the next 12 to 18 months.

• Business criteria provide insight into the nonfunctional requirements that factor into a purchase decision and determine a solution’s impact on an organization.

These decision criteria are summarized below. More detailed descriptions can be found in the corresponding report, “GigaOm Key Criteria for Evaluating Deception Technology Solutions.”

Key Features

• Cloud-native deception: Cloud-native deception provides purpose-built deceptive assets that seamlessly integrate with cloud environments, mimicking authentic cloud services, containers, and infrastructure components. This specialized approach ensures deception is effective across multicloud architectures while maintaining cloud-specific authenticity and scalability.

• Cross-platform support: Cross-platform support ensures compatibility and functionality across various operating systems and network architectures, enhancing the versatility and effectiveness of security measures. It is a vital feature of modern deception technology, designed to ensure that deceptive elements such as honeypots, decoys, and other traps are fully functional across a diverse range of operating systems, hardware platforms, and network environments. This inclusivity enables organizations to deploy deception strategies seamlessly, regardless of their IT infrastructure’s complexity or diversity.

• Behavioral analysis: Behavioral analysis involves scrutinizing interactions with decoys to identify and understand malicious activities based on behavior patterns and anomalies. It is the methodical examination of how attackers interact with decoy systems, such as honeypots or other deceptive methods. This process entails monitoring and analyzing the actions, methods, and patterns of behavior exhibited by potential intruders.

• Customization of engagement level: Customization of engagement level means tailoring the interaction depth with decoys, from low-interaction simple traps to high-interaction complex environments. It is a key feature in deception technology that enables the creation of decoys and traps with varying levels of complexity and interactivity.

• Multilayer deception: Multilayer deception involves deploying a series of interconnected decoys and traps at various network levels, creating a comprehensive defense strategy. It is an advanced strategy in deception technology that involves setting up a series of deceptive elements—such as honeypots, decoy systems, and fake data repositories—across different layers of an organization’s IT infrastructure.

• OT and IoT-specific decoys: OT/IoT-specific decoys are specialized traps designed to mimic OT and IoT devices, detecting targeted cyberthreats in these environments. These decoys are crafted to appear as authentic OT/IoT components—such as industrial control systems, smart sensors, and connected appliances—to attract and engage attackers targeting these specific environments.

Table 2. Key Features Comparison

Emerging Features

• Identity-focused deception: Identity-focused deception creates sophisticated decoy credentials, access tokens, and identity-related breadcrumbs specifically designed to detect credential theft and abuse attempts. This capability directly addresses the growing trend of identity-based attacks by creating deceptive identity elements that appear authentic to attackers while providing early warning of credential harvesting and lateral movement attempts.

• LLM assistant: A large language model (LLM) assistant automatically generates, customizes, and maintains contextually relevant deceptive content and assets. This AI-powered capability ensures deceptive elements remain convincing and aligned with the organization’s actual environment while reducing manual configuration effort and improving the overall effectiveness of deception deployments.

Table 3. Emerging Features Comparison

Business Criteria

• Cost: Cost evaluation involves analyzing the financial implications of deploying and maintaining the system, considering both initial investment and ongoing operational expenses. The cost criterion for evaluating deception technology encompasses a comprehensive analysis of the financial aspects, including initial setup costs, licensing fees, and the expenses related to the deployment and maintenance of the technology.

• Scalability: Scalability assesses a solution’s ability to adapt and expand efficiently with the growing needs and complexity of an organization’s network infrastructure. The scalability criterion evaluates how well deception technology can accommodate an increasing number of users, devices, and network traffic without compromising performance.

• Flexibility: Flexibility refers to the system’s adaptability to various network environments and its ability to tailor defensive measures to specific security needs. This criterion focuses on the system’s capability to adjust to different network architectures, operating systems, and evolving cyberthreats.

• Ease of use: User experience looks at how intuitive, manageable, and user-friendly the system is for administrators and security teams. For this criterion, we assess the ease with which security personnel can deploy, manage, and interact with the deception technology. This includes the simplicity of setting up decoys, the clarity of real-time alerts, and the straightforwardness of analyzing data from deceptive elements.

• Ecosystem: The deception technology ecosystem encompasses integration capabilities with existing security tools, threat intelligence sharing networks, and partnerships with major security vendors and cloud providers. A robust ecosystem ensures deception platforms can enhance the overall security infrastructure while providing seamless operational workflows and enriched threat intelligence.

Table 4. Business Criteria Comparison

The GigaOm Radar plots vendor solutions across a series of concentric rings, with those set closer to the center judged to be of higher overall value. The chart characterizes each vendor on two axes—balancing Maturity versus Innovation and Feature Play versus Platform Play—while providing an arrowhead that projects each solution’s evolution over the coming 12 to 18 months.

Figure 1. GigaOm Radar for Deception Technology

As you can see in Figure 1, this Radar chart reveals several interesting patterns in the deception technology market. The chart shows a distribution between the Maturity and Innovation axes, though the Maturity hemisphere clearly delivers the majority of solutions. There’s a notable cluster in the upper-right Maturity/Platform Play quadrant, underscoring that this is a particularly competitive space where vendors focus on established, comprehensive solutions.

The Platform Play side shows more activity than the Feature Play side, indicating the market is moving toward integrated, comprehensive deception technology solutions rather than point products. This aligns with enterprise preferences for consolidated security platforms that reduce complexity and integration challenges.

The presence of multiple Fast Movers and Forward Movers aligns with our research, confirming that vendors are steadily introducing new features and enhancements. Most vendors fall within the Challenger ring, with a select few recognized as Leaders. However, several vendors are on the cusp of the Leader ring, indicating that valuable solutions exist beyond the Leaders, depending on the customer’s use case.

While innovation is present, the clustering pattern shows that many vendors are taking an incremental approach to development, balancing new capabilities with proven solutions. The spread of vendors across different sections confirms that multiple valid approaches exist to solving customer challenges.

The distribution pattern suggests a maturing market that has yet to consolidate around a few dominant players. The presence of vendors across all sections indicates diverse customer needs that can’t be met with a one-size-fits-all approach.

In reviewing solutions, it’s important to keep in mind that there are no universal “best” or “worst” offerings; every solution has aspects that might make it a better or worse fit for specific customer requirements. Prospective customers should consider their current and future needs when comparing solutions and vendor roadmaps.

INSIDE THE GIGAOM RADAR

To create the GigaOm Radar graphic, key features, emerging features, and business criteria are scored and weighted. Key features and business criteria receive the highest weighting and have the most impact on vendor positioning on the Radar graphic. Emerging features receive a lower weighting and have a lower impact on vendor positioning on the Radar graphic. The resulting chart is a forward-looking perspective on all the vendors in this report, based on their products’ technical capabilities and roadmaps.

Note that the Radar is technology-focused, and business considerations such as vendor market share, customer share, spend, recency or longevity in the market, and so on are not considered in our evaluations. As such, these factors do not impact scoring and positioning on the Radar graphic.

For more information, please visit our Methodology.

Acalvio: ShadowPlex*

Solution Overview
Acalvio specializes in cyber deception and threat detection solutions, with ShadowPlex serving as its primary security offering. The solution utilizes autonomous deception technology and AI to detect and respond to threats within enterprise environments.

ShadowPlex is a comprehensive deception solution that operates as a standalone product. It deploys and manages decoys across cloud, on-premises, and hybrid environments to detect adversary presence and activities. The solution includes three main components: ShadowPlex Cloud Security for cloud-native deployments, ShadowPlex Advanced Threat Defense for on-premises implementations, and ShadowPlex Identity Protection for Active Directory protection.

The solution takes a structured approach to deception technology, focusing on the scalable and consistent deployment of deception assets. Acalvio emphasizes operational efficiency and maintains a methodical development cycle that prioritizes stability and reliable threat detection capabilities.

Acalvio is positioned as a Leader and Outperformer in the Maturity/Platform Play quadrant of the deception technology Radar report.

Strengths
Acalvio scored well on a number of decision criteria, including:

• Cross-platform support: Acalvio offers comprehensive support across public cloud, private cloud, and on-premises environments, including Kubernetes, IoT, OT, and traditional IT systems like AIX, FreeBSD, Linux, macOS, and Windows, with varying levels of decoy interaction capabilities.

• Customization of engagement level: Acalvio provides dynamic deception features that allow real-time adjustment of interaction types based on policy settings, enabling defenders to gather more actionable data while potentially delaying or preventing detection of the deception technology.

• OT/IoT-specific decoys: Acalvio features specialized OT/IoT capabilities, including native support for multiple OT/ICS protocols such as Modbus, Siemens S7, and BACnet, which is available as a white-labeled solution through Honeywell called the Threat Defense Solution.

