Agent skill

monitor-security

Nightly self-hack orchestrator and continuous security monitoring for embry-os. Four-tier probe system: T0 deterministic (Semgrep, pip-audit, gitleaks), T0.5 threat intelligence (consume-feed, social-bridge, dogpile), T1 OWASP LLM Top 10 analysis, T2 Docker self-hack (containerized /hack against a twin), T3 cascade validation (GPT swarm classifiers + Brandon teacher). Composes /hack, /battle, /consume-feed, /social-bridge, /dogpile, /assistant, and /scillm.

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Install this agent skill to your Project

npx add-skill https://github.com/majiayu000/claude-skill-registry/tree/main/skills/other/other/monitor-security

Metadata

Additional technical details for this skill

short description
Nightly self-hack orchestrator with four-tier probe cascade

SKILL.md

monitor-security

Continuous Operation (Non-Negotiable)

This skill is always-on. It:

  • Runs on its configured schedule indefinitely — it NEVER stops unless explicitly halted by the user
  • The agent MUST NOT stop and wait for the human to ask for status or remember to check
  • If a cycle fails, diagnose the failure, attempt auto-repair, and continue
  • Only escalate to the human if genuinely blocked after exhausting /dogpile research
  • Gracefully handles restarts and maintains state across cycles
  • Is designed for multi-day/week/month autonomous operation

Anti-pattern: Reporting status and waiting for the human to ask "what next?" is UNACCEPTABLE. The agent must proactively fix issues and continue the monitoring loop.

Architecture

Hourly Threat Intel Loop (:00-:10)
  consume-feed → social-bridge → dogpile (if critical CVE) → threat_intel_digest.json

Nightly Self-Hack (00:30-03:00)
  00:30  Read threat_intel_digest.json → prioritize attack vectors
  01:00  T0: Deterministic (Semgrep, pip-audit, gitleaks, grep audits)
  01:15  T1: OWASP LLM Top 10 static analysis
  01:30  T2: Docker self-hack (build twin → /hack scan → score)
  02:00  T3: Cascade validation (T0→T1.5 GPT swarm→T2 Brandon)
  02:30  /battle (conditional — only if T2 critical findings)
  03:00  Report + /memory learn findings

Commands

bash
./run.sh check [--tier N] [--probe NAME] [--autofix] [--json]
./run.sh dashboard
./run.sh fix <probe-name>
./run.sh threat-intel [--dry-run]
./run.sh register-nightly
./run.sh register-hourly
./run.sh help

Probe Tiers

Tier Probes Description Cadence
0 P01-P07 Deterministic (Semgrep, pip-audit, gitleaks, grep) Nightly
0.5 P08-P09 Threat intel ingest + cross-reference Hourly
1 P10-P14 OWASP LLM Top 10 analysis Nightly
2 P20-P23 Docker self-hack Nightly
3 P30-P33 Cascade validation + label accumulation Nightly

Environment Variables

Variable Default Description
MONITOR_TARGET_ROOT auto-detect (pi-mono root) Target project to scan
MONITOR_STATE_DIR ~/.pi/monitor-security State file directory
CASCADE_SHADOW_FILE ~/.pi/monitor-security/shadow.jsonl Shadow mode log
CASCADE_METRICS_FILE ~/.pi/monitor-security/metrics.jsonl Cascade metrics
THREAT_INTEL_DIGEST ~/.pi/monitor-security/threat_intel_digest.json Hourly digest
RETRAIN_LABEL_THRESHOLD 50 Labels before triggering /create-gpt retrain

State

  • ~/.pi/monitor-security/latest_report.json — Latest probe results
  • ~/.pi/monitor-security/threat_intel_digest.json — Accumulated hourly threat intel
  • ~/.pi/monitor-security/training_labels.jsonl — Brandon teacher judgments
  • ~/.pi/monitor-security/shadow.jsonl — Shadow mode comparison log
  • ~/.pi/monitor-security/report_t{0,1,2,3}.json — Per-tier reports

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