Python-Icap-Yara

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Comprehensive python-icap-yara commands and workflows for system administration across all platforms.

Basic Commands

Command	Description
python-icap-yara --version	Show python-icap-yara version
python-icap-yara --help	Display help information
python-icap-yara init	Initialize python-icap-yara in current directory
python-icap-yara status	Check current status
python-icap-yara list	List available options
python-icap-yara info	Display system information
python-icap-yara config	Show configuration settings
python-icap-yara update	Update to latest version
python-icap-yara start	Start python-icap-yara service
python-icap-yara stop	Stop python-icap-yara service
python-icap-yara restart	Restart python-icap-yara service
python-icap-yara reload	Reload configuration

Installation

Linux/Ubuntu

# Package manager installation
sudo apt update
sudo apt install python-icap-yara

# Alternative installation
wget https://github.com/example/python-icap-yara/releases/latest/download/python-icap-yara-linux
chmod +x python-icap-yara-linux
sudo mv python-icap-yara-linux /usr/local/bin/python-icap-yara

# Build from source
git clone https://github.com/example/python-icap-yara.git
cd python-icap-yara
make && sudo make install

macOS

# Homebrew installation
brew install python-icap-yara

# MacPorts installation
sudo port install python-icap-yara

# Manual installation
curl -L -o python-icap-yara https://github.com/example/python-icap-yara/releases/latest/download/python-icap-yara-macos
chmod +x python-icap-yara
sudo mv python-icap-yara /usr/local/bin/

Windows

# Chocolatey installation
choco install python-icap-yara

# Scoop installation
scoop install python-icap-yara

# Winget installation
winget install python-icap-yara

# Manual installation
# Download from https://github.com/example/python-icap-yara/releases
# Extract and add to PATH

Configuration

Command	Description
python-icap-yara config show	Display current configuration
python-icap-yara config list	List all configuration options
python-icap-yara config set <key> <value>	Set configuration value
python-icap-yara config get <key>	Get configuration value
python-icap-yara config unset <key>	Remove configuration value
python-icap-yara config reset	Reset to default configuration
python-icap-yara config validate	Validate configuration file
python-icap-yara config export	Export configuration to file

