About ShadowMatrix CDF
The Problem
The cybersecurity community has made significant strides in standardizing cyber deception concepts. MITRE Engage defines adversary engagement goals and activities. MITRE D3FEND catalogs defensive countermeasures including decoys. Academic researchers have proposed taxonomies for classifying deception techniques.
However, a gap persists between these conceptual frameworks and operational reality. As noted in a 2025 IEEE Communications Surveys & Tutorials paper, no comprehensive framework currently integrates multiple deception dimensions with all defense phases while providing the implementation-level detail that practitioners need to actually deploy and manage deception operations in production environments.
Security teams who want to operationalize deception still face practical questions that existing frameworks do not fully address: How do I implement this specific technique in AWS versus on-premise? What will it cost? How long will it take? What monitoring do I need? How does the technique differ for an OT environment? These implementation-level details are where many deception initiatives stall.
The Solution
ShadowMatrix CDF builds on the conceptual foundations established by MITRE Engage, D3FEND, and academic research to provide what those frameworks intentionally leave to the practitioner: detailed, environment-aware implementation guidance for operationalizing cyber deception. This operational depth is the framework's core contribution.
The framework is organized around seven operational phases that cover the full deception lifecycle: from strategic planning through environment preparation, asset deployment, adversary engagement, detection, intelligence analysis, and operational response. Each phase contains specific techniques with implementation steps, difficulty ratings, cost and time estimates, environment-specific guidance, and mappings to the MITRE ATT&CK techniques they counter or detect.
Related Frameworks
ShadowMatrix CDF exists within a broader ecosystem of cybersecurity frameworks and builds on the work of several foundational efforts:
MITRE Engage
A framework for discussing and planning adversary engagement, deception, and denial activities. Engage defines strategic and engagement goals (Prepare, Expose, Affect, Elicit, Understand) with 23 engagement activities. ShadowMatrix CDF complements Engage by providing environment-specific implementation depth for the activities Engage defines at a conceptual level.
MITRE D3FEND
A knowledge graph of cybersecurity countermeasures that includes a dedicated Deceive tactic with 11 techniques covering honeynets, decoy objects, and decoy credentials. ShadowMatrix CDF techniques can be mapped to D3FEND countermeasures for organizations using D3FEND as their defensive taxonomy.
MITRE ATT&CK
The adversary behavior knowledge base that ShadowMatrix CDF cross-references throughout. Each deception technique in the matrix maps to the ATT&CK techniques it is designed to counter or detect, creating a direct link between adversary behavior and defensive deception.
Academic Research
The framework draws on academic contributions including game-theoretic deception taxonomies (Pawlick, Colbert & Zhu, 2019), three-decade deception surveys (Zhang & Thing, 2021), and recent systematic meta-surveys consolidating cross-domain deception research. These works inform the technique taxonomy and phase structure.
Research Context
This project is part of ongoing research into cyber deception for cyber defense, with particular focus on critical infrastructure protection. The research plan encompasses five stages: framework conceptualization, matrix creation, technical implementation, integration with existing defense frameworks, and deployment automation.
The web navigator you are using represents the framework mapping layer, making the conceptual framework tangible and interactive. Future stages will add technical implementation specifications and Infrastructure-as-Code playbooks for automated deployment of deception environments.
The research findings at various stages will be published in peer-reviewed scientific journals for access by the academic community and cybersecurity practitioners.
About the Team
The ShadowMatrix CDF is developed and operated by a cyber defense research team.
ShadowMatrix CDF is built by security practitioners with hands-on experience in security architecture, detection engineering, and critical infrastructure protection across the energy, financial, manufacturing, and food industries.
The project draws on direct operational experience with threat intelligence, rootkit detection, DDoS mitigation, and advanced threat group analysis. This practitioner background informs the operationally-grounded approach taken throughout the framework — every technique is written from the perspective of someone who has had to actually deploy and maintain defensive infrastructure.
Chris Bassey
Cybersecurity researcher and engineer specializing in security architecture, detection and response, cloud security, adversary emulation, and critical infrastructure security. Based in Prague, with published research and a focus on building practical defensive tooling. Previously led adversary emulation research on threat actors including FIN7 and APT29 at Wazuh. OWASP, IEEE, and ISACA member.
Samson Idowu
Senior Cybersecurity Engineer focused on SIEM architecture, detection engineering, and cloud security. Builds enterprise-scale detection infrastructure at Wazuh, with expertise in MITRE ATT&CK-mapped detection rules, DevSecOps, and AWS. Based in Abuja, Nigeria.
Ifeanyi Onyia-Odike
Cybersecurity analyst with a background in network administration and experience across financial services including FCMB Group and Fidelity Bank. An open-source contributor at Wazuh and active member of the OWASP and ISACA communities. Holds an MS in Security and Network Engineering from Innopolis University.
Abung Ofuka
Cybersecurity strategist and data analytics expert specializing in predictive threat modeling, cyber-economic risk quantification, and enterprise process optimization. Leverages operational cyber deception telemetry from ShadowMatrix to feed predictive threat models, translating active security events into actionable economic-impact metrics. Experienced in utilizing advanced business intelligence and financial modeling to design resilient, data-driven defense strategies. Holds an MBA in Business Analytics, an MSc in Economics, and is currently pursuing a Doctorate in Information Assurance.
Contributing & Contact
ShadowMatrix CDF is designed as an open framework that benefits from community input. Security practitioners, researchers, and organizations with experience in cyber deception are invited to contribute techniques, provide feedback on existing content, and help validate the framework against real-world deployments.
Contributions can take many forms: suggesting new techniques, improving existing descriptions, adding environment-specific guidance, providing MITRE ATT&CK mapping validation, or sharing operational experience with deception deployments.
Contribute
Send proposed techniques, corrections, mapping validations, or operational experience to the contribution inbox.
[email protected]Questions
For general questions about the framework, research collaboration, or adoption guidance, reach the project directly.
[email protected]Roadmap
Framework Creation & Publication
Define the framework taxonomy, publish academic whitepaper for peer review. (Completed)
Matrix Mapping
Map techniques for on-premise, cloud (AWS, Azure, GCP), hybrid, and OT environments. (Completed)
Technical Implementation
Build reference implementations with technical specifications for each environment. (Current stage)
Defense Framework Integration
Integrate with MITRE ATT&CK, SIEMs, EDRs, and SOAR platforms.
Automation Platform
Infrastructure-as-Code playbooks for automated deception environment deployment (Terraform, Ansible).
Disclaimer
The Shadow Matrix and all associated technologies, branding, methodologies, and intellectual property are owned exclusively by ShadowMatrix CDF.
ShadowMatrix CDF is a defensive cybersecurity research framework intended for use by authorized security professionals within their own organizational environments. The techniques described are for defensive purposes: detecting, studying, and misdirecting adversaries who have already breached perimeter defenses. This framework should be used in accordance with applicable laws, regulations, and organizational policies. MITRE ATT&CK, MITRE Engage, and MITRE D3FEND are trademarks or registered trademarks of The MITRE Corporation. References to these frameworks are for interoperability and cross-referencing purposes and do not imply endorsement or affiliation.