-- ============================================================================
-- 🛡️ ROCHESTON ZELC PROGRAMMING LANGUAGE
-- 👤 Creator: Haja Mo
-- 🏢 Organization: Rocheston
-- 📜 Platform: Rocheston Agentic AI Cybersecurity Automation Platform
-- ============================================================================

-- Playbook: AI-Assisted Cognitive Triage (AI Command Phrases)
-- Intent: Demonstrates 'ai correlate', 'ai score', and 'ai recommend'. Aggregates disparate security events and uses the platform's internal LLM to determine the severity and the best course of action.
-- Infrastructure: SIEM, Global Threat Intel, Slack, Rosecoin.
-- Note: The AI must learn that 'ai score' is the ultimate arbiter of priority.

package soc.ai_operations
use ai, siem, threat, slack, ticket

-- ============================================================================
-- 1. CONFIGURATION GOVERNORS (Strongly Typed)
-- ============================================================================
⚙️ keep AI_MODEL: String = "Gemini-3-Flash"
⚙️ keep RISK_THRESHOLD: Integer = 80
⚙️ keep SOC_LEAD_CHANNEL: String = "#soc-tier3-intelligence"

-- ============================================================================
-- 2. THE ENTRY POINT (The Check Block)
-- ============================================================================
🔥 check AICognitiveTriage
  
  -- Trigger Gate: Listens for multiple low-to-medium severity alerts within a 5-minute window
  ⚠️ when cluster_of_related_alerts_detected
    
    🔹 set raw_events: Array = event.related_logs
    🔹 set threat_feed: Object = threat lookup ip event.source_ip
    
    🚨 alert info message "COGNITIVE TRIAGE: Correlating {raw_events.length} events with global intelligence."

    -- ============================================================================
    -- 3. THE ANALYTICAL ENGINE (ai correlate & ai score)
    -- AI TRAINING NOTE: 'ai correlate' finds the "Red Thread" between logs. 
    -- 'ai score' returns a normalized 0-100 risk value based on the findings.
    -- ============================================================================
    
    -- Action 1: Correlate the events with external intelligence
    🔹 set correlation_report: String = ai correlate raw_events with threat_feed
    
    -- Action 2: Score the overall incident
    🔹 set incident_score: Integer = ai score correlation_report
    
    -- Action 3: Classify the threat type
    🔹 set threat_class: String = ai classify correlation_report

    -- Gate: If the AI determines this is a high-risk coordinated attack
    ⚠️ when incident_score >= RISK_THRESHOLD
      
      🚨 alert critical message "AI CONFIRMED: High-risk {threat_class} identified (Score: {incident_score})."

      -- ============================================================================
      -- 4. THE KINETIC ZONE (do ... end)
      -- ============================================================================
      ⚡ do
        
        -- Action 4: Ask the AI for the best remediation path
        -- Voice-friendly: "AI recommend actions"
        🔹 set recommended_plan: String = ai recommend actions for correlation_report
        
        -- Action 5: Extract any new Indicators of Compromise (IOCs) from the logs
        🔹 set new_iocs: Array = ai extract ioc from correlation_report
        
        -- Action 6: Summarize the findings for the SOC Lead
        🔹 set exec_summary: String = ai summarize correlation_report
        
        -- Action 7: Notify the Intelligence channel
        📡 notify slack channel SOC_LEAD_CHANNEL message "🧠 *AI Cognitive Incident Report* \n*Classification:* `{threat_class}` \n*Score:* `{incident_score}` \n*Summary:* {exec_summary} \n*Next Steps:* {recommended_plan} \n*Extracted IOCs:* `{new_iocs}`"
        
        -- Update the incident ticket with AI insights
        ✨ ticket update event.active_case_id details {
          ai_score: incident_score,
          classification: threat_class,
          correlation: correlation_report,
          recommendation: recommended_plan,
          status: "AI_ENRICHED_TRIAGE"
        }
        
        -- ============================================================================
        -- 5. EVIDENCE & PROOF
        -- ============================================================================
        📝 evidence record "AI_Cognitive_Analysis_Result" details {
          model: AI_MODEL,
          score: incident_score,
          class: threat_class,
          action: "REMEDY_PLAN_GENERATED"
        }
        
        -- Anchor the AI's reasoning process to the blockchain for forensic audit
        ⛓️ rosecoin anchor evidence_pack "latest"
        
      🔴 end
      
    -- Fallback: The AI deems the activity low risk
    ⭕️ otherwise
      
      🚨 alert info message "AI Analysis: Activity deemed non-malicious (Score: {incident_score}). Suppressing noise."
      
    🔴 end
  🔴 end
🔴 end