Introduction and Overview
Attackers are often inside the network for weeks before they are noticed, and traditional controls produce too many alerts and too little certainty. Deception technology reverses that: decoy systems, fake credentials, and canary assets that no legitimate user should ever touch, so any interaction is a high-confidence alert. This course teaches participants to design, deploy, and operate honeypots and deception layers across on-premises, cloud, and identity environments, and to feed what they capture into the SOC.
The course is hands-on. Participants build decoys, plant honeytokens, connect alerts to SIEM and SOAR, and use AI tools to generate realistic decoy content and triage interactions. It also covers legal, ethical, and operational risks (isolation, data confidentiality, attribution limits) so deployments are safe and defensible.
General Objectives
By the end of the course, participants will be able to:
- Explain the principles of cyber deception and map them to MITRE ATT&CK, MITRE Engage, and the kill chain.
- Choose the right honeypot type (low, medium, high interaction) for a given detection goal.
- Deploy and harden honeypots, including isolation, logging, and containment, so they cannot become a pivot point.
- Create and place honeytokens, canary files, fake credentials, and decoy Active Directory and cloud objects.
- Integrate deception alerts with SIEM/SOAR and write detection rules with low false positives.
- Analyze attacker behavior captured in decoys and convert it into threat intelligence and detection improvements.
- Use AI responsibly to generate believable decoy data and speed up alert triage without exposing real data.
- Build a deception program roadmap with metrics, governance, and legal compliance.
Target Audience
- SOC analysts and incident responders
- Threat hunters and detection engineers
- Security architects and security engineers
- Blue team and purple team members
- Cloud and infrastructure security specialists
- CISOs, security managers, and risk and compliance leaders
Course Outline :
Day 1: Foundations of cyber deception
- Why deception works: attacker psychology, dwell time, and the economics of detection
- Honeypots, honeynets, honeytokens, and canaries: definitions and use cases
- MITRE ATT&CK, MITRE Engage, and mapping decoys to attacker techniques
- Deception vs. traditional detection: where it fits in the security stack
- Legal, ethical, and privacy considerations (entrapment, data, jurisdiction)
- Lab setup: isolated environment, virtualization, and logging baseline
Day 2: Building and deploying honeypots
- Interaction levels: low, medium, and high, and when to use each
- Deploying common honeypots for SSH, web, SMB, RDP, and database services (e.g., Cowrie, OpenCanary, T-Pot)
- Making decoys believable: banners, services, naming, and realistic content
- Network placement: DMZ, internal VLANs, and segmentation
- Hardening and containment so decoys never become a pivot point
- Centralized logging and health monitoring of honeypots
Day 3: Honeytokens, identity, and cloud deception
- Honeytokens and canary tokens: files, URLs, API keys, and database records
- Decoy credentials and fake accounts in Active Directory (honey users, honey SPNs, decoy shares)
- Detecting Kerberoasting, credential dumping, and lateral movement with deceptive assets
- Cloud deception: decoy S3 buckets, fake IAM keys, and canary resources in AWS/Azure
- Deception for data: decoy databases and documents with tracking
- Placement strategy: where attackers actually look
Day 4: Detection engineering, integration, and AI
- Turning decoy interactions into high-confidence alerts
- SIEM integration and detection rules (Splunk, Sentinel, Elastic) with low false positives
- SOAR playbooks: automatic enrichment, isolation, and ticketing on decoy hits
- Using AI to generate realistic decoy content and speed up alert triage, with safeguards on data confidentiality and accuracy
- Analyzing captured attacker behavior: commands, tools, and TTPs
- Converting honeypot data into threat intelligence and IOCs
Day 5: Operating a deception program and capstone
- Deception program design: scope, governance, ownership, and lifecycle
- Metrics: time to detect, alert fidelity, coverage, and cost
- Avoiding detection of the decoys by attackers (fingerprinting and anti-honeypot techniques) and maintaining freshness
- Commercial deception platforms vs. open source: selection criteria
- Capstone workshop: design and deploy a multi-layer deception plan for a case-study organization (network, identity, and cloud), then run a simulated intrusion and respond