k7-total-security-unified-defense

K7 Total Security Unified Defense Framework

Skill by ara.so — Security Skills collection.

Overview

K7 Total Security 16.0.1195 is a unified endpoint protection framework providing multi-layered defense across Windows, macOS, and Linux platforms. The system employs signatureless AI detection, behavioral monitoring, and centralized policy management with external AI integration (OpenAI/Claude) for threat analysis.

Key Capabilities:

• Cross-platform security profile deployment (Windows, macOS, Linux)
• Signatureless AI-based threat detection
• Modular protection layers (executable guard, memory scanner, USB/web filters)
• AI-powered incident analysis via OpenAI GPT and Claude APIs
• Centralized management console with remote policy application
• SIEM integration and webhook alerting

Installation

Prerequisites

• Administrative/root access on target systems
• Network connectivity for central management
• Optional: API keys for OpenAI/Claude integration

Installation Methods

Windows:

# Download and install agent
Invoke-WebRequest -Uri "https://k7-releases.example/K7-Agent-16.0.1195-x64.msi" -OutFile "K7-Agent.msi"
msiexec /i K7-Agent.msi /quiet /log install.log MANAGEMENT_SERVER="10.0.1.50"

macOS:

# Install via DMG or Homebrew
brew tap k7security/tap
brew install k7-total-security

# Configure management server
sudo k7-agent --set-server 10.0.1.50 --enroll

Linux (Ubuntu/Debian):

# Add repository and install
wget -qO - https://apt.k7security.example/pubkey.gpg | sudo apt-key add -
echo "deb https://apt.k7security.example/ stable main" | sudo tee /etc/apt/sources.list.d/k7.list
sudo apt update && sudo apt install k7-total-security

# Configure
sudo k7-agent configure --server 10.0.1.50

Configuration

Profile Structure

Security profiles are defined in YAML format and applied via the management console or CLI:

profile_name: "production_strict"
version: "16.0.1195"
enforcement_level: "strict"  # strict | adaptive | permissive

protection_layers:
  executable_guard:
    state: enabled
    action_on_threat: "quarantine"  # quarantine | block | alert
    exceptions:
      - path: "/opt/approved-tools/*"
      - hash: "sha256:abc123..."
    
  memory_scanner:
    state: enabled
    sensitivity: "high"  # low | medium | high
    scan_interval_seconds: 300
    
  usb_filter:
    state: enabled
    policy: "block_all"  # allow_all | read_only | block_all | read_only_for_unknown
    allow_list:
      - vendor_id: "0x0781"  # SanDisk
      - serial: "ABC-12345"
    
  web_filter:
    state: enabled
    categories_blocked:
      - "malware_distribution"
      - "phishing"
      - "cryptomining_scripts"
      - "c2_servers"
    allow_list:
      - domain: "*.trusted-cdn.com"
      - ip_range: "10.0.0.0/8"

ai_integration:
  incident_analysis:
    provider: "openai"  # openai | claude | none
    model: "gpt-4-turbo"
    endpoint: "https://api.openai.com/v1/chat/completions"
    api_key_env: "K7_OPENAI_API_KEY"
    max_tokens: 2000
    temperature: 0.3
    
  automated_response:
    provider: "claude"
    model: "claude-3-opus-20240229"
    endpoint: "https://api.anthropic.com/v1/messages"
    api_key_env: "K7_CLAUDE_API_KEY"
    webhook_retries: 3

logging:
  verbose: true
  retention_days: 90
  forward_to:
    - type: "syslog"
      server: "10.0.1.50:514"
    - type: "elasticsearch"
      url: "https://logs.example.io:9200"
      index_prefix: "k7-security"

notifications:
  email:
    enabled: true
    smtp_server: "smtp.example.com:587"
    from: "k7-alerts@example.com"
    recipients:
      - "secops@example.com"
  webhook:
    enabled: true
    url_env: "K7_SLACK_WEBHOOK"
    format: "slack"  # slack | discord | teams | generic

Environment Variables

Set these in your deployment environment:

