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name: image-generation description: | Create diagrams, charts, and visual assets for security documentation. Generate network diagrams, architecture visuals, and data visualizations. Use when creating visual content for reports or presentations. license: Apache-2.0 compatibility: |

• Python 3.9+
• Required packages: pillow, matplotlib, graphviz metadata: author: SherifEldeeb version: "1.0.0" category: baseline

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Image Generation Skill

Create diagrams, charts, and visual assets for security documentation with support for network diagrams, data visualizations, and flowcharts.

Capabilities

• Diagrams: Generate network topology and architecture diagrams
• Charts: Create data visualizations (bar, pie, line, heatmaps)
• Flowcharts: Build process and workflow diagrams
• Risk Matrices: Generate risk assessment visualizations
• Timelines: Create incident and event timelines
• Export: Save to PNG, SVG, and PDF formats

Quick Start

import matplotlib.pyplot as plt

# Create a simple bar chart
severities = ['Critical', 'High', 'Medium', 'Low']
counts = [3, 8, 15, 22]

plt.figure(figsize=(10, 6))
plt.bar(severities, counts, color=['#e74c3c', '#e67e22', '#f1c40f', '#3498db'])
plt.title('Findings by Severity')
plt.savefig('severity_chart.png', dpi=150)

Usage

Bar Charts

Create bar charts for comparisons.

Example:

import matplotlib.pyplot as plt
from typing import Dict

def create_severity_chart(data: Dict[str, int], output_path: str = 'chart.png'):
    """Create a severity distribution bar chart."""
    colors = {
        'Critical': '#e74c3c', 'High': '#e67e22',
        'Medium': '#f1c40f', 'Low': '#3498db'
    }

    severities = list(data.keys())
    counts = list(data.values())
    bar_colors = [colors.get(s, '#333') for s in severities]

    plt.figure(figsize=(10, 6))
    plt.bar(severities, counts, color=bar_colors)
    plt.title('Findings by Severity', fontsize=14, fontweight='bold')
    plt.savefig(output_path, dpi=150, bbox_inches='tight')
    plt.close()

# Usage
create_severity_chart({'Critical': 3, 'High': 8, 'Medium': 15, 'Low': 22})

Network Diagrams

Create network topology diagrams using Graphviz.

Example:

from graphviz import Digraph

def create_network_diagram(nodes: list, edges: list, output_path: str = 'network'):
    """Create a network topology diagram."""
    dot = Digraph()
    dot.attr(rankdir='TB')

    shapes = {'firewall': 'box3d', 'server': 'box', 'database': 'cylinder'}

    for node in nodes:
        dot.node(node['id'], node['label'],
                shape=shapes.get(node.get('type', 'server'), 'box'),
                style='filled', fillcolor=node.get('color', 'lightblue'))

    for edge in edges:
        dot.edge(edge['from'], edge['to'], label=edge.get('label', ''))

    dot.render(output_path, format='png', cleanup=True)

# Usage
nodes = [
    {'id': 'fw', 'label': 'Firewall', 'type': 'firewall', 'color': 'lightcoral'},
    {'id': 'web', 'label': 'Web Server', 'type': 'server'},
    {'id': 'db', 'label': 'Database', 'type': 'database'}
]
edges = [{'from': 'fw', 'to': 'web'}, {'from': 'web', 'to': 'db'}]
create_network_diagram(nodes, edges)

Flowcharts

Create process flowcharts.

Example:

from graphviz import Digraph

def create_flowchart(steps: list, output_path: str = 'flowchart'):
    """Create a process flowchart."""
    dot = Digraph()
    dot.attr(rankdir='TB')

    shapes = {'start': 'ellipse', 'end': 'ellipse',
              'process': 'box', 'decision': 'diamond'}
    colors = {'start': 'lightgreen', 'end': 'lightcoral',
              'process': 'lightblue', 'decision': 'lightyellow'}

    for step in steps:
        dot.node(step['id'], step['label'],
                shape=shapes.get(step.get('type', 'process'), 'box'),
                style='filled',
                fillcolor=colors.get(step.get('type', 'process'), 'white'))

        if 'next' in step:
            for n in (step['next'] if isinstance(step['next'], list) else [step['next']]):
                if isinstance(n, dict):
                    dot.edge(step['id'], n['to'], label=n.get('label', ''))
                else:
                    dot.edge(step['id'], n)

    dot.render(output_path, format='png', cleanup=True)

Risk Heatmaps

Create risk assessment heatmaps.

Example:

import matplotlib.pyplot as plt
import numpy as np

def create_risk_heatmap(data: list, x_labels: list, y_labels: list, output_path: str):
    """Create a risk assessment heatmap."""
    fig, ax = plt.subplots(figsize=(10, 8))
    im = ax.imshow(data, cmap='RdYlGn_r')

    ax.set_xticks(np.arange(len(x_labels)))
    ax.set_yticks(np.arange(len(y_labels)))
    ax.set_xticklabels(x_labels)
    ax.set_yticklabels(y_labels)

    for i in range(len(y_labels)):
        for j in range(len(x_labels)):
            ax.text(j, i, data[i][j], ha='center', va='center',
                   color='white' if data[i][j] > 5 else 'black')

    ax.set_title('Risk Matrix')
    plt.colorbar(im)
    plt.savefig(output_path, dpi=150)
    plt.close()

Configuration

Environment Variables

Variable	Description	Required	Default
IMAGE_OUTPUT_DIR	Output directory	No	./output
IMAGE_DPI	Default DPI	No	150

Limitations

• Interactive: Static images only
• 3D: Limited 3D support
• Graphviz: Required for diagrams

Troubleshooting

Graphviz Not Found

Install the system package:

apt-get install graphviz  # Ubuntu
brew install graphviz      # macOS

Related Skills

• pptx: Embed images in presentations
• docx: Include visuals in reports
• pdf: Add charts to PDF reports

References

• Detailed API Reference
• Matplotlib Documentation
• Graphviz Documentation