Acalvio was classified as an Outperformer given its ability to continuously improve on existing features, expand its feature set, and rapidly develop new services, demonstrating significant market momentum and innovation potential.

Challenges
Acalvio scored well on all key features but has room for improvement in the following decision criteria:

• Cloud-native deception: Organizations with complex hybrid environments may find the separation between cloud and on-premises deception capabilities challenging to manage effectively. While the solution offers comprehensive cloud coverage, the integration complexity across multicloud and hybrid networks might present operational challenges for teams with limited cloud expertise.

• Behavioral analysis: The effectiveness of Acalvio’s AI-driven analysis system may be limited by customers’ inability to tune or adjust the AI model training. Organizations with unique threat landscapes or specific detection requirements might find this lack of customization restrictive, particularly in scenarios where standard AI models may not align with their specific use cases.

• Multilayer deception: The solution’s architecture of separate base and attack-specific layers may create unnecessary complexity. Security teams might struggle to understand the distinct features and capabilities of each layer, potentially leading to suboptimal deployment configurations or missed detection opportunities.

Purchase Considerations
Acalvio provides clear licensing terms with a straightforward deployment model that doesn’t require extensive infrastructure investments. The solution demonstrates strong cost efficiency through built-in automation capabilities and the absence of additional third-party licensing requirements that are common in the deception technology market.

The solution is designed as a feature-complete offering that can operate independently while maintaining compatibility with existing security infrastructure through numerous integration points. This is evidenced by extensive integration capabilities with essential security technologies, including endpoint detection and response (EDR); security information and event management (SIEM); security orchestration, automation, and response (SOAR); and threat intelligence solutions, along with established partnerships with major cloud providers and security vendors.

An intuitive interface, including role-based views and guided configuration wizards, reduces implementation complexity. The solution’s “reflection” approach to deception deployment enables broad coverage across various technology environments while maintaining operational simplicity.

From a scalability perspective, Acalvio’s architecture allows for deployment flexibility across diverse environments. Their fluid deception technology extends the effectiveness of decoys by modulating behaviors, which reduces maintenance requirements and operational overhead.

Use Cases
Identity defense represents a standout use case where Acalvio detects unauthorized access attempts through strategically placed deception assets that monitor both cloud and on-premises identity systems. The solution’s ability to deploy fluid deception across multiple identity providers while integrating with existing identity and access management (IAM) infrastructure makes it particularly effective for organizations concerned with credential theft and privilege escalation.

OT/ICS security presents another compelling scenario where Acalvio’s reflection technology enables deception deployment without disrupting sensitive operational systems. The solution can emulate industrial protocols and devices while maintaining separation between IT and OT networks, providing early warning of threats targeting critical infrastructure.

Cloud-native security operations benefit from Acalvio’s ability to adapt deception assets automatically as cloud environments change. The solution’s integration with major cloud providers and ability to protect containerized workloads helps security teams maintain visibility across dynamic cloud infrastructure without requiring constant reconfiguration of deception elements.

CounterCraft: The Platform

Solution Overview
CounterCraft provides cyber deception technology designed to gather threat intelligence and detect adversaries. The company is dedicated to delivering deception capabilities for enterprise organizations and government entities.

The Platform is a comprehensive security offering that operates as a standalone product. The solution integrates deception, threat intelligence, and automated response capabilities through a centralized management console. It includes modules for campaign management, threat intelligence integration, and automated incident response.

CounterCraft implements a systematic approach to deception technology, emphasizing operational efficiency and ease of deployment across complex environments. Its solution methodology centers on delivering consistent, reliable deception campaigns that generate actionable threat intelligence.

CounterCraft’s offering maintains consistent functionality throughout the contract lifecycle. The vendor prioritizes stability and reliability, focusing on incremental improvements to existing capabilities such as deployment automation, threat detection accuracy, and intelligence-gathering functions. CounterCraft’s development approach emphasizes methodical advancement and structured updates, ensuring compatibility and maintaining a consistent user experience.

CounterCraft is positioned as a Leader and Outperformer in the Maturity/Platform Play quadrant of the deception technology Radar report.

Strengths
CounterCraft scored well on a number of decision criteria, including:

• Cloud-native deception: CounterCraft can deploy decoy VMs and cloud services in AWS and Azure environments, including support for S3 buckets, IAM keys, and integration with Microsoft 365 and Google Workspace, while collecting kernel-level telemetry from infected systems.

• Behavioral analysis: CounterCraft has the capability to provide custom threat intelligence gathered from deception technologies, demonstrating advanced behavioral analysis capabilities for clients.

• Multilayer deception: CounterCraft provides comprehensive management of deception campaigns that span internal networks, public networks, and cloud environments, enhanced by cloud user activity monitoring capabilities.

CounterCraft was classified as an Outperformer given its rapid expansion of features, particularly in cloud-native deception and behavioral analysis capabilities, along with its promising near-term roadmap that positions the company to outpace peers in the space.

Challenges
CounterCraft has room for improvement in the following decision criteria:

• Cross-platform support: Organizations with extensive IoT deployments may find the solution’s limited telemetry capabilities insufficient for comprehensive threat detection. This could be particularly challenging in environments where IoT devices are critical infrastructure components.

• Customization of engagement level: In scenarios requiring rapid response to sophisticated attackers, the automated nature of the decoys might not provide the real-time manual intervention capabilities needed. Security teams in highly regulated industries or those facing advanced persistent threats might find the preset interaction levels restrictive.

• OT/IoT-specific decoys: Organizations with specialized industrial protocols or legacy OT systems might encounter integration challenges. The solution’s focus on major vendors like Siemens and Allen-Bradley may leave gaps in environments using lesser-known or proprietary industrial control systems.

Purchase Considerations
The solution’s licensing structure is straightforward, with all features included in the base cost, though overall costs are influenced by its requirement for fully licensed operating systems in deployments. This creates a predictable pricing model without hidden fees or add-on modules but may impact the total cost of ownership.

CounterCraft operates as a feature-complete solution with native capabilities enhanced by ActiveSense and ActiveBehavior functionalities. The solution integrates with common security infrastructure, including SIEM, SOAR, and threat intelligence platforms, with a notable partnership with Elastic.co for enhanced SIEM integration.

The solution offers an intuitive user interface that balances accessibility with advanced functionality, providing straightforward access to basic features while maintaining depth for experienced users. Support services are included in the base cost, which adds value to the overall package.

Recent improvements to back-end horizontal scaling have enhanced the solution’s ability to handle larger deployments, though the VM-based approach may present some inherent scalability limitations compared to alternative deployment methods. The solution maintains consistent performance in standard deployment scenarios while supporting core security operations requirements.

Use Cases
Military and defense organizations benefit from CounterCraft’s full operating system deception capabilities for threat intelligence collection. The solution’s ActiveSense and ActiveBehavior features enable detailed adversary monitoring while maintaining convincing deception environments that can mirror complex military network structures.

Critical infrastructure protection represents another significant use case where CounterCraft deploys deception across both IT and OT networks. The solution’s ability to maintain separate, isolated environments while collecting detailed adversary tactics makes it effective for organizations requiring comprehensive visibility into threats targeting industrial systems.

Public sector threat intelligence operations leverage CounterCraft’s specialized deception campaigns to understand adversary techniques and gather actionable intelligence. The solution’s partnership with major global integrators facilitates deployment in government environments where detailed threat actor profiling and early warning capabilities are essential.

CyberTrap: CyberTrap Deception Platform

Solution Overview
CyberTrap develops and maintains deception technology focused on early threat detection and attacker behavior analysis. The company specializes in delivering enterprise-grade deception capabilities, emphasizing European market requirements and compliance standards.

The CyberTrap Deception Platform is a standalone product that provides comprehensive deception capabilities. It includes components for deception deployment, threat monitoring, and forensic analysis. Core offerings encompass the Enterprise Deception Server, Deception Host software, and Analysis Center for threat investigation.

CyberTrap implements a methodical approach to deception technology, focusing on reliable threat detection and detailed attack analysis. Its solution strategy emphasizes consistent performance and dependable deployment across enterprise environments, with particular attention to regulatory compliance and data privacy requirements.

As a mature solution provider, CyberTrap’s offering maintains consistent functionality throughout the contract lifecycle. The vendor prioritizes stability and operational reliability, making incremental improvements to existing capabilities in areas such as deployment efficiency, detection accuracy, and analysis capabilities. Its development approach focuses on structured advancement and maintaining compatibility with existing security infrastructure, ensuring a stable and predictable user experience.

