performing-deception-technology-deployment▌
mukul975/Anthropic-Cybersecurity-Skills · updated May 25, 2026
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Deploys deception technology including honeypots, honeytokens, and decoy systems to detect attackers who have bypassed perimeter defenses, providing high-fidelity alerts with near-zero false positive rates. Use when SOC teams need early warning of lateral movement, credential abuse, or internal reconnaissance by deploying convincing traps across the network.
| name | performing-deception-technology-deployment |
| description | 'Deploys deception technology including honeypots, honeytokens, and decoy systems to detect attackers who have bypassed perimeter defenses, providing high-fidelity alerts with near-zero false positive rates. Use when SOC teams need early warning of lateral movement, credential abuse, or internal reconnaissance by deploying convincing traps across the network. ' |
| domain | cybersecurity |
| subdomain | soc-operations |
| tags | - soc - deception - honeypot - honeytoken - canary - lateral-movement - detection |
| version | '1.0' |
| author | mahipal |
| license | Apache-2.0 |
| nist_csf | - DE.CM-01 - DE.AE-02 - RS.MA-01 - DE.AE-06 |
Performing Deception Technology Deployment
When to Use
Use this skill when:
- SOC teams need high-fidelity detection of post-compromise lateral movement with near-zero false positives
- Existing detection tools miss advanced attackers who avoid triggering threshold-based alerts
- The organization wants to detect credential abuse by planting fake credentials as honeytokens
- Network segmentation gaps need compensating detection controls
Do not use as a replacement for fundamental security controls (patching, EDR, network segmentation) — deception is a detection layer, not a prevention mechanism.
Prerequisites
- Network segments identified for honeypot/decoy deployment (server VLANs, DMZ, OT networks)
- Deception platform (Thinkst Canary, Attivo/SentinelOne Hologram, or open-source alternatives)
- SIEM integration for deception alerts (any interaction with deception assets is suspicious)
- Active Directory access for honeytoken account and credential creation
- Network team coordination for IP allocation and traffic routing
Workflow
Step 1: Map Attack Surface for Deception Placement
Identify high-value network segments where attackers would traverse:
DECEPTION DEPLOYMENT MAP
━━━━━━━━━━━━━━━━━━━━━━━━
Segment Decoy Type Rationale
Server VLAN Fake file server Attackers enumerate SMB shares during recon
Database VLAN Fake DB server SQL scanning detected in past incidents
AD/DC Segment Honeytoken account Credential theft detection
Executive Subnet Fake workstation Targeted attacks pivot through exec systems
DMZ Honeypot web app External attacker detection
OT Network Fake PLC/HMI Industrial threat detection
Cloud (AWS VPC) Canary EC2 + S3 Cloud lateral movement detection
Step 2: Deploy Thinkst Canary Devices
Configure Canary devices mimicking real infrastructure:
Windows File Server Canary:
{
"device_name": "FILESERVER-BK04",
"personality": "windows-server-2019",
"services": {
"smb": {
"enabled": true,
"shares": ["Finance_Backup", "HR_Archive", "IT_Docs"],
"files": [
{"name": "Q4_Revenue_2024.xlsx", "alert_on": "read"},
{"name": "employee_ssn_export.csv", "alert_on": "read"},
{"name": "admin_passwords.kdbx", "alert_on": "read"}
]
},
"rdp": {"enabled": true},
"http": {"enabled": false}
},
"network": {
"ip": "10.0.5.200",
"hostname": "FILESERVER-BK04",
"domain": "company.local"
},
"alert_webhook": "https://soar.company.com/api/webhook/canary"
}
Database Server Canary:
{
"device_name": "DB-ARCHIVE-02",
"personality": "linux-mysql",
"services": {
"mysql": {
"enabled": true,
"port": 3306,
"databases": ["customer_pii", "payment_archive"],
"alert_on_login_attempt": true
},
"ssh": {
"enabled": true,
"port": 22,
"alert_on_login_attempt": true
}
},
"network": {
"ip": "10.0.10.50",
"hostname": "db-archive-02"
}
}
Step 3: Deploy Honeytokens in Active Directory
Create fake privileged accounts that should never be used:
# Create honeytoken service account
New-ADUser -Name "svc_sql_backup" `
-SamAccountName "svc_sql_backup" `
-UserPrincipalName "[email protected]" `
-Description "SQL Backup Service Account - DO NOT DELETE" `
-AccountPassword (ConvertTo-SecureString "FakeP@ssw0rd2024!" -AsPlainText -Force) `
-Enabled $true `
-PasswordNeverExpires $true `
-CannotChangePassword $true
# Add to a group that looks attractive (but monitor for any use)
Add-ADGroupMember -Identity "Domain Admins" -Members "svc_sql_backup"
# Place cached credentials on decoy workstation
# (Mimikatz/credential dumping will find these)
cmdkey /add:fileserver-bk04.company.local /user:company\svc_sql_backup /pass:FakeP@ssw0rd2024!