# AI Integration
export K7_OPENAI_API_KEY="sk-..."
export K7_CLAUDE_API_KEY="sk-ant-..."

# Webhook Notifications
export K7_SLACK_WEBHOOK="https://hooks.slack.com/services/..."

# Management Server
export K7_MGMT_SERVER="10.0.1.50"
export K7_MGMT_PORT="4451"
export K7_AUTH_CERT="/path/to/admin.pem"

CLI Commands

k7-console (Management Console)

# Apply profile to remote endpoint
k7-console --apply-profile production_strict.yaml \
           --target 192.168.8.105 \
           --auth-file $K7_AUTH_CERT \
           --log-level verbose \
           --timeout 120

# Bulk deployment to multiple hosts
k7-console --apply-profile production_strict.yaml \
           --target-file hosts.txt \
           --parallel 10 \
           --auth-file $K7_AUTH_CERT

# Query endpoint status
k7-console --query-status --target 192.168.8.105 \
           --auth-file $K7_AUTH_CERT \
           --output json

# Force policy sync
k7-console --sync-policy --target 192.168.8.105 \
           --auth-file $K7_AUTH_CERT

# View active threats
k7-console --list-threats --target 192.168.8.105 \
           --since "2026-01-01" \
           --severity high

k7-agent (Local Agent)

# Check agent status
k7-agent status

# Manual scan
k7-agent scan --path /home/user/Downloads --deep

# Update threat definitions
k7-agent update --force

# View quarantine
k7-agent quarantine list

# Restore quarantined file
k7-agent quarantine restore --id QID-12345

# Generate diagnostic report
k7-agent diagnostics --output /tmp/k7-diag.zip

# Configure local settings
k7-agent configure --memory-limit 2G --scan-threads 4

Code Examples

Python: Policy Deployment Automation

import yaml
import subprocess
import os
from pathlib import Path

class K7PolicyManager:
    def __init__(self, auth_cert_path: str, mgmt_server: str = None):
        self.auth_cert = auth_cert_path
        self.mgmt_server = mgmt_server or os.getenv('K7_MGMT_SERVER')
        
    def apply_profile(self, profile_path: str, targets: list[str], 
                     timeout: int = 120) -> dict:
        """Apply security profile to multiple endpoints."""
        results = {}
        
        for target in targets:
            cmd = [
                'k7-console',
                '--apply-profile', profile_path,
                '--target', target,
                '--auth-file', self.auth_cert,
                '--timeout', str(timeout),
                '--output', 'json'
            ]
            
            try:
                result = subprocess.run(
                    cmd, 
                    capture_output=True, 
                    text=True, 
                    check=True
                )
                results[target] = {
                    'success': True,
                    'output': result.stdout
                }
            except subprocess.CalledProcessError as e:
                results[target] = {
                    'success': False,
                    'error': e.stderr
                }
                
        return results
    
    def generate_profile(self, name: str, enforcement: str = 'adaptive',
                        ai_provider: str = 'openai') -> str:
        """Generate a security profile from template."""
        profile = {
            'profile_name': name,
            'version': '16.0.1195',
            'enforcement_level': enforcement,
            'protection_layers': {
                'executable_guard': {
                    'state': 'enabled',
                    'action_on_threat': 'quarantine'
                },
                'memory_scanner': {
                    'state': 'enabled',
                    'sensitivity': 'high',
                    'scan_interval_seconds': 300
                },
                'usb_filter': {
                    'state': 'enabled',
                    'policy': 'read_only_for_unknown'
                },
                'web_filter': {
                    'state': 'enabled',
                    'categories_blocked': [
                        'malware_distribution',
                        'phishing',
                        'cryptomining_scripts'
                    ]
                }
            },
            'ai_integration': {
                'incident_analysis': {
                    'provider': ai_provider,
                    'model': 'gpt-4-turbo' if ai_provider == 'openai' else 'claude-3-opus-20240229',
                    'api_key_env': f'K7_{ai_provider.upper()}_API_KEY',
                    'max_tokens': 2000
                }
            }
        }
        
        output_path = f'/tmp/k7-profile-{name}.yaml'
        with open(output_path, 'w') as f:
            yaml.dump(profile, f, default_flow_style=False)
            
        return output_path

# Usage
manager = K7PolicyManager(auth_cert_path='/etc/k7/admin.pem')

# Generate profile
profile_path = manager.generate_profile(
    name='dev_workstations',
    enforcement='adaptive',
    ai_provider='openai'
)