CyberTrap is positioned as a Challenger and Fast Mover in the Maturity/Platform Play quadrant of the deception technology Radar report.

Strengths
CyberTrap scored well on a number of decision criteria, including:

• OT/IoT-specific decoys: CyberTrap can emulate OT/IoT devices, including programmable logic controllers (PLCs) and smart devices, using virtualized firmware for SCADA system simulation, though with basic emulation capabilities rather than full device replication.

• Behavioral analysis: CyberTrap can log attacker interactions with decoys, including commands, files, and network activity, while mapping behaviors to the MITRE ATT&CK framework. However, it primarily relies on predefined rules for analysis.

• Customization of engagement level: CyberTrap offers configurable decoy features, including basic port listening, simulated databases, and auto-generated file systems, though the generated data relies on templates that may be identifiable as artificial.

Challenges
CyberTrap has room for improvement in the following decision criteria:

• Cloud-native deception: CyberTrap lacks the ability to integrate with native cloud services or leverage provider-specific features. The solution’s basic cloud operation fails to meet modern enterprise requirements for cloud-native functionality and deep cloud service integration.

• Cross-platform support: CyberTrap has limited platform coverage development. While the solution provides basic Windows and Linux system emulation, the lack of advancement in this area has resulted in capabilities that have fallen behind market expectations and competitor offerings.

• Dynamic content generation: CyberTrap relies on template-based data generation for decoys. The templated approach to file systems and databases may produce detectable patterns that sophisticated attackers could identify as artificial, potentially compromising the effectiveness of the deception environment.

Purchase Considerations
The solution employs an endpoint-based pricing model that scales with volume discounts, providing transparency in the cost structure. The base price includes the orchestration platform and decoy systems, helping avoid unexpected costs during implementation.

From a deployment perspective, CyberTrap operates across both physical and cloud environments through a centralized management console. However, cloud deployment options are currently limited to AWS environments, which may impact organizations requiring multicloud support.

The solution demonstrates flexibility in decoy configuration, allowing customization of operating systems, applications, and interaction levels. While it includes basic OT/IoT system emulation capabilities, these features are limited to common protocols, which may affect organizations with specialized operational technology requirements.

An uncluttered interface with straightforward navigation to essential information enhances the user experience. The solution utilizes templates and automation for decoy management, simplifying operational tasks through the central console. Integration capabilities focus primarily on SIEM systems, providing standard monitoring and reporting functions through dashboard interfaces.

Use Cases
Defense research organizations benefit from CyberTrap’s high-interaction decoy capabilities that allow deep analysis of attacker behaviors. The solution’s ability to maintain detailed interaction logs while isolating malicious activity makes it particularly effective for organizations conducting in-depth threat research and analysis.

Manufacturing environments leverage CyberTrap’s basic OT/IoT system emulation features to protect industrial networks. The solution deploys convincing decoys that mirror common industrial protocols while maintaining separation between IT and OT environments, providing early warning of threats targeting production systems.

Traditional enterprise environments utilize CyberTrap’s Windows and Linux decoy deployments to detect lateral movement attempts. The solution’s automated template-based deployment across network segments helps security teams maintain coverage while minimizing administrative overhead in standard corporate environments.

Deceptive Bytes: Active Endpoints Deception

Solution Overview
Deceptive Bytes develops endpoint deception technology, focusing specifically on endpoint protection through deception-based prevention mechanisms. The company specializes in delivering lightweight deception capabilities that integrate with existing endpoint security infrastructure.

The Deceptive Bytes Active Endpoint Deception solution functions as a standalone endpoint security product. The solution deploys deceptive elements directly on endpoints to detect and prevent malicious activities. Their product includes components for endpoint deception deployment, threat detection, and response management through a centralized console.

Deceptive Bytes implements a focused approach to endpoint deception, emphasizing simplicity and efficient deployment. Their solution strategy centers on providing reliable endpoint protection through deceptive mechanisms, with particular attention to minimizing system resource usage and maintaining operational stability.

As a mature solution provider, Deceptive Bytes’ offering maintains consistent functionality throughout the contract lifecycle. The vendor prioritizes stability and operational reliability, making incremental improvements to existing capabilities in areas such as deployment efficiency and detection accuracy. Their development approach focuses on the structured advancement of core endpoint deception features, ensuring compatibility with existing security tools and maintaining a predictable user experience.

Deceptive Bytes is positioned as a Challenger and Forward Mover in the Maturity/Feature Play quadrant of the deception technology Radar report.

Strengths
Deceptive Bytes scored well on a number of decision criteria, including:

• Cross-platform support: Deceptive Bytes offers management server compatibility with Windows Server 2019-2025 and Ubuntu 24.04 and 22.04 LTS, along with deception agents that support common Windows and Linux versions to create fake environments aimed at malware prevention.

• Behavioral analysis: Deceptive Bytes can log attack behaviors, evasion techniques, and system interactions, with the functionality to map these activities to indicators of compromise (IoCs). Enhancements year over year include expanded support for evasion techniques, ransomware prevention, DLL hijacking prevention, and more.

• Multilayer deception: Deceptive Bytes has a specialized focus on endpoint-based deception, though this comes with the limitation of excluding cloud, network, and identity deception capabilities.

Challenges
Deceptive Bytes has room for improvement in the following decision criteria:

• Cloud-native deception: Deceptive Bytes has significant limitations in cloud service support. The solution’s capability is restricted to basic VM deployment in cloud environments, and it lacks integration with essential cloud-native services such as serverless functions, storage services, and identity management features.

• Customization of engagement level: Deceptive Bytes takes a rigid approach to threat engagement. The solution offers only preset evasion techniques without the ability to customize engagement methods or environmental configurations, limiting its effectiveness in adapting to specific security needs and threat scenarios.

• OT/IoT-specific decoys: Deceptive Bytes lacks purpose-built OT deception capabilities. While the solution can function on devices running Windows or Linux operating systems, it lacks specific OT protocol support and industrial control system emulation features necessary for effective OT environment protection.

Deceptive Bytes was classified as a Forward Mover given its relatively slow development rate in the last 6 to 12 months. This is particularly evident in its basic feature set and limited customization capabilities. The lack of advancement in cloud-native services and OT-specific functionality suggests that the vendor may continue to fall behind market leaders in key areas of deception technology.

Purchase Considerations
The solution demonstrates cost efficiency through reduced operational requirements, as it operates with minimal monitoring needs. This approach helps minimize the personnel resources required for attack handling and mitigation, contributing to a lower total cost of ownership. It is also one of the few solutions with a built-in LLM assistant.

Deceptive Bytes functions primarily as a focused Feature Play, specifically targeting endpoint protection scenarios. While this specialization allows for deep endpoint coverage, it also means the solution has limited application beyond endpoint use cases.

The management interface provides an intuitive operational experience, enabling quick configuration and efficient handling of prevention notifications. This ease of use helps reduce the learning curve for new operators and streamlines daily management tasks.

The solution maintains broad integration capabilities with common enterprise tools, including email systems, SIEM solutions, directory services, cloud storage, threat intelligence platforms, and ticketing systems. While deployment is straightforward, scalability considerations should account for the requirement to install software on each Windows or Linux endpoint individually.

Use Cases
Endpoint protection is the primary use case for Deceptive Bytes, which deploys deception directly on Windows and Linux endpoints to detect and prevent malicious activities. The solution’s ability to operate without constant monitoring while maintaining effective protection makes it particularly valuable for organizations seeking to enhance endpoint security with minimal operational overhead.

Ransomware defense offers another key scenario where the solution’s endpoint-focused deception capabilities help identify and prevent ransomware activities before they can cause significant damage. The solution’s integration with enterprise security tools enables quick response to detected threats.

Zero-day attack detection leverages the solution’s endpoint deception capabilities to identify previously unknown threats targeting workstations and servers. The solution’s ability to operate independently on endpoints while maintaining connectivity with broader security infrastructure helps organizations detect sophisticated attacks that might evade traditional security controls.

Fortinet: FortiDeceptor

Solution Overview
Fortinet’s FortiDeceptor, its enterprise deception technology offering, integrates with the broader Fortinet Security Fabric ecosystem. The solution extends Fortinet’s established security architecture to deliver deception capabilities that align with its existing portfolio of network security solutions.

FortiDeceptor functions as both a standalone solution and an integrated component of the Fortinet Security Fabric. The offering includes the FortiDeceptor management console, deception sensors, and integration modules. Core deployment options include virtual and hardware-based appliances designed to support enterprise-scale deception operations.

The solution implements a systematic approach to deception technology, emphasizing operational efficiency and integration with existing Fortinet deployments. The vendor’s strategy focuses on delivering reliable deception capabilities while maintaining compatibility with the Security Fabric architecture.