Monitor honeytoken usage in Splunk:
index=wineventlog sourcetype="WinEventLog:Security"
(EventCode=4624 OR EventCode=4625 OR EventCode=4648 OR EventCode=4768 OR EventCode=4769)
TargetUserName="svc_sql_backup"
| eval alert_severity = "CRITICAL"
| eval alert_message = "HONEYTOKEN ACCOUNT USED — Likely credential theft detected"
| table _time, EventCode, src_ip, ComputerName, TargetUserName, Logon_Type, alert_message
Step 4: Deploy Canary Files and Documents
Plant tracked documents that beacon when opened:
Canary Document (Word doc with tracking):
# Using Thinkst Canary API to create a canary token document
import requests
response = requests.post(
"https://YOURCOMPANY.canary.tools/api/v1/canarytoken/create",
data={
"auth_token": "YOUR_API_TOKEN",
"kind": "doc-msword",
"memo": "Finance backup folder canary document",
"flock_id": "flock:default"
}
)
token = response.json()
download_url = token["canarytoken"]["canarytoken_url"]
print(f"Download canary doc: {download_url}")
# Place this document in honeypot SMB shares and sensitive directories
AWS Canary Token (S3 access key):
# Create AWS canary token — alerts when access key is used
response = requests.post(
"https://YOURCOMPANY.canary.tools/api/v1/canarytoken/create",
data={
"auth_token": "YOUR_API_TOKEN",
"kind": "aws-id",
"memo": "Canary AWS key in developer laptop .aws/credentials"
}
)
aws_keys = response.json()
print(f"Access Key: {aws_keys['canarytoken']['access_key_id']}")
print(f"Secret Key: {aws_keys['canarytoken']['secret_access_key']}")
# Plant in .aws/credentials on developer workstations
Step 5: Integrate Deception Alerts with SIEM/SOAR
All deception alerts are high-fidelity — any interaction is suspicious:
Splunk Alert for Canary Triggers:
index=canary sourcetype="canary:alerts"
| eval severity = "CRITICAL"
| eval confidence = "HIGH — Deception asset triggered, zero false positive expected"
| table _time, canary_name, alert_type, source_ip, service, details
| sendalert create_notable param.rule_title="Deception Alert — Canary Triggered"
param.severity="critical" param.drilldown_search="index=canary source_ip=$source_ip$"
SOAR Automated Response:
def canary_triggered(container):
"""Auto-response for deception alerts — high confidence, no approval needed"""
source_ip = container["artifacts"][0]["cef"]["sourceAddress"]
# Immediately isolate the source
phantom.act("quarantine device",
parameters=[{"ip_hostname": source_ip}],
assets=["crowdstrike_prod"],
name="isolate_attacker_host")
# Block at firewall
phantom.act("block ip",
parameters=[{"ip": source_ip, "direction": "both"}],
assets=["palo_alto_prod"],
name="block_attacker_ip")
# Create high-priority incident
phantom.act("create ticket",
parameters=[{
"short_description": f"DECEPTION ALERT: Canary triggered from {source_ip}",
"urgency": "1",
"impact": "1"
}],
assets=["servicenow_prod"])
phantom.set_severity(container, "critical")
Step 6: Maintain Deception Realism
Regularly update decoys to maintain believability:
- Rotate honeytoken passwords quarterly (update cached credentials on decoy workstations)
- Update canary file modification dates to appear recently accessed
- Add realistic network traffic to honeypots (scheduled SMB enumeration, DNS lookups)
- Register honeypot hostnames in DNS and Active Directory to appear in network scans
- Update canary document contents to match current business context
Key Concepts
| Term | Definition |
|---|---|
| Honeypot | Decoy system mimicking real infrastructure to attract and detect attackers in the network |
| Honeytoken | Fake credential, file, or data record that triggers an alert when accessed or used |
| Canary | Lightweight deception device or token that alerts on any interaction (Thinkst Canary platform) |
| Breadcrumb | Planted artifact (cached credential, bookmark, config file) leading attackers to deception assets |
| High-Fidelity Alert | Detection signal with near-zero false positive rate because no legitimate user should interact with deception assets |
| Decoy Network | Set of interconnected honeypots simulating a realistic network segment to observe attacker TTPs |
Tools & Systems
- Thinkst Canary: Commercial deception platform offering hardware/virtual canaries and canary tokens
- Canarytokens.org: Free honeytoken generation service (DNS, HTTP, AWS keys, Word docs, SQL queries)
- Attivo Networks (SentinelOne): Enterprise deception platform with AD decoys and endpoint breadcrumbs
- HoneyDB: Community honeypot data aggregation platform for threat intelligence sharing
- T-Pot: Open-source multi-honeypot platform combining 20+ honeypot types in a Docker deployment
Common Scenarios
- Lateral Movement Detection: Attacker enumerates SMB shares and accesses honeypot file server — immediate high-fidelity alert
- Credential Theft Discovery: Mimikatz dumps honeytoken cached credentials — usage of fake account triggers alert
- Cloud Key Compromise: Stolen AWS canary token used from external IP — detects supply chain or insider compromise
- Ransomware Early Warning: Ransomware encrypts canary files on honeypot shares — early detection before production systems affected
