Deploy honeypots, honeytokens, and canaries to detect attacker activity.
npx skills add https://github.com/DCx7C5/ai-marketplace --skill skill-md
Please help me install this Agent Skill. Skill: SKILL.md- Source: https://github.com/DCx7C5/ai-marketplace/tree/main/skills/deception Command: npx skills add https://github.com/DCx7C5/ai-marketplace --skill skill-md
Deception-based defense provides early warning by deploying decoy assets (honeypots, honeytokens, and canaries) that lure and alert on attacker activity, enabling faster detection and containment.
Deploy deception assets across your network to begin monitoring for attacker activity.
High-intent search queries and answers about installing and using this skill.
Deploying honeypots and honeytokens across networks detects lateral movement by luring attackers into interacting with decoy assets, which generates immediate alerts for intrusion detection and breach containment.
Deception technology detects credential abuse by embedding honeytokens that trigger high-fidelity alerts when attackers attempt unauthorized access, enabling SOC teams to automate containment and incident response workflows.
Canary alerts integrate with SIEM workflows to automate containment and case creation, streamlining incident response by feeding high-fidelity breach detection data directly into existing SOC operations.
The best way to set up enterprise deception environments is orchestrating decoy assets across networks to satisfy realism requirements, catching reconnaissance attempts and credential abuse through high-fidelity alerting.
Deception technology works for detecting network reconnaissance by deploying decoy assets that attackers probe during initial pivoting, generating alerts that reveal attacker techniques and lateral movement paths.
Honeypots for breach detection require careful orchestration to maintain realism; avoid deployment without proper alerting integration, as poorly configured decoys can generate noise and fail to integrate with SOC containment workflows.
michaelsvanbeekDetect unusual patterns in time-series, logs, and metric data.
zenobi-usCoordinate incident response for security breaches and operational incidents.
AdawoduAutomate Sigma SIEM rule creation, MITRE ATT&CK mapping, and detection-as-code pipelines.
TumeloRamaphosaMonitors live applications after deployment for console errors, performance regressions, and page failures.