Advanced Operations

File Operations

# Create new file/resource
python-icap-yara create <name>

# Read file/resource
python-icap-yara read <name>

# Update existing file/resource
python-icap-yara update <name>

# Delete file/resource
python-icap-yara delete <name>

# Copy file/resource
python-icap-yara copy <source> <destination>

# Move file/resource
python-icap-yara move <source> <destination>

# List all files/resources
python-icap-yara list --all

# Search for files/resources
python-icap-yara search <pattern>

Network Operations

# Connect to remote host
python-icap-yara connect <host>:<port>

# Listen on specific port
python-icap-yara listen --port <port>

# Send data to target
python-icap-yara send --target <host> --data "<data>"

# Receive data from source
python-icap-yara receive --source <host>

# Test connectivity
python-icap-yara ping <host>

# Scan network range
python-icap-yara scan <network>

# Monitor network traffic
python-icap-yara monitor --interface <interface>

# Proxy connections
python-icap-yara proxy --listen <port> --target <host>:<port>

Process Management

# Start background process
python-icap-yara start --daemon

# Stop running process
python-icap-yara stop --force

# Restart with new configuration
python-icap-yara restart --config <file>

# Check process status
python-icap-yara status --verbose

# Monitor process performance
python-icap-yara monitor --metrics

# Kill all processes
python-icap-yara killall

# Show running processes
python-icap-yara ps

# Manage process priority
python-icap-yara priority --pid <pid> --level <level>

Security Features

Authentication

# Login with username/password
python-icap-yara login --user <username>

# Login with API key
python-icap-yara login --api-key <key>

# Login with certificate
python-icap-yara login --cert <cert_file>

# Logout current session
python-icap-yara logout

# Change password
python-icap-yara passwd

# Generate new API key
python-icap-yara generate-key --name <key_name>

# List active sessions
python-icap-yara sessions

# Revoke session
python-icap-yara revoke --session <session_id>

Encryption

# Encrypt file
python-icap-yara encrypt --input <file> --output <encrypted_file>

# Decrypt file
python-icap-yara decrypt --input <encrypted_file> --output <file>

# Generate encryption key
python-icap-yara keygen --type <type> --size <size>

# Sign file
python-icap-yara sign --input <file> --key <private_key>

# Verify signature
python-icap-yara verify --input <file> --signature <sig_file>

# Hash file
python-icap-yara hash --algorithm <algo> --input <file>

# Generate certificate
python-icap-yara cert generate --name <name> --days <days>

# Verify certificate
python-icap-yara cert verify --cert <cert_file>

Monitoring and Logging

System Monitoring

# Monitor system resources
python-icap-yara monitor --system

# Monitor specific process
python-icap-yara monitor --pid <pid>

# Monitor network activity
python-icap-yara monitor --network

# Monitor file changes
python-icap-yara monitor --files <directory>

# Real-time monitoring
python-icap-yara monitor --real-time --interval 1

# Generate monitoring report
python-icap-yara report --type monitoring --output <file>

# Set monitoring alerts
python-icap-yara alert --threshold <value> --action <action>

# View monitoring history
python-icap-yara history --type monitoring

Logging

# View logs
python-icap-yara logs

# View logs with filter
python-icap-yara logs --filter <pattern>

# Follow logs in real-time
python-icap-yara logs --follow

# Set log level
python-icap-yara logs --level <level>

# Rotate logs
python-icap-yara logs --rotate

# Export logs
python-icap-yara logs --export <file>

# Clear logs
python-icap-yara logs --clear

# Archive logs
python-icap-yara logs --archive <archive_file>

Troubleshooting

Common Issues

Issue: Command not found

# Check if python-icap-yara is installed
which python-icap-yara
python-icap-yara --version

# Check PATH variable
echo $PATH

# Reinstall if necessary
sudo apt reinstall python-icap-yara
# or
brew reinstall python-icap-yara

Issue: Permission denied

# Run with elevated privileges
sudo python-icap-yara <command>

# Check file permissions
ls -la $(which python-icap-yara)

# Fix permissions
chmod +x /usr/local/bin/python-icap-yara

# Check ownership
sudo chown $USER:$USER /usr/local/bin/python-icap-yara

Issue: Configuration errors

# Validate configuration
python-icap-yara config validate

# Reset to default configuration
python-icap-yara config reset

# Check configuration file location
python-icap-yara config show --file

# Backup current configuration
python-icap-yara config export > backup.conf

# Restore from backup
python-icap-yara config import backup.conf

Issue: Service not starting

# Check service status
python-icap-yara status --detailed

# Check system logs
journalctl -u python-icap-yara

# Start in debug mode
python-icap-yara start --debug

# Check port availability
netstat -tulpn|grep <port>

# Kill conflicting processes
python-icap-yara killall --force

Debug Commands

Command	Description
python-icap-yara --debug	Enable debug output
python-icap-yara --verbose	Enable verbose logging
python-icap-yara --trace	Enable trace logging
python-icap-yara test	Run built-in tests
python-icap-yara doctor	Run system health check
python-icap-yara diagnose	Generate diagnostic report
python-icap-yara benchmark	Run performance benchmarks
python-icap-yara validate	Validate installation and configuration