- Insider Threat Signal: Employee accesses honeypot "salary database" — indicates unauthorized data exploration
Output Format
DECEPTION ALERT — CRITICAL
━━━━━━━━━━━━━━━━━━━━━━━━━━
Time: 2024-03-15 14:23:07 UTC
Canary: FILESERVER-BK04 (10.0.5.200)
Service: SMB — File share "Finance_Backup" accessed
Source: 192.168.1.105 (WORKSTATION-042, Finance Dept)
User: company\jsmith
File Accessed: Q4_Revenue_2024.xlsx (canary document)
Alert Confidence: HIGH — No legitimate reason to access deception asset
False Positive Likelihood: <1%
Automated Response:
[DONE] WORKSTATION-042 isolated via CrowdStrike
[DONE] 192.168.1.105 blocked at firewall (bidirectional)
[DONE] Incident INC0012567 created (P1 — Critical)
[PENDING] Tier 2 investigation — determine if workstation compromised or insider threat
How to use performing-deception-technology-deployment on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add performing-deception-technology-deployment
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches performing-deception-technology-deployment from GitHub repository mukul975/Anthropic-Cybersecurity-Skills and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate performing-deception-technology-deployment. Access the skill through slash commands (e.g., /performing-deception-technology-deployment) or your agent's skill management interface.
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
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Use Cases▌
Task Automation & Efficiency
Automate repetitive workflows and reduce manual effort
Example
Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Knowledge Enhancement
Learn new skills, understand complex topics, get expert guidance
Example
Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Quality Improvement
Enhance output quality through reviews, suggestions, and refinements
Example
Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client with skill support
- ›Clear understanding of task or problem to solve
- ›Willingness to iterate and refine outputs
Time Estimate
15-45 minutes depending on use case complexity
Installation Steps
- 1.Install skill using provided installation command
- 2.Test with simple use case relevant to your work
- 3.Evaluate output quality and relevance
- 4.Iterate on prompts to improve results
- 5.Integrate into regular workflow if valuable
Common Pitfalls
- ⚠Expecting perfect results without iteration
- ⚠Not providing enough context in prompts
- ⚠Using skill for tasks outside its intended scope
- ⚠Accepting outputs without review and validation
Best Practices▌
✓ Do
- +Start with clear, specific prompts
- +Provide relevant context and constraints
- +Review and refine all outputs before using
- +Iterate to improve output quality
- +Document successful prompt patterns
✗ Don't
- −Don't use without understanding skill limitations
- −Don't skip validation of outputs
- −Don't share sensitive information in prompts
- −Don't expect skill to replace human judgment
💡 Pro Tips
- ★Be specific about desired format and style
- ★Ask for multiple options to choose from
- ★Request explanations to understand reasoning
- ★Combine AI efficiency with human expertise
When to Use This▌
✓ Use When
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid When
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
Learning Path▌
- 1Familiarize yourself with skill capabilities and limitations
- 2Start with low-risk, non-critical tasks
- 3Progress to more complex and valuable use cases
- 4Build expertise through regular use and experimentation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.4★★★★★60 reviews- ★★★★★Daniel Sharma· Dec 28, 2024
performing-deception-technology-deployment fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Aditi Yang· Dec 20, 2024
performing-deception-technology-deployment reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Charlotte Ramirez· Dec 20, 2024
I recommend performing-deception-technology-deployment for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Diya Khanna· Dec 12, 2024
performing-deception-technology-deployment has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Sakura Choi· Nov 19, 2024
We added performing-deception-technology-deployment from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Diya Dixit· Nov 11, 2024
Keeps context tight: performing-deception-technology-deployment is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Sakura Lopez· Nov 11, 2024
performing-deception-technology-deployment is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Amelia Iyer· Nov 11, 2024
Useful defaults in performing-deception-technology-deployment — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Sakura Abbas· Oct 10, 2024
Solid pick for teams standardizing on skills: performing-deception-technology-deployment is focused, and the summary matches what you get after install.
- ★★★★★Diya Menon· Oct 2, 2024
performing-deception-technology-deployment has been reliable in day-to-day use. Documentation quality is above average for community skills.
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