As a Fast Mover in the Maturity hemisphere of the Radar, FortiDeceptor demonstrates structured advancement while maintaining stability. The vendor prioritizes incremental improvements to existing capabilities, focusing on areas such as automation, integration options, and threat detection accuracy. Its development approach emphasizes methodical progression and assured compatibility, ensuring the solution maintains consistent functionality throughout the contract lifecycle. Recent updates have concentrated on strengthening Security Fabric integration and expanding automated response capabilities.

Fortinet is positioned as a Leader and Fast Mover in the Maturity/Platform Play quadrant of the deception technology Radar report.

Strengths
Fortinet scored well on a number of decision criteria, including:

• OT/IoT-specific decoys: FortiDeceptor has the ability to emulate industrial devices across Purdue Model zones, supporting common OT protocols and vendors while incorporating intrusion prevention system (IPS) engine capabilities for OT/IoT threat detection and asset discovery.

• Cross-platform support: Fortinet has comprehensive IT/OT/IoT decoy deployment capabilities across cloud platforms and air-gapped networks, including support for common protocols and services, MITRE industrial control system (ICS) mapping, and custom image support.

• Behavioral analysis: Fortinet takes an integrated approach to analyzing captured malware and network traffic using sandbox analysis, IPS, web filtering, and ML, though primarily leveraging existing Fortinet security tools rather than deception-specific analysis capabilities.

Challenges
Fortinet has room for improvement in the following decision criteria:

• Cloud-native deception: Fortinet has significant gaps in cloud-native service integration. While FortiDeceptor operates on major cloud platforms, it lacks essential capabilities for modern cloud environments, including support for serverless functions, storage services, networking features, and IAM integration.

• Multilayer deception: Fortinet has limitations in network traffic simulation authenticity. The solution’s generated traffic patterns follow fixed intervals that sophisticated attackers may identify as artificial, potentially compromising the effectiveness of the deception environment.

• Identity-focused deception: Fortinet depends on external SIEM integration for lateral movement detection. This reliance on third-party solutions for critical functionality may impact response times and create potential gaps in threat detection coverage.

Purchase Considerations
The solution utilizes a subscription-based pricing model that scales with the number of network VLANs under protection. Cost transparency is maintained through the inclusion of FortiDeceptor decoys and deception tokens within the base product license, avoiding hidden fees or additional charges.

The deployment approach demonstrates clear scalability parameters, particularly in cloud and customer-managed environments. The solution provides straightforward scaling calculations based on hardware or VLAN limits, making capacity planning more predictable.

Implementation is streamlined through wizard-based deployment processes, requiring minimal steps to establish decoys and generate deception campaigns. The incident alert visualization system enables efficient analysis across all skill levels, with automated risk scoring to aid in response prioritization.

The solution maintains broad integration capabilities with standard enterprise security tools through API and syslog connections, including identity management, EDR platforms, SIEM systems, firewalls, network access control (NAC) solutions, and sandbox environments. The “bring your own” model for assets extends deployment flexibility across environments that may not be directly supported by Fortinet’s native offerings.

Use Cases
Industrial control system protection represents a primary use case where Fortinet deploys deception across OT networks using its “bring your own” asset model. The solution’s ability to integrate with existing OT infrastructure while maintaining separation between IT and OT environments helps organizations detect threats targeting industrial systems without disrupting operations.

Enterprise network defense is another key scenario where the solution leverages wizard-based deployment to establish comprehensive deception across VLANs. The tight integration with NAC solutions, firewalls, and EDR platforms enables automated response to detected threats while maintaining visibility across the environment.

Retail environments benefit from Fortinet’s ability to deploy standardized deception across multiple locations using simple scaling calculations. The solution’s automated risk scoring and incident visualization features help distributed security teams quickly identify and respond to threats targeting point-of-sale and customer-facing systems.

Labyrinth: Deception Platform

Solution Overview
Labyrinth specializes in cyber deception solutions, focusing on leveraging advanced automation and high-fidelity emulations of IT services. The company concentrates on delivering innovative deception capabilities that adapt to evolving threat landscapes.

The Labyrinth Deception Platform is a standalone product designed for automated threat detection and response. It employs high-interaction deception mechanisms to create and manage dynamic decoy environments. Core components include the deception orchestration engine, automated deployment tools, and an analytics dashboard.

Labyrinth implements an agile approach to deception technology, emphasizing rapid adaptation and innovative response capabilities. An example of this, introduced this year, is the SEEKER module, an attack vector validation tool that provides real-time validation of deception deployment. Labryinth’s strategy focuses on delivering cutting-edge deception techniques while maintaining flexibility in deployment and operation.

As an innovative solution provider, Labyrinth’s offering will undergo significant evolution over the contract lifecycle. The vendor prioritizes rapid advancement and frequent updates, focusing on developing new capabilities and features to address emerging threats. Its development approach emphasizes quick adaptation and innovative solutions, which may result in more frequent changes to the user experience.

Labyrinth is positioned as a Challenger and Fast Mover in the Innovation/Feature Play quadrant of the deception technology Radar report.

Strengths
Labyrinth scored well on a number of decision criteria, including:

• OT/IoT-specific decoys: Labyrinth offers comprehensive OT device emulation capabilities, including Allen-Bradley components, MQTT broker, Siemens equipment, and Universal Web Point interface for machine GUI emulation.

• Customization of engagement level: Labyrinth provides competitive customization features that allow deception assets to be tuned to specific customer scenarios, including the ability to create universal HTTP endpoints with customizable personally identifiable information (PII), HTTP headers, and session cookies.

Challenges
Labyrinth has room for improvement in the following decision criteria:

• Cross-platform support: Labyrinth has limited platform coverage. While the solution supports traditional virtualization platforms and Azure, it lacks integration with major cloud providers like AWS, potentially limiting its effectiveness in multicloud environments.

• Behavioral analysis: Labyrinth offers only basic telemetry collection; however, it is able to map events to an attacker framework (MITRE ATT&CK). Although the solution gathers various data points about attacker interactions, the absence of statistical analysis and ML implementations restricts its ability to identify sophisticated attack patterns and predict threat behaviors.

• Multilayer deception: Although Labyrinth focuses on network-layer deception, the SEEDER agent can be used on Linux and Windows to leave breadcrumbs behind. While the solution provides comprehensive network-based deception techniques, this emphasis comes at the expense of cloud and identity, limiting its effectiveness in modern hybrid environments.

Purchase Considerations
The solution employs a transparent pricing structure based on decoy points, with tiered packages offering volume discounts. Both subscription and perpetual licensing options are available, providing flexibility in procurement approaches. The solution operates independently without requiring third-party licensing, contributing to a predictable total cost of ownership.

Labyrinth’s network-centric approach to deception enables efficient resource utilization and straightforward management. However, the solution’s deployment options are primarily focused on traditional network environments, which may present limitations for organizations with predominantly cloud-based or distributed infrastructures.

The user experience emphasizes simplicity and intuition and is designed to minimize the need for specialized expertise. Within its supported deployment scenarios, the solution delivers straightforward implementation and operation, making it accessible for teams with varying levels of technical proficiency.

Integration capabilities include standard notification channels through email and collaboration platforms, along with specific integrations for select EDR solutions and firewall systems. SIEM and SOAR connectivity is enabled through syslog forwarding with bidirectional communication capabilities. Additionally, the REST API that is available allows customers to build custom integrations.

Use Cases
Traditional enterprise network protection represents a primary use case where Labyrinth decoys and traps incorporate active feature sets to create more authentic environments. The solution’s lightweight deployment model and focus on network layer deception make it particularly effective for organizations seeking to identify threats moving within their internal network segments without impacting existing infrastructure.

Industrial control environments benefit from Labyrinth’s ability to deploy deception across network segments without requiring endpoint agents or system modifications. The solution’s simplified deployment model helps maintain operational technology network integrity while providing early warning of threats targeting industrial systems.

Branch office security presents another key scenario where the solution’s efficient resource utilization and straightforward management enable consistent deception coverage across distributed locations. The solution’s network-centric approach allows organizations to maintain effective threat detection at remote sites without requiring significant local infrastructure or expertise.

Lupovis: Snare and Prowl

Solution Overview
Lupovis delivers cyber deception technology with an emphasis on automated threat engagement and advanced analytics. The company focuses on providing enterprise-grade deception capabilities that create interactive environments for threat detection and analysis.

The Lupovis deception solution functions as a comprehensive deception offering, incorporating multiple components for threat detection and response. The solution includes modules for deception deployment, threat engagement, and intelligence gathering through a centralized management interface. Core components encompass the Deception Engine, Engagement Analytics, and Response Automation tools.

