performing-deception-technology-deployment

mukul975/Anthropic-Cybersecurity-Skills · updated May 25, 2026

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$npx skills install mukul975/Anthropic-Cybersecurity-Skills/performing-deception-technology-deployment
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summary

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.

skill.md
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

TermDefinition
HoneypotDecoy system mimicking real infrastructure to attract and detect attackers in the network
HoneytokenFake credential, file, or data record that triggers an alert when accessed or used
CanaryLightweight deception device or token that alerts on any interaction (Thinkst Canary platform)
BreadcrumbPlanted artifact (cached credential, bookmark, config file) leading attackers to deception assets
High-Fidelity AlertDetection signal with near-zero false positive rate because no legitimate user should interact with deception assets
Decoy NetworkSet 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

How to use performing-deception-technology-deployment on Cursor

AI-first code editor with Composer

1

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
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills install mukul975/Anthropic-Cybersecurity-Skills/performing-deception-technology-deployment

The skills CLI fetches performing-deception-technology-deployment from GitHub repository mukul975/Anthropic-Cybersecurity-Skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
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│ ●Cursor(selected)
│ • Cursor
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4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/performing-deception-technology-deployment

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. 1.Install skill using provided installation command
  2. 2.Test with simple use case relevant to your work
  3. 3.Evaluate output quality and relevance
  4. 4.Iterate on prompts to improve results
  5. 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

  1. 1Familiarize yourself with skill capabilities and limitations
  2. 2Start with low-risk, non-critical tasks
  3. 3Progress to more complex and valuable use cases
  4. 4Build expertise through regular use and experimentation

Discussion

Product Hunt–style comments (not star reviews)
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general reviews

Ratings

4.460 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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