# Deploy to endpoints
targets = ['192.168.1.10', '192.168.1.11', '192.168.1.12']
results = manager.apply_profile(profile_path, targets)

for target, result in results.items():
    if result['success']:
        print(f"✓ {target}: Profile applied successfully")
    else:
        print(f"✗ {target}: {result['error']}")

Bash: Automated Threat Response

#!/bin/bash
# k7-threat-monitor.sh - Monitor and respond to threats

K7_AUTH_CERT="${K7_AUTH_CERT:-/etc/k7/admin.pem}"
ALERT_WEBHOOK="${K7_SLACK_WEBHOOK}"

monitor_threats() {
    local target="$1"
    
    # Query for high-severity threats in last hour
    threats=$(k7-console --list-threats \
        --target "$target" \
        --auth-file "$K7_AUTH_CERT" \
        --since "1 hour ago" \
        --severity high \
        --output json)
    
    if [ "$(echo "$threats" | jq '.count')" -gt 0 ]; then
        echo "⚠️  High-severity threats detected on $target"
        
        # Send webhook alert
        send_alert "$target" "$threats"
        
        # Trigger AI analysis
        analyze_with_ai "$target" "$threats"
        
        # Auto-isolate if critical
        if [ "$(echo "$threats" | jq '.critical_count')" -gt 0 ]; then
            isolate_endpoint "$target"
        fi
    fi
}

send_alert() {
    local target="$1"
    local threats="$2"
    
    curl -X POST "$ALERT_WEBHOOK" \
        -H 'Content-Type: application/json' \
        -d @- <<EOF
{
    "text": "K7 Security Alert",
    "attachments": [{
        "color": "danger",
        "title": "Threats detected on $target",
        "text": "$(echo "$threats" | jq -r '.summary')",
        "fields": [
            {
                "title": "Severity",
                "value": "HIGH",
                "short": true
            },
            {
                "title": "Count",
                "value": "$(echo "$threats" | jq '.count')",
                "short": true
            }
        ]
    }]
}
EOF
}

analyze_with_ai() {
    local target="$1"
    local threats="$2"
    
    # Trigger AI analysis via K7 console
    k7-console --analyze-threat \
        --target "$target" \
        --auth-file "$K7_AUTH_CERT" \
        --threat-data "$threats" \
        --ai-provider openai \
        --output /var/log/k7/analysis-$(date +%s).json
}

isolate_endpoint() {
    local target="$1"
    
    echo "🔒 Isolating endpoint $target"
    
    k7-console --isolate \
        --target "$target" \
        --auth-file "$K7_AUTH_CERT" \
        --reason "Critical threat detected - automated response"
}

# Monitor list of endpoints
ENDPOINTS_FILE="${1:-/etc/k7/monitored-hosts.txt}"

while IFS= read -r endpoint; do
    monitor_threats "$endpoint"
done < "$ENDPOINTS_FILE"

PowerShell: Windows Fleet Management

# K7-FleetManager.ps1

class K7FleetManager {
    [string]$AuthCert
    [string]$MgmtServer
    
    K7FleetManager([string]$authCertPath) {
        $this.AuthCert = $authCertPath
        $this.MgmtServer = $env:K7_MGMT_SERVER
    }
    
    [hashtable] GetEndpointStatus([string[]]$targets) {
        $results = @{}
        
        foreach ($target in $targets) {
            $cmd = @(
                'k7-console',
                '--query-status',
                '--target', $target,
                '--auth-file', $this.AuthCert,
                '--output', 'json'
            )
            
            try {
                $output = & $cmd[0] $cmd[1..($cmd.Length-1)] 2>&1 | ConvertFrom-Json
                $results[$target] = @{
                    Success = $true
                    Status = $output
                }
            }
            catch {
                $results[$target] = @{
                    Success = $false
                    Error = $_.Exception.Message
                }
            }
        }
        
        return $results
    }
    
    [void] DeployProfileByGroup([hashtable]$groupProfiles) {
        foreach ($group in $groupProfiles.Keys) {
            $profilePath = $groupProfiles[$group].Profile
            $targets = $groupProfiles[$group].Endpoints
            