Lupovis presents two solutions: The Snare deception-as-a-service offering and the Prowl Internet scanning and analysis service. The company implements a systematic approach to deception technology, emphasizing operational efficiency and reliable threat detection. Its strategy focuses on delivering consistent deception capabilities while maintaining compatibility with existing security infrastructure. The solution particularly emphasizes automated threat engagement and detailed adversary tracking.

As a mature solution provider and Fast Mover, Lupovis demonstrates structured advancement while maintaining stability. The vendor prioritizes both innovation and reliability, making significant improvements to existing capabilities while ensuring operational consistency. Its development approach focuses on the methodical progression of core features, particularly in areas such as automation, threat engagement mechanics, and analysis capabilities.

Lupovis is positioned as a Leader and Fast Mover in the Maturity/Platform Play quadrant of the deception technology Radar report.

Strengths
Lupovis scored well on a number of decision criteria, including:

• Behavioral analysis: Lupovis offers advanced behavioral analysis capabilities that were developed in partnership with the University of Strathclyde. These capabilities provide a thorough understanding of adversary actions and strategies that can be translated into actionable intelligence.

• Customization of engagement level: Lupovis provides a narrative feature that enables customers to create multiple coordinated enticement points for adversaries. The customizable narrative capabilities work in concert across multiple decoys.

• OT/IoT-specific decoys: Lupovis offers a comprehensive range of decoys covering various aspects of digital infrastructure, including IT, OT, and IoT systems. While this approach provides a solid foundation for deception-based threat detection, organizations with highly specialized or proprietary OT/IoT environments may find these decoys less effective at accurately mimicking their specific systems.

Challenges
Lupovis has room for improvement in the following decision criteria:

• Cloud-native deception: While Lupovis scored quite well in cloud-native deception because of its comprehensive coverage of decoys in AWS and Azure, it falls short of a higher score for two reasons. First, it lacks coverage for Google Cloud Platform decoys, which is a popular cloud computing platform among enterprises. Second, it lacks container- and orchestration-based decoys, which can provide early warning mechanisms in Kubernetes-dominant cloud environments.

• Cross-platform support: Lupovis provides standard deployment capabilities. Although the solution supports multiple environments, including IoT devices and bare metal servers, it may lack the depth of customization and advanced features needed for complex, heterogeneous infrastructures.

• Multilayer deception: Lupovis’ deception system is designed to deploy a variety of representative systems across the network and create customized, convincing, dynamic decoys that reflect the actual environment. While this addresses common use cases in the enterprise, the solution’s multilayer capabilities may fall short for organizations with highly specialized use cases in the OT domain (with legacy systems and OT protocols).

Purchase Considerations
The solution employs a usage-based pricing model that scales according to deployment size and Prowl request volume. This approach provides some flexibility in cost structure, though accurately forecasting expenses may require careful consideration of expected usage patterns.

Lupovis demonstrates strong technical scalability, with no limitations on decoy deployment while maintaining consistent performance. The solution’s Snare component offers sector-agnostic functionality, enabling adaptation across various industries and use cases. It can also create linked decoy narratives that enhance deception strategies.

The user experience accommodates different operational preferences through both a graphical interface and SIEM integration options, allowing security teams to work within their preferred environment. This dual-mode approach helps streamline adoption across teams with varying technical backgrounds.

Use Cases
Critical infrastructure defense is a key use case for Lupovis’s Snare component, which deploys sector-specific deception scenarios. The solution’s ability to create linked narratives between decoys helps establish convincing environments that attract and track adversaries targeting industrial systems.

Advanced threat detection highlights another scenario where the solution’s Prowl monitoring capabilities track attacker behavior across networked environments. The ability to construct interconnected deception scenarios enables security teams to observe and analyze sophisticated attack patterns while maintaining operational security.

Lupovis can create customized deception scenarios that mirror specific technical environments, benefiting research and development environments. The solution’s flexible deployment model allows security teams to establish targeted deception environments that help protect intellectual property while gathering detailed threat intelligence.

Proofpoint: Identity Threat Defense*

Solution Overview
Proofpoint provides comprehensive cybersecurity solutions with a focus on email and data security, threat protection, and compliance. Its portfolio extends into deception technology through integration with its broader security ecosystem.

The Proofpoint Identity Threat Defense solution incorporates several security features, including deception capabilities. The solution also includes email protection, threat response, and automated defense mechanisms. Core components encompass Email Fraud Defense, Targeted Attack Protection, and Threat Response Auto-Pull, which work together to provide comprehensive threat detection and response.

Proofpoint implements a structured approach to deception technology, emphasizing reliability and integration across its product portfolio. Its strategy focuses on delivering consistent protection while maintaining compatibility with existing security infrastructure.

As a mature solution provider in the Challenger ring, Proofpoint demonstrates methodical advancement while maintaining stability. The vendor prioritizes reliability and operational consistency, making incremental improvements to existing capabilities in areas such as threat detection accuracy, automation, and compliance. Its development approach focuses on the structured progression of core features, ensuring compatibility and maintaining a predictable user experience.

Proofpoint is positioned as a Challenger and Forward Mover in the Maturity/Platform Play quadrant of the deception technology Radar report.

Strengths
Proofpoint scored well on a number of decision criteria, including:

• Behavioral analysis: Proofpoint features comprehensive detection capabilities, including over 75 types of deceptions and the ability to detect and alert on high-risk Active Directory administrative tasks, with all detections mapped to the MITRE ATT&CK framework.

• Multilayer deception: Proofpoint offers flexible endpoint deception capabilities that can be customized based on factors such as endpoint type (server or client), operating system, and existing applications and files on the machine.

• OT/IoT-specific decoys: Proofpoint includes both decoys and emulations designed to mimic OT/IoT platforms, though specific protocol support details were not provided.

Challenges
Proofpoint has room for improvement in the following decision criteria:

• Cloud-native deception: Proofpoint has significant gaps in cloud service coverage. While the solution integrates with Microsoft 365, Okta, and AWS for identity-based detection, it lacks essential cloud-native service support, including serverless functions and storage objects, limiting its effectiveness in modern cloud environments.

• Cross-platform support: Proofpoint offers only basic platform coverage. Although the solution supports major operating systems and some cloud services, it may not provide the depth of integration and advanced features required for complex, hybrid environments.

• Customization of engagement level: Proofpoint takes a standard approach to deception customization. While the solution offers basic control over technique families and engagement levels, it may not provide the granular configuration options needed for sophisticated threat detection scenarios.

Proofpoint was classified as a Forward Mover given its relatively slow pace of development in the last 6 to 12 months, particularly evident in its limited cloud-native capabilities and basic platform support. The lack of advancement in these areas suggests the vendor may continue to fall behind market leaders in providing comprehensive deception technology solutions.

Purchase Considerations
The solution features a cost-efficient deployment model with minimal ongoing maintenance requirements. Initial implementation can be completed within weeks, and standard integrations for privileged access management (PAM), Active Directory, IT service management (ITSM), SIEM, and extended detection and response (XDR) capabilities are included in the base cost.

Proofpoint demonstrates proven scalability across both large and small deployments, supporting environments with up to half a million decoys and tokens. The solution maintains consistent performance across both SaaS and on-premises implementations, providing deployment flexibility based on organizational requirements.

The user interface is optimized for security operations center (SOC) operations. It combines deception management and incident triage within a unified console. Automated collection and presentation of forensic evidence streamlines the analysis process for security teams.

The solution’s detection-based deception approach requires minimal environmental tuning, enhancing operational efficiency. Integration capabilities span core identity management systems, including Active Directory, Entra ID, AWS Identity Center, and Okta, with support for existing EDR and multifactor authentication (MFA) solutions. The solution operates effectively alongside PAM tools and across Microsoft 365 environments.

Use Cases
Identity protection is a primary use case for the solution, which deploys deception across hosts such as clients and servers, as well as Active Directory, Entra ID, and AWS Identity Center environments. The solution’s automated detection capabilities help security teams identify credential theft and privilege escalation attempts without requiring extensive tuning or maintenance.

Large-scale enterprise deployments highlight another scenario in which Proofpoint’s solution can effectively manage environments with hundreds of thousands of decoys and tokens. The detection-based approach minimizes environmental tuning requirements while maintaining consistent performance across SaaS and on-premises implementations.

SOC operations benefit from the solution’s integrated approach to deception management and incident triage. The automated collection and presentation of forensic evidence, combined with seamless EDR and MFA integration, enables efficient threat detection and response workflows while reducing analytical overhead.