Performance Optimization

Resource Management

# Set memory limit
python-icap-yara --max-memory 1G <command>

# Set CPU limit
python-icap-yara --max-cpu 2 <command>

# Enable caching
python-icap-yara --cache-enabled <command>

# Set cache size
python-icap-yara --cache-size 100M <command>

# Clear cache
python-icap-yara cache clear

# Show cache statistics
python-icap-yara cache stats

# Optimize performance
python-icap-yara optimize --profile <profile>

# Show performance metrics
python-icap-yara metrics

Parallel Processing

# Enable parallel processing
python-icap-yara --parallel <command>

# Set number of workers
python-icap-yara --workers 4 <command>

# Process in batches
python-icap-yara --batch-size 100 <command>

# Queue management
python-icap-yara queue add <item>
python-icap-yara queue process
python-icap-yara queue status
python-icap-yara queue clear

Integration

Scripting

#!/bin/bash
# Example script using python-icap-yara

set -euo pipefail

# Configuration
CONFIG_FILE="config.yaml"
LOG_FILE="python-icap-yara.log"

# Check if python-icap-yara is available
if ! command -v python-icap-yara &> /dev/null; then
    echo "Error: python-icap-yara is not installed" >&2
    exit 1
fi

# Function to log messages
log() \\\\{
    echo "$(date '+%Y-%m-%d %H:%M:%S') - $1"|tee -a "$LOG_FILE"
\\\\}

# Main operation
main() \\\\{
    log "Starting python-icap-yara operation"

    if python-icap-yara --config "$CONFIG_FILE" run; then
        log "Operation completed successfully"
        exit 0
    else
        log "Operation failed with exit code $?"
        exit 1
    fi
\\\\}

# Cleanup function
cleanup() \\\\{
    log "Cleaning up"
    python-icap-yara cleanup
\\\\}

# Set trap for cleanup
trap cleanup EXIT

# Run main function
main "$@"

API Integration

#!/usr/bin/env python3
"""
Python wrapper for the tool
"""

import subprocess
import json
import logging
from pathlib import Path
from typing import Dict, List, Optional

class ToolWrapper:
    def __init__(self, config_file: Optional[str] = None):
        self.config_file = config_file
        self.logger = logging.getLogger(__name__)

    def run_command(self, args: List[str]) -> Dict:
        """Run command and return parsed output"""
        cmd = ['tool_name']

        if self.config_file:
            cmd.extend(['--config', self.config_file])

        cmd.extend(args)

        try:
            result = subprocess.run(
                cmd,
                capture_output=True,
                text=True,
                check=True
            )
            return \\\\{'stdout': result.stdout, 'stderr': result.stderr\\\\}
        except subprocess.CalledProcessError as e:
            self.logger.error(f"Command failed: \\\\{e\\\\}")
            raise

    def status(self) -> Dict:
        """Get current status"""
        return self.run_command(['status'])

    def start(self) -> Dict:
        """Start service"""
        return self.run_command(['start'])

    def stop(self) -> Dict:
        """Stop service"""
        return self.run_command(['stop'])

# Example usage
if __name__ == "__main__":
    wrapper = ToolWrapper()
    status = wrapper.status()
    print(json.dumps(status, indent=2))

Environment Variables

Variable	Description	Default
PYTHON-ICAP-YARA_CONFIG	Configuration file path	~/.python-icap-yara/config.yaml
PYTHON-ICAP-YARA_HOME	Home directory	~/.python-icap-yara
PYTHON-ICAP-YARA_LOG_LEVEL	Logging level	INFO
PYTHON-ICAP-YARA_LOG_FILE	Log file path	~/.python-icap-yara/logs/python-icap-yara.log
PYTHON-ICAP-YARA_CACHE_DIR	Cache directory	~/.python-icap-yara/cache
PYTHON-ICAP-YARA_DATA_DIR	Data directory	~/.python-icap-yara/data
PYTHON-ICAP-YARA_TIMEOUT	Default timeout	30s
PYTHON-ICAP-YARA_MAX_WORKERS	Maximum workers	4

Configuration File

# ~/.python-icap-yara/config.yaml
version: "1.0"

# General settings
settings:
  debug: false
  verbose: false
  log_level: "INFO"
  log_file: "~/.python-icap-yara/logs/python-icap-yara.log"
  timeout: 30
  max_workers: 4