            Write-Host "Deploying profile '$profilePath' to $($targets.Count) endpoints in group '$group'"
            
            $cmd = @(
                'k7-console',
                '--apply-profile', $profilePath,
                '--target-file', ($targets -join "`n" | Out-File -FilePath "$env:TEMP\k7-targets-$group.txt" -PassThru).FullName,
                '--auth-file', $this.AuthCert,
                '--parallel', '10'
            )
            
            & $cmd[0] $cmd[1..($cmd.Length-1)]
        }
    }
    
    [object[]] AuditCompliance([string[]]$targets, [string]$requiredProfile) {
        $nonCompliant = @()
        
        $statuses = $this.GetEndpointStatus($targets)
        
        foreach ($target in $statuses.Keys) {
            if ($statuses[$target].Success) {
                $currentProfile = $statuses[$target].Status.active_profile
                if ($currentProfile -ne $requiredProfile) {
                    $nonCompliant += [PSCustomObject]@{
                        Endpoint = $target
                        CurrentProfile = $currentProfile
                        RequiredProfile = $requiredProfile
                    }
                }
            }
        }
        
        return $nonCompliant
    }
}

# Usage
$manager = [K7FleetManager]::new("C:\K7\admin.pem")

# Deploy profiles by organizational groups
$groupProfiles = @{
    'Engineering' = @{
        Profile = 'C:\K7\profiles\engineering-adaptive.yaml'
        Endpoints = @('10.0.1.10', '10.0.1.11', '10.0.1.12')
    }
    'Finance' = @{
        Profile = 'C:\K7\profiles\finance-strict.yaml'
        Endpoints = @('10.0.2.10', '10.0.2.11')
    }
}

$manager.DeployProfileByGroup($groupProfiles)

# Audit compliance
$nonCompliant = $manager.AuditCompliance(
    @('10.0.1.10', '10.0.1.11', '10.0.2.10'),
    'production_strict'
)

if ($nonCompliant.Count -gt 0) {
    Write-Warning "Found $($nonCompliant.Count) non-compliant endpoints:"
    $nonCompliant | Format-Table
}

Common Patterns

Pattern 1: Zero-Trust USB Policy

profile_name: "zero_trust_usb"
version: "16.0.1195"

protection_layers:
  usb_filter:
    state: enabled
    policy: "block_all"
    allow_list:
      # Only allow specific approved devices by serial
      - vendor_id: "0x0781"
        product_id: "0x5581"
        serial: "APPROVED-SN-001"
      - vendor_id: "0x13FE"
        product_id: "0x4200"
        serial: "APPROVED-SN-002"
    
    auto_scan: true
    mount_read_only: true
    log_all_attempts: true

notifications:
  webhook:
    enabled: true
    url_env: "K7_USB_ALERT_WEBHOOK"
    notify_on:
      - "unauthorized_usb_attempt"
      - "usb_scan_threat_found"

Pattern 2: Developer Workstation (Balanced)

profile_name: "developer_balanced"
version: "16.0.1195"
enforcement_level: "adaptive"

protection_layers:
  executable_guard:
    state: enabled
    action_on_threat: "alert"  # Alert only, don't block
    exceptions:
      - path: "/home/*/.npm/*"
      - path: "/opt/nodejs/*"
      - path: "/usr/local/bin/docker*"
      - path: "C:\\Program Files\\Docker\\*"
      - path: "C:\\Users\\*\\AppData\\Local\\Programs\\*"
    
  memory_scanner:
    state: enabled
    sensitivity: "medium"
    scan_interval_seconds: 600  # Less frequent
    exclude_processes:
      - "node"
      - "python"
      - "docker"
    
  web_filter:
    state: enabled
    categories_blocked:
      - "malware_distribution"
      - "phishing"
    allow_list:
      - domain: "*.npmjs.com"
      - domain: "*.github.com"
      - domain: "*.docker.io"

ai_integration:
  incident_analysis:
    provider: "openai"
    model: "gpt-4-turbo"
    api_key_env: "K7_OPENAI_API_KEY"