RevBits: Deception Technology*

Solution Overview
RevBits Deception Technology is part of the company’s broader cybersecurity portfolio and provides a focused approach to endpoint protection and threat detection capabilities. The company specializes in providing deception mechanisms that complement existing security infrastructure.

The RevBits solution incorporates endpoint-focused deception capabilities through a centralized management interface. Core components include deception deployment tools, threat monitoring features, and basic response automation functionality.

RevBits implements a targeted approach to deception technology, emphasizing straightforward deployment and basic threat detection capabilities. Its strategy focuses on delivering fundamental deception features while maintaining simplicity in operation and management. The solution particularly emphasizes endpoint protection through deceptive mechanisms.

Residing in the Challenger ring of the Maturity hemisphere in the GigaOm Radar chart, RevBits demonstrates methodical advancement while maintaining stability. The vendor prioritizes reliability and operational consistency, making incremental improvements to existing capabilities in areas such as deployment efficiency and detection accuracy. The vendor’s development approach focuses on the structured progression of core features, ensuring compatibility and maintaining a predictable user experience.

RevBits is positioned as a Challenger and Fast Mover in the Maturity/Feature Play quadrant of the deception technology Radar report.

Strengths
RevBits scored well on a number of decision criteria, including:

• Cross-platform support: RevBits offers versatile deployment capabilities across public cloud, private cloud, and on-premises environments, though offering standard platform compatibility without specialized features for specific platforms.

• Behavioral analysis: RevBits can monitor system calls, processes, and file activity, incorporating sandbox analysis and MITRE ATT&CK mapping for threat classification.

• Multilayer deception: RevBits makes use of real operating systems, which provide multiple layers of deception from OS to application to user level. However, the solution lacks network, identity, and cloud-layer deception capabilities.

Challenges
RevBits has room for improvement in the following decision criteria:

• Cloud-native deception: RevBits has a limited cloud integration approach. While the solution can deploy basic virtual honeypots across major cloud providers, it relies primarily on prebuilt images and lacks deeper integration with cloud-native services, potentially limiting its effectiveness in modern cloud-first environments.

• Customization of engagement level: RevBits takes a rudimentary approach to engagement configuration. The solution’s reliance on decoy quantity as the primary means of controlling engagement levels lacks the sophistication needed for targeted threat detection and analysis scenarios.

• OT/IoT-specific decoys: RevBits has only basic OT/IoT protocol support that may not meet industrial environment requirements. While the solution includes basic Modbus and SNMP protocol emulation, the limited depth of industrial protocol support and basic emulation capabilities make it inadequate for complex OT environments.

Purchase Considerations
The solution operates as part of a broader security suite that includes multiple modules, such as email security, endpoint protection, PAM, and zero-trust networking. While the solution allows for unlimited decoy deployment and includes support services, the lack of transparent pricing information may complicate procurement planning.

RevBits utilizes full operating system deployments for decoys, which can be implemented through one-click deployment processes. However, this approach may present inherent limitations in scalability and flexibility compared to projection-based deception methods, particularly in cloud environments where direct integrations are limited.

The user interface is a core strength of the solution. It features an intuitive design that simplifies operational management. The solution can be deployed on-premises or as a SaaS offering. It has basic SIEM integration capabilities to support security operations workflows.

The solution’s architecture may require additional consideration for organizations seeking highly scalable or cloud-native implementations, as the full OS approach to deception could impact deployment agility and resource requirements.

Use Cases
Traditional enterprise network monitoring represents a primary use case where RevBits deploys full operating system decoys to detect lateral movement and network reconnaissance. The one-click deployment model helps security teams establish believable deception assets that can identify threats moving within corporate networks.

Security operations centers benefit from RevBits’ integrated approach to deception management and incident response. The solution’s intuitive interface enables efficient threat detection and investigation workflows while maintaining visibility across deployed decoys.

Hybrid infrastructure protection highlights another scenario where RevBits can deploy deception across both on-premises and SaaS environments. The solution’s ability to maintain consistent decoy deployment across varied infrastructure helps organizations detect threats targeting different segments of their environment, though cloud-native capabilities are currently limited.

Seedata.io

Solution Overview
Seedata.io delivers deception technology, focusing on network security and threat detection. The company specializes in providing targeted deception capabilities that complement existing security infrastructure while maintaining operational simplicity.

The Seedata.io deception solution is a standalone product designed for specific use cases within enterprise environments. Its core components include deception deployment tools, threat monitoring capabilities, and basic response automation features, all managed through a centralized interface.

Seedata.io implements a targeted approach to deception technology, emphasizing straightforward deployment and reliable threat detection. Its strategy focuses on delivering fundamental deception capabilities while maintaining operational stability. The solution particularly emphasizes network protection through the strategic placement of deception assets.

As a mature solution provider in the Challenger ring, Seedata.io demonstrates methodical advancement while maintaining consistency. The vendor prioritizes reliability and operational stability, making incremental improvements to existing capabilities in areas such as deployment efficiency and detection accuracy. Its development approach focuses on the structured progression of core features, ensuring compatibility and maintaining a predictable user experience.

Seedata.io is positioned as a Challenger and Forward Mover in the Maturity/Feature Play quadrant of the deception technology Radar report.

Strengths
Seedata.io scored well on a number of decision criteria, including:

• Cloud-native deception: Seedata.io’s current AWS integration supports several use cases, including EC2, Dynamo DB tables, SSM parameters, and IAM credential decoys. More AWS use cases are planned and will be delivered in the next quarter of 2025.

• Behavioral analysis: Seedata.io provides event monitoring capabilities that track network interactions with decoys and planted data online, incorporating a priority rating system (P1-P5) based on actor behavior, customer-defined impact levels, and event types.

• Customization of engagement level: Seedata.io features configurable decoy interaction levels and deployment methods, offering both automated and manual options with strategic placement guidance based on objectives.

Challenges
Seedata.io has room for improvement in the following decision criteria:

• Cross-platform support: Seedata.io has limited platform coverage. While the solution supports Linux-based decoys across cloud and on-premises environments, the lack of comprehensive Windows support and restricted decoy types limits its effectiveness in heterogeneous environments.

• OT/IoT-specific decoys: Seedata.io supports only a narrow range of OT devices. The solution’s reliance on a single PLC model and vendor-dependent custom profile development may not meet the immediate needs of diverse industrial environments that require multiple device types and protocols.

• Identity-focused deception: Seedata.io supports only a basic AWS-centric identity deception approach. The solution’s limited focus on AWS services and pending development of key identity deception features suggest gaps in comprehensive identity protection across multicloud environments.

Seedata.io was classified as a Forward Mover given its relatively slow pace of development in the last 6 to 12 months, particularly evident in its basic platform support and limited OT capabilities. The dependency on vendor intervention for custom device profiles and pending feature releases indicates potential delays in meeting evolving market requirements, suggesting the vendor may continue to lag behind market leaders in providing comprehensive deception technology solutions.

Purchase Considerations
The solution features an accessible pricing structure with a trial period, allowing organizations to validate use cases before committing to a purchase. This approach helps reduce initial investment risk and enables proper evaluation of the solution’s fit within existing security operations.

While the solution has theoretical scalability potential, practical limitations exist due to the requirement for VM deployment and portal connectivity. This architecture may introduce operational friction during scaling activities, particularly in larger environments.

The user interface provides standard functionality typical of deception solutions, meeting basic operational requirements while leaving room for improvement. The solution continues to evolve, with new features being added based on customer feedback, indicating ongoing development but potential gaps in current capabilities.

Integration capabilities are primarily focused on basic SIEM and SOAR connectivity, with deployment options across cloud and on-premises environments. The solution’s ecosystem is currently limited, with partnerships primarily concentrated in specific geographic regions and the AWS Marketplace, which may impact organizations requiring broader integration support.

Use Cases
Software development environments are a primary use case for the solution, which monitors API endpoints and cloud services for unauthorized access attempts. The solution’s automated deployment capabilities help security teams maintain consistent coverage across development infrastructure while detecting potential threats to build processes and code repositories.

Cloud infrastructure protection highlights another scenario where Seedata.io deploys deception across multicloud environments. The solution’s ability to adapt to environmental changes through infrastructure as code (IaC) templates helps organizations maintain effective deception coverage as their cloud footprint evolves.

DevSecOps operations benefit from the solution’s ability to integrate security testing into development workflows. The solution’s automated discovery and deployment features help security teams maintain visibility across development environments while minimizing operational overhead, though its effectiveness depends on template coverage and update frequency.

Thinkst Applied Research: Canary

Solution Overview
Thinkst Applied Research delivers deception technology with an emphasis on simplicity and reliability in threat detection. The company maintains a focused approach to deception through its Canary solution, which has established a significant presence in the market.

