k7-total-security-deployment-framework

# K7 Total Security Deployment Framework > Skill by [ara.so](https://ara.so) — Security Skills collection. ## Overview K7 Total Security 16.0.1195 is a unified endpoint protection framework supporting multi-platform deployment (Windows, macOS, Linux) with AI-powered threat detection, signatureless behavioral analysis, and centralized policy management. This skill covers configuration, deployment automation, and integration patterns. ## Installation ### Prerequisites - Administrative access on target endpoints - Network connectivity to management console (default port 4451) - Valid K7 Total Security license - (Optional) OpenAI or Claude API credentials for AI-powered analysis ### Console Installation ```bash # Download and install management console curl -O https://download.k7computing.com/k7-console-16.0.1195.tar.gz tar -xzf k7-console-16.0.1195.tar.gz cd k7-console # Install with default settings sudo ./install.sh --silent --accept-license # Verify installation k7-console --version # Expected: K7 Total Security Console 16.0.1195 ``` ### Agent Deployment ```bash # Windows (PowerShell as Administrator) Invoke-WebRequest -Uri "https://download.k7computing.com/k7-agent-win-16.0.1195.msi" -OutFile "k7-agent.msi" msiexec /i k7-agent.msi /quiet SERVERURL="https://console.example.com:4451" # macOS curl -O https://download.k7computing.com/k7-agent-mac-16.0.1195.pkg sudo installer -pkg k7-agent-mac-16.0.1195.pkg -target / # Linux (Debian/Ubuntu) wget https://download.k7computing.com/k7-agent-linux-16.0.1195.deb sudo dpkg -i k7-agent-linux-16.0.1195.deb ``` ## Core Configuration ### Profile Structure Security profiles are defined in YAML and applied to endpoints via the console or API. ```yaml # enterprise_strict.yaml profile_name: "Enterprise Strict" version: "16.0.1195" enforcement_level: "strict" protection_layers: executable_guard: state: enabled action_on_threat: "block_and_alert" exceptions: - path: "/opt/approved-tools/*" - hash: "sha256:a3f9c82..." memory_scanner: state: enabled sensitivity: "maximum" scan_interval_seconds: 180 exclude_processes: - "vmware-vmx" - "VirtualBox" usb_filter: state: enabled policy: "block_all" allow_list: - vendor_id: "0x0781" product_id: "0x5581" serial: "ABC123DEF456" web_filter: state: enabled ssl_inspection: true categories_blocked: - "malware_distribution" - "phishing" - "cryptomining_scripts" - "peer_to_peer" allow_list: - domain: "*.corp.internal" network_protection: firewall_mode: "application_aware" block_outbound_smtp: true dns_filtering: true dns_servers: - "1.1.1.1" - "8.8.8.8" ai_integration: incident_analysis: provider: "openai" api_key_env: "K7_OPENAI_API_KEY" model: "gpt-4-turbo" max_tokens: 2000 temperature: 0.3 endpoint: "https://api.openai.com/v1/chat/completions" automated_response: provider: "claude" api_key_env: "K7_CLAUDE_API_KEY" model: "claude-3-opus-20240229" max_tokens: 1500 endpoint: "https://api.anthropic.com/v1/messages" logging: verbose: true retention_days: 365 forward_to: - type: "syslog" host: "siem.example.com" port: 514 protocol: "tcp" - type: "elasticsearch" url: "https://elk.example.com:9200" index: "k7-security-events" auth_token_env: "K7_ELK_TOKEN" notifications: email: enabled: true smtp_server: "smtp.example.com:587" from: "security@example.com" recipients: - "soc@example.com" tls: true auth_user_env: "K7_SMTP_USER" auth_pass_env: "K7_SMTP_PASS" webhook: enabled: true url_env: "K7_WEBHOOK_URL" method: "POST" headers: Content-Type: "application/json" retry_attempts: 3 timeout_seconds: 10 ``` ### Applying Profiles ```bash # Apply to single endpoint k7-console apply-profile \ --profile enterprise_strict.yaml \ --target 192.168.1.100 \ --auth-cert /etc/k7/admin.pem \ --log-level verbose # Apply to endpoint group k7-console apply-profile \ --profile enterprise_strict.yaml \ --group "engineering-team" \ --auth-cert /etc/k7/admin.pem \ --schedule "2024-01-15T02:00:00Z" # Validate profile before deployment k7-console validate-profile --file enterprise_strict.yaml ``` ## API Integration ### Python Client Example ```python import os import requests from typing import Dict, List class K7SecurityClient: def __init__(self, base_url: str, cert_path: str): self.base_url = base_url.rstrip('/') self.session = requests.Session() self.session.cert = cert_path self.session.verify = True def apply_profile(self, profile_data: Dict, targets: List[str]) -> Dict: """Apply security profile to multiple endpoints""" payload = { "profile": profile_data, "targets": targets, "async": True } response = self.session.post( f"{self.base_url}/api/v1/profiles/apply", json=payload, timeout=30 ) response.raise_for_status() return response.json() def get_endpoint_status(self, endpoint_id: str) -> Dict: """Retrieve current protection status for endpoint""" response = self.session.get( f"{self.base_url}/api/v1/endpoints/{endpoint_id}/status", timeout=10 ) response.raise_for_status() return response.json() def query_threats(self, start_time: str, severity: str = "high") -> List[Dict]: """Query threat events from centralized log""" params = { "start": start_time, "severity": severity, "limit": 1000 } response = self.session.get( f"{self.base_url}/api/v1/threats/query", params=params, timeout=30 ) response.raise_for_status() return response.json()["events"] def trigger_ai_analysis(self, event_id: str) -> Dict: """Request AI analysis for specific threat event""" payload = {"event_id": event_id} response = self.session.post( f"{self.base_url}/api/v1/ai/analyze", json=payload, timeout=60 ) response.raise_for_status() return response.json() # Usage client = K7SecurityClient( base_url=os.environ["K7_CONSOLE_URL"], cert_path="/etc/k7/admin.pem" ) # Deploy profile to engineering workstations profile = { "profile_name": "Engineering Developer", "enforcement_level": "balanced", "protection_layers": { "executable_guard": { "state": "enabled", "exceptions": ["/opt/dev-tools/*"] } } } result = client.apply_profile( profile_data=profile, targets=["192.168.1.10", "192.168.1.11", "192.168.1.12"] ) print(f"Deployment job ID: {result['job_id']}") # Check endpoint status status = client.get_endpoint_status("192.168.1.10") print(f"Protection active: {status['protection_active']}") print(f"Last scan: {status['last_scan_timestamp']}") # Query recent high-severity threats threats = client.query_threats( start_time="2024-01-01T00:00:00Z", severity="critical" ) for threat in threats: print(f"Threat: {threat['type']} on {threat['endpoint_id']}") # Request AI analysis analysis = client.trigger_ai_analysis(threat["event_id"]) print(f"AI recommendation: {analysis['recommendation']}") ``` ### Webhook Integration for Slack Notifications ```python import os import hmac import hashlib from flask import Flask, request, jsonify app = Flask(__name__) WEBHOOK_SECRET = os.environ["K7_WEBHOOK_SECRET"] SLACK_URL = os.environ["SLACK_WEBHOOK_URL"] @app.route("/k7-webhook", methods=["POST"]) def handle_k7_event(): # Verify signature signature = request.headers.get("X-K7-Signature") body = request.get_data() expected = hmac.new( WEBHOOK_SECRET.encode(), body, hashlib.sha256 ).hexdigest() if not hmac.compare_digest(signature, expected): return jsonify({"error": "Invalid signature"}), 403 event = request.json # Format Slack message slack_payload = { "text": f"🚨 K7 Security Alert: {event['threat_type']}", "blocks": [ { "type": "section", "text": { "type": "mrkdwn", "text": f"*Threat Detected*\n*Type:* {event['threat_type']}\n*Endpoint:* {event['endpoint_id']}\n*Severity:* {event['severity']}" } }, { "type": "section", "text": { "type": "mrkdwn", "text": f"*AI Analysis:*\n{event.get('ai_recommendation', 'Pending analysis...')}" } } ] } # Forward to Slack requests.post(SLACK_URL, json=slack_payload) return jsonify({"status": "processed"}), 200 if __name__ == "__main__": app.run(host="0.0.0.0", port=8080) ``` ## Common Deployment Patterns ### Mass Deployment via Ansible ```yaml # k7-deploy.yml --- - name: Deploy K7 Total Security to fleet hosts: all_endpoints become: yes vars: k7_console_url: "https://console.example.com:4451" k7_profile: "{{ lookup('file', 'profiles/{{ inventory_hostname_short }}.yaml') }}" tasks: - name: Install K7 agent (Debian/Ubuntu) apt: deb: "https://download.k7computing.com/k7-agent-linux-16.0.1195.deb" state: present when: ansible_os_family == "Debian" - name: Configure agent connection template: src: agent-config.j2 dest: /etc/k7/agent.conf mode: '0600' notify: restart k7-agent - name: Apply security profile command: > k7-console apply-profile --profile {{ k7_profile }} --target {{ ansible_default_ipv4.address }} --auth-cert /etc/k7/admin.pem delegate_to: localhost handlers: - name: restart k7-agent service: name: k7-agent state: restarted ``` ### Dynamic Policy Based on Host Role ```python def generate_profile_for_role(role: str) -> Dict: """Generate K7 profile based on host role""" base = { "version": "16.0.1195", "enforcement_level": "adaptive", "logging": {"verbose": True, "retention_days": 90} } role_configs = { "web_server": { "web_filter": {"state": "disabled"}, "network_protection": { "firewall_mode": "strict", "allowed_ports": [80, 443] } }, "database_server": { "usb_filter": {"state": "enabled", "policy": "block_all"}, "network_protection": {