# Network configuration
network:
  host: "localhost"
  port: 8080
  ssl: true
  timeout: 30
  retries: 3

# Security settings
security:
  auth_required: true
  api_key: ""
  encryption: "AES256"
  verify_ssl: true

# Performance settings
performance:
  cache_enabled: true
  cache_size: "100M"
  cache_dir: "~/.python-icap-yara/cache"
  max_memory: "1G"

# Monitoring settings
monitoring:
  enabled: true
  interval: 60
  metrics_enabled: true
  alerts_enabled: true

Examples

Basic Workflow

# 1. Initialize python-icap-yara
python-icap-yara init

# 2. Configure basic settings
python-icap-yara config set host example.com
python-icap-yara config set port 8080

# 3. Start service
python-icap-yara start

# 4. Check status
python-icap-yara status

# 5. Perform operations
python-icap-yara run --target example.com

# 6. View results
python-icap-yara results

# 7. Stop service
python-icap-yara stop

Advanced Workflow

# Comprehensive operation with monitoring
python-icap-yara run \
  --config production.yaml \
  --parallel \
  --workers 8 \
  --verbose \
  --timeout 300 \
  --output json \
  --log-file operation.log

# Monitor in real-time
python-icap-yara monitor --real-time --interval 5

# Generate report
python-icap-yara report --type comprehensive --output report.html

Automation Example

#!/bin/bash
# Automated python-icap-yara workflow

# Configuration
TARGETS_FILE="targets.txt"
RESULTS_DIR="results/$(date +%Y-%m-%d)"
CONFIG_FILE="automation.yaml"

# Create results directory
mkdir -p "$RESULTS_DIR"

# Process each target
while IFS= read -r target; do
    echo "Processing $target..."

    python-icap-yara \
        --config "$CONFIG_FILE" \
        --output json \
        --output-file "$RESULTS_DIR/$\\\\{target\\\\}.json" \
        run "$target"

done < "$TARGETS_FILE"

# Generate summary report
python-icap-yara report summary \
    --input "$RESULTS_DIR/*.json" \
    --output "$RESULTS_DIR/summary.html"

Best Practices

Security

• Always verify checksums when downloading binaries
• Use strong authentication methods (API keys, certificates)
• Regularly update to the latest version
• Follow principle of least privilege
• Enable audit logging for compliance
• Use encrypted connections when possible
• Validate all inputs and configurations
• Implement proper access controls

Performance

• Use appropriate resource limits for your environment
• Monitor system performance regularly
• Optimize configuration for your use case
• Use parallel processing when beneficial
• Implement proper caching strategies
• Regular maintenance and cleanup
• Profile performance bottlenecks
• Use efficient algorithms and data structures

Operational

• Maintain comprehensive documentation
• Implement proper backup strategies
• Use version control for configurations
• Monitor and alert on critical metrics
• Implement proper error handling
• Use automation for repetitive tasks
• Regular security audits and updates
• Plan for disaster recovery

Development

• Follow coding standards and conventions
• Write comprehensive tests
• Use continuous integration/deployment
• Implement proper logging and monitoring
• Document APIs and interfaces
• Use version control effectively
• Review code regularly
• Maintain backward compatibility

Resources

Official Documentation

• Official Website
• Documentation
• API Reference
• Installation Guide
• Configuration Reference

Community Resources

• GitHub Repository
• Issue Tracker
• Community Forum
• Discord Server
• Reddit Community
• Stack Overflow

Learning Resources

• Getting Started Guide
• Tutorial Series
• Best Practices Guide
• Video Tutorials
• Training Courses
• Certification Program

Related Tools

• Git - Complementary functionality
• Docker - Alternative solution
• Kubernetes - Integration partner

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Last updated: 2025-07-06|Edit on GitHub