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