The Canary solution functions as a comprehensive deception offering that includes both hardware and software components. The product suite consists of physical and virtual Canaries for deployment across environments, the Canary Console for centralized management, and Canary Tokens for distributed threat detection. These components work together to provide broad coverage while maintaining operational simplicity.

Thinkst implements a systematic approach to deception technology, emphasizing operational efficiency and reliable threat detection. Its strategy focuses on delivering consistent, dependable deception capabilities while maintaining simplicity in deployment and management. The solution particularly emphasizes quick deployment and reliable alerting mechanisms.

As a mature solution provider, Thinkst demonstrates methodical advancement while maintaining stability. The vendor prioritizes reliability and operational consistency, making incremental improvements to existing capabilities in areas such as detection accuracy, deployment efficiency, and alert fidelity. Its development approach focuses on the structured progression of core features, ensuring compatibility and maintaining a predictable user experience.

Thinkst Applied Research is positioned as a Leader and Fast Mover in the Maturity/Platform Play quadrant of the deception technology Radar report.

Strengths
Thinkst Canary scored well on a number of decision criteria, including:

• Cloud-native deception: Thinkst Canary offers automated template-based deployment of cloud decoys across AWS, Azure, and Google Cloud, featuring one-time setup and centralized management of tokens and “birds.”

• Cross-platform support: The solution provides kernel-level emulation of common enterprise systems, including Windows servers and desktops, Linux distributions, network devices, and enterprise applications, though with potential limitations in fully replicating actual system behaviors.

• Multilayer deception: Thinkst Canary provides comprehensive emulation of network devices, servers, and storage systems across multiple network layers, with capabilities for detecting port scans and reconnaissance activity through basic protocol simulation.

Challenges
Thinkst Canary has room for improvement in the following decision criteria:

• Behavioral analysis: Thinkst Canary focuses on immediate alert generation rather than comprehensive threat analysis. While the solution excels at real-time detection, the lack of advanced behavioral analysis capabilities, including MITRE ATT&CK mapping and kill chain correlation, limits its ability to provide deeper threat intelligence insights.

• Customization of engagement level: The solution has limited engagement configuration options. Although the solution allows for service customization within enterprise environments, the absence of dynamic or static engagement profiles restricts the ability of security teams to control and adapt threat actor interactions based on specific scenarios.

• OT/IoT-specific decoys: Thinkst Canary offers basic industrial protocol support. While the solution provides emulation for three PLC models with Modbus service, organizations with diverse industrial environments may find the limited protocol coverage and reliance on custom TCP service configuration insufficient for comprehensive OT security needs.

Purchase Considerations
The solution features transparent pricing with a straightforward annual cost structure: $3,000 for the management console plus $1,000 per decoy device annually. Volume discounts begin at 20 devices, and tokens are included at no additional cost. Notably, Thinkst Canary offers a portion of its product free indefinitely, distinguishing it from typical limited-capability trial offerings.

The licensing model provides flexibility in device deployment, allowing conversion between hardware, VM, cloud, and container formats. This adaptability starts with small-scale implementations of 5-10 devices with the ability to expand based on organizational needs.

The user experience emphasizes operational simplicity through an intuitive interface and streamlined feature set. Management of larger deployments is facilitated through grouping capabilities called “flocks,” which help organize and maintain decoy devices efficiently.

Integration capabilities focus on essential notification methods, including email, SMS, webhook, and syslog protocols. The solution supports team-based management structures and provides API automation options while maintaining preconfigured settings that minimize initial setup requirements. Customization options for tokens and honeypots enable adaptation to various use cases.

Use Cases
Network security monitoring is a primary use case for Thinkst’s straightforward deployment of Canary devices, which detect unauthorized access attempts. The solution’s simplified approach allows security teams to establish effective detection capabilities within minutes, requiring minimal configuration or ongoing maintenance.

Branch office protection highlights another scenario where Thinkst’s lightweight deployment model enables consistent security coverage across distributed locations. The solution’s intuitive “flocks” feature allows central teams to manage multiple sites efficiently without requiring local technical expertise.

Small-to-medium enterprise environments benefit from Thinkst’s uncomplicated approach to deception deployment. The solution’s focus on essential detection capabilities, combined with straightforward token distribution and preconfigured settings, enables organizations to implement effective deception without dedicating significant resources to management or tuning.

Tracebit

Solution Overview
Tracebit delivers specialized deception technology, emphasizing innovative threat detection and automated response capabilities. The company focuses on providing advanced deception mechanisms that adapt dynamically to emerging threats.

The Tracebit deception solution is a standalone product designed for specific use cases within enterprise environments. It leverages AI-driven deployment and management of deceptive assets through a centralized console. Core components include automated deception deployment tools, threat detection mechanisms, and response automation features.

Tracebit implements an aggressive approach to deception technology, emphasizing rapid advancement and innovative capabilities. Its strategy focuses on delivering cutting-edge deception techniques while maintaining flexibility in deployment options. The solution particularly emphasizes autonomous operation and adaptive response mechanisms.

As an innovative solution provider and Fast Mover in the Challenger ring, Tracebit demonstrates rapid advancement and frequent updates. The vendor prioritizes cutting-edge development, focusing on emerging technologies and new feature releases that may result in significant changes over the contract lifecycle. Its development approach emphasizes quick adaptation to new threats and innovative response mechanisms.

Tracebit is positioned as a Challenger and Fast Mover in the Innovation/Feature Play quadrant of the deception technology Radar report.

Strengths
Tracebit scored well on a number of decision criteria, including:

• Cloud-native deception: Tracebit offers comprehensive cloud deployment capabilities in AWS and Azure, featuring Okta integration for identity-based deception. It supports full lifecycle management of deployed deceptions, including recommendations for deployment, refresh, and deletion through a streamlined interface.

• Cross-platform support: Tracebit focuses on major cloud providers and identity-focused detection capabilities for Windows, Mac, and Linux operating systems, though it lacks network telemetry collection capabilities.

• Multilayer deception: Tracebit can deploy decoys across cloud environments, identity systems, development pipelines, and workstations, though with limited endpoint and mobile device coverage restricted to identity-based deception objects.

Challenges
Tracebit has room for improvement in the following decision criteria:

• Behavioral analysis: Tracebit offers only a basic approach to activity monitoring. The solution relies on standard log analysis of AWS CloudTrail and similar audit sources without implementing advanced behavioral analytics or unique detection capabilities, limiting its effectiveness in identifying sophisticated attack patterns.

• Customization of engagement level: Tracebit provides rudimentary decoy configuration options. The solution’s current focus on basic alert-driven decoys, with more advanced interaction features not planned until later in 2025, leaves organizations without the sophisticated engagement capabilities needed for effective threat detection and analysis.

• OT/IoT-specific decoys: Tracebit has significant limitations in OT/IoT support. While the solution can deploy credentials to supported operating systems in OT environments, the lack of protocol emulation and device-specific deception capabilities makes it inadequate for industrial environments requiring comprehensive OT security controls.

Purchase Considerations
The solution employs a resource-based pricing model that scales according to specific metrics, including cloud instances, functions, protected endpoints, build processes, and Okta user counts. This granular approach to pricing requires careful consideration of deployment scope to forecast costs accurately.

Tracebit focuses primarily on cloud-native deception technologies, utilizing IaC templates and read-only access for automated deployment. The solution’s autodiscovery capabilities simplify initial setup and ongoing management by suggesting deception assets based on environmental changes.

The user experience emphasizes automation and simplicity, with an interface that presents suggested deployments and modifications as the environment evolves. This approach reduces operational complexity, though the solution’s effectiveness depends on template coverage and update frequency.

Integration capabilities center on common cloud operations tools, including specific SIEM platforms, alerting systems, IaC solutions, and messaging platforms. While the solution excels in cloud environments, its limited endpoint coverage and network telemetry collection may impact organizations requiring broader deception coverage across traditional infrastructure.

Use Cases
Cloud infrastructure protection is a primary use case for Tracebit’s automated discovery and deployment capabilities, which monitor cloud environments for unauthorized access attempts. The solution’s ability to use read-only access for implementation while maintaining IaC templates enables security teams to maintain consistent coverage as cloud environments evolve.

Software development pipeline security is another scenario where Tracebit monitors build processes and code repositories for potential compromise. The solution’s integration with development tools and automated deployment features helps security teams maintain visibility across the development lifecycle.

Identity monitoring in cloud environments presents a third use case where the solution deploys identity-focused tokens to detect credential theft attempts. While the solution provides effective coverage for cloud-native scenarios, its capabilities are more limited for traditional infrastructure and endpoint protection needs.

