:; cat << 'EOF' > /root/CISA-Vulnerability-Regulatory-Compliance-Tracker/SEC-FTC-FCC/app.py
import streamlit as st
import numpy as np
import plotly.graph_objects as go
import plotly.express as px

st.set_page_config(page_title="CISA SEC/FTC Quantum & Geodesic Tracker", layout="wide")

st.title("CISA Vulnerability & Regulatory Compliance Tracker")
st.subheader("Module: FractalPlanckQuantum & Spacetime Dynamics")

# Sidebar Controls
st.sidebar.header("Quantum & Field Parameters")
n_scale = st.sidebar.slider("Scale Order (n)", 0.0, 5.0, 1.0, 0.1)
d_fractal = st.sidebar.slider("Fractal Dimension (D_f)", 1.0, 3.0, 1.618, 0.05)
mass_curvature = st.sidebar.slider("Field Mass Curvature (M)", 0.0, 10.0, 2.5, 0.5)

# Invariant Calculation
omega_n = np.exp(d_fractal - 1) * ((2 * np.pi) ** (-n_scale))