Security Vulnerability Clustermap

import matplotlib.pyplot as plt
import seaborn as sns
import pandas as pd
import numpy as np
from matplotlib.colors import LinearSegmentedColormap

np.random.seed(456)

threats = ['SQL Injection', 'XSS', 'CSRF', 'DDoS', 'Phishing', 
           'Malware', 'Ransomware', 'MitM', 'Brute Force', 'Zero-Day']
systems = ['Web App', 'API', 'Database', 'Network', 'Email', 'Endpoint', 'Cloud', 'IoT']

data = np.random.rand(10, 8) * 5
data[0, 2] = 9
data[1, 0] = 8
data[3, 3] = 9
data[6, 5] = 8

df = pd.DataFrame(data, index=threats, columns=systems)

neon_cmap = LinearSegmentedColormap.from_list('threat', ['#0a0a0f', '#4927F5', '#F5B027', '#F5276C', '#C82909'])

g = sns.clustermap(df, cmap=neon_cmap, vmin=0, vmax=10,
                   method='average', metric='euclidean',
                   linewidths=0.5, linecolor='#1a1a2e',
                   figsize=(9, 8), dendrogram_ratio=(0.12, 0.12),
                   cbar_pos=(0.01, 0.08, 0.008, 0.12),
                   annot=True, fmt='.1f', annot_kws={'size': 7, 'color': 'white'},
                   tree_kws={'linewidths': 1.5, 'colors': '#6CF527'})

g.fig.patch.set_facecolor('#0a0a0f')
g.ax_heatmap.set_facecolor('#0a0a0f')
g.ax_heatmap.tick_params(colors='white', labelsize=8)
g.ax_row_dendrogram.set_facecolor('#0a0a0f')
g.ax_col_dendrogram.set_facecolor('#0a0a0f')
g.cax.tick_params(colors='white', labelsize=7)

g.fig.suptitle('Security Risk Assessment', color='white', fontsize=13, fontweight='bold', y=1.02)
plt.show()