Zscaler: Zscaler Deception*

Solution Overview
Zscaler delivers cloud-native security solutions with integrated deception capabilities as part of its Zero Trust Exchange architecture. The company maintains a comprehensive security portfolio that incorporates deception technology within its broader cloud security framework.

The Zscaler Zero Trust Exchange functions as an integrated security ecosystem that includes deception capabilities alongside core security services. The solution incorporates automated deployment of deceptive assets through their cloud infrastructure. Core components include Zscaler Internet Access (ZIA), Zscaler Private Access (ZPA), and Zscaler Digital Experience (ZDX), which work together to provide comprehensive security coverage.

Zscaler implements a structured approach to security technology, emphasizing cloud-native deployment and integration across its solution portfolio. The strategy focuses on delivering consistent protection while maintaining seamless integration with existing security infrastructure. The solution particularly emphasizes zero-trust principles and cloud-delivered security.

As a mature solution provider and Fast Mover in the Challenger ring, Zscaler demonstrates rapid advancement while maintaining stability. The vendor prioritizes both innovation and reliability, making significant improvements to existing capabilities while ensuring operational consistency.

Zscaler is positioned as a Challenger and Fast Mover in the Maturity/Platform Play quadrant of the deception technology Radar report.

Strengths
Zscaler scored well on a number of decision criteria, including:

• Behavioral analysis: Zscaler features advanced behavioral analysis capabilities that incorporate anomaly detection and ML-based profiling, offering behavioral analytics and threat scoring to prioritize response efforts against advanced threats.

• Cross-platform support: Zscaler offers comprehensive platform support across cloud, hybrid, and on-premises environments, enhanced by Zscaler’s expertise in secure remote access. This provides strong network coverage.

• Customization of engagement level: Zscaler supports flexible engagement options, which can be adjusted manually or dynamically based on threat intelligence, network activity, system vulnerabilities, and user behavior. These options enable tailored deception-based threat detection and response.

Challenges
Zscaler has room for improvement in the following decision criteria:

• Cloud-native deception: Zscaler has significant gaps in cloud-native service coverage. While the solution supports basic VM and identity deployment in cloud environments, it lacks essential capabilities for modern cloud architectures, including serverless functions, storage objects, and secrets management integration.

• OT/IoT-specific decoys: Zscaler takes a basic approach to industrial deception. Although the solution creates fake industrial devices, the depth of protocol support and device-specific behaviors may not meet the requirements of complex industrial environments requiring sophisticated OT security controls.

• Identity-focused deception: Zscaler has significant infrastructure dependencies for identity-focused deception. While the solution integrates well with Zscaler’s zero-trust platform, being tied to Zscaler’s infrastructure may create deployment challenges for organizations with multi-vendor security stacks or specific infrastructure requirements.

Purchase Considerations
The solution’s cost structure presents different value propositions depending on existing infrastructure investments. Organizations already utilizing the Zscaler ecosystem may find favorable pricing, while those considering it as an initial Zscaler deployment may encounter higher costs relative to standalone deception alternatives.

The deployment model leverages existing ZPA infrastructure, eliminating the need for additional hardware while maintaining strong scalability characteristics. This approach streamlines implementation for current Zscaler customers but may impact organizations without existing Zscaler investments.

The user experience benefits from Zscaler’s established interface design principles, reflecting years of refinement across the broad security portfolio. The solution provides coverage for common enterprise use cases and basic operational technology scenarios, though it currently lacks certain advanced features such as cloud-native deception capabilities.

Integration capabilities focus on core security infrastructure, including SIEM, SOAR, and EDR systems, with deployment options spanning endpoints and cloud environments. The solution’s effectiveness is closely tied to the broader Zscaler ecosystem, which may influence its suitability for organizations with varying security infrastructure requirements.

Use Cases
Enterprise identity protection is a primary use case for Zscaler’s solution, which leverages existing ZPA infrastructure to deploy deception across distributed environments. The solution’s automated deployment capabilities help security teams maintain consistent coverage while monitoring for credential theft and privilege escalation attempts.

Branch office security is another scenario where the solution’s integration with Zscaler’s broader security ecosystem enables efficient deception deployment across remote locations. The ability to maintain deception coverage without additional hardware requirements makes it particularly effective for distributed organizations.

Traditional network security operations benefit from Zscaler’s integrated approach to deception management. The solution’s ability to work alongside existing EDR systems and SIEM platforms helps security teams maintain visibility across both cloud and on-premises environments while leveraging established security workflows.

The deception technology market has matured significantly from its honeypot origins into a sophisticated security discipline that spans traditional infrastructure, cloud environments, and identity protection. Today’s solutions offer varying approaches to deception, from lightweight token-based deployments to full operating system decoys, with increasing emphasis on cloud-native capabilities and identity-focused use cases.

Several key themes are shaping the market and influencing purchase decisions. Automation has become critical for both deployment and maintenance, with leading vendors leveraging ML to optimize deception placement and reduce operational overhead. Cloud integration capabilities have evolved beyond basic infrastructure support to include native deception for cloud-specific assets and services. Identity deception has emerged as a primary use case, reflecting the broader shift toward identity-centric security architectures.

For organizations evaluating the adoption of deception technology, the initial focus should be on identifying specific use cases aligned with current security gaps and operational capabilities. Rather than attempting comprehensive coverage immediately, consider starting with focused implementations in high-priority areas such as identity protection or cloud infrastructure monitoring. This approach allows security teams to develop expertise with the technology while demonstrating clear value to stakeholders.

Integration capabilities should be a primary consideration during vendor evaluation, as deception technologies are most effective when integrated with existing security infrastructure. Look for solutions that offer proven integrations with your current SIEM, SOAR, and EDR platforms, as well as identity management systems and cloud security tools. Pay particular attention to automation capabilities that can reduce operational overhead and ensure consistent coverage as environments evolve.

Looking forward, the deception technology market is trending toward increased convergence with broader security platforms while maintaining specialized capabilities for specific use cases. ML will play an increasingly important role in deployment optimization and threat detection, while cloud-native capabilities will continue to expand in response to evolving infrastructure requirements. Identity-focused deception will likely become a standard component of zero-trust architectures, requiring closer integration with identity and access management systems.

To prepare for these developments, organizations should establish clear metrics for measuring the effectiveness of deception technology and develop processes for incorporating deception-generated intelligence into security operations. They should also consider how deception technology fits into their broader zero-trust initiatives and ensure their security architecture can support increasing integration between deception and other security controls.

Success with deception technology requires a balanced approach that considers both technical capabilities and operational requirements. While the technology has matured significantly, careful consideration of use cases, integration requirements, and operational capabilities remains essential for successful implementation.

To learn about related topics in this space, check out the following GigaOm Radar reports:

• GigaOm Radar for Attack Surface Management v3.0

• GigaOm Radar for Cloud-Native Application Protection Platforms (CNAPPs) v1.0

• GigaOm Radar for Operational Technology (OT) Security v1.02

*Vendors marked with an asterisk did not participate in our research process for the Radar report, and their capsules and scoring were compiled via desk research.

For more information about our research process for Radar reports, please visit our Methodology.

Chris Ray is a veteran of the cyber security domain. He has a collection of experiences ranging from small teams to large financial institutions. Additionally, Chris has worked in healthcare, manufacturing, and tech. More recently, he has acquired an extensive amount of experience advising and consulting with security vendors, helping them find product-market fit as well as deliver cyber security services.

GigaOm provides technical, operational, and business advice for IT’s strategic digital enterprise and business initiatives. Enterprise business leaders, CIOs, and technology organizations partner with GigaOm for practical, actionable, strategic, and visionary advice for modernizing and transforming their business. GigaOm’s advice empowers enterprises to successfully compete in an increasingly complicated business atmosphere that requires a solid understanding of constantly changing customer demands.

GigaOm works directly with enterprises both inside and outside of the IT organization to apply proven research and methodologies designed to avoid pitfalls and roadblocks while balancing risk and innovation. Research methodologies include but are not limited to adoption and benchmarking surveys, use cases, interviews, ROI/TCO, market landscapes, strategic trends, and technical benchmarks. Our analysts possess 20+ years of experience advising a spectrum of clients from early adopters to mainstream enterprises.

GigaOm’s perspective is that of the unbiased enterprise practitioner. Through this perspective, GigaOm connects with engaged and loyal subscribers on a deep and meaningful level.

© Knowingly, Inc. 2025 "GigaOm Radar for Deception Technology" is a trademark of Knowingly, Inc. For permission to reproduce this report, please contact sales@gigaom.com.