Pattern 3: Multi-Site SIEM Integration

profile_name: "enterprise_siem"
version: "16.0.1195"

logging:
  verbose: true
  retention_days: 365
  forward_to:
    # Primary SIEM
    - type: "elasticsearch"
      url: "https://siem-primary.corp.example:9200"
      index_prefix: "k7-security"
      auth_env: "K7_ES_PRIMARY_TOKEN"
      
    # Backup SIEM
    - type: "elasticsearch"
      url: "https://siem-backup.corp.example:9200"
      index_prefix: "k7-security"
      auth_env: "K7_ES_BACKUP_TOKEN"
      
    # Syslog for legacy systems
    - type: "syslog"
      server: "10.0.10.50:514"
      protocol: "tcp"
      format: "rfc5424"
      
  enrichment:
    include_system_info: true
    include_user_context: true
    include_process_tree: true

Troubleshooting

Agent Not Connecting to Management Server

Symptom: Agent shows "Disconnected" status

# Check network connectivity
k7-agent diagnostics --network-test

# Verify certificate
openssl verify -CAfile /etc/k7/ca.crt $K7_AUTH_CERT

# Test management server reachability
nc -zv $K7_MGMT_SERVER 4451

# Check agent logs
k7-agent logs --tail 100 --level error

# Force re-enrollment
sudo k7-agent configure --server $K7_MGMT_SERVER --force-enroll

High Memory Usage

Symptom: Agent consuming excessive RAM

# Check current memory usage
k7-agent status --verbose | grep Memory

# Adjust memory limits
k7-agent configure --memory-limit 1G --scan-threads 2

# Exclude large directories from real-time scanning
# Edit profile and add exceptions
k7-agent configure --exclude-path /mnt/large-storage

Profile Application Fails

Symptom: k7-console --apply-profile returns error

# Validate profile syntax
k7-console --validate-profile production.yaml

# Check permissions
ls -l production.yaml
stat $K7_AUTH_CERT

# Test with verbose output
k7-console --apply-profile production.yaml \
           --target 192.168.1.10 \
           --auth-file $K7_AUTH_CERT \
           --log-level debug \
           --dry-run  # Test without applying

# Check target agent version compatibility
k7-console --query-status --target 192.168.1.10 \
           --auth-file $K7_AUTH_CERT | grep version

AI Integration Not Working

Symptom: Threat analysis not invoking AI

# Verify API key is set
echo $K7_OPENAI_API_KEY | wc -c  # Should be >0

# Test API connectivity
curl -H "Authorization: Bearer $K7_OPENAI_API_KEY" \
     https://api.openai.com/v1/models

# Check AI integration logs
k7-console --query-logs --target 192.168.1.10 \
           --auth-file $K7_AUTH_CERT \
           --filter "ai_integration" \
           --since "1 hour ago"

# Verify profile has correct AI settings
grep -A10 "ai_integration:" production.yaml

USB Filter Blocking Legitimate Device

Symptom: Approved USB device is blocked

# List currently connected USB devices
lsusb  # Linux
system_profiler SPUSBDataType  # macOS

# Get vendor/product IDs
# Add to allow_list in profile
k7-agent usb list --verbose

# Temporarily allow device (until next policy sync)
k7-agent usb allow --vendor-id 0x0781 --serial ABC123

# Update profile and re-apply
# Edit yaml file, then:
k7-console --apply-profile updated.yaml --target <host>

Best Practices

1. Always use environment variables for secrets — Never hardcode API keys or credentials in profiles
2. Test profiles in dry-run mode before deploying to production
3. Use adaptive enforcement for developer workstations, strict for production servers
4. Enable verbose logging initially, reduce after stabilization
5. Set up automated compliance audits to detect configuration drift
6. Integrate with existing SIEM for centralized monitoring
7. Define clear exception paths for development tools and CI/CD systems
8. Implement AI analysis for high-severity threats to reduce response time
9. Regularly update threat definitions via k7-agent update
10. Backup profile configurations and version control them in Git