Cybersecurity Threat Score KDE

import numpy as np
import matplotlib.pyplot as plt
from scipy.stats import gaussian_kde

np.random.seed(654)
BG_COLOR = '#0d1117'
TEXT_COLOR = 'white'

# Threat scores (0-100)
malware = np.random.beta(8, 2, 400) * 100
phishing = np.random.beta(5, 3, 400) * 100
ddos = np.random.beta(6, 2.5, 400) * 100

fig, ax = plt.subplots(figsize=(10, 6), facecolor=BG_COLOR)
ax.set_facecolor(BG_COLOR)

x_range = np.linspace(0, 100, 500)

for data, color, label in [(malware, '#C82909', 'Malware'), 
                            (phishing, '#F5B027', 'Phishing'),
                            (ddos, '#4927F5', 'DDoS')]:
    kde = gaussian_kde(data)
    density = kde(x_range)
    ax.plot(x_range, density, color=color, linewidth=2.5, label=label)
    ax.fill_between(x_range, density, alpha=0.3, color=color)

ax.axvline(70, color='#ef4444', linestyle='--', alpha=0.8, linewidth=2)
ax.text(72, ax.get_ylim()[1]*0.8, 'Critical', color='#ef4444', fontsize=10)

ax.set_xlabel('Threat Severity Score', fontsize=12, color=TEXT_COLOR, fontweight='500')
ax.set_ylabel('Density', fontsize=12, color=TEXT_COLOR, fontweight='500')
ax.set_title('Cybersecurity Threat Score Distribution', fontsize=14, color=TEXT_COLOR, fontweight='bold', pad=15)

ax.tick_params(colors='#888888', labelsize=10)
for spine in ax.spines.values():
    spine.set_color('#333333')
ax.legend(facecolor=BG_COLOR, edgecolor='#333333', labelcolor=TEXT_COLOR, fontsize=10)

plt.tight_layout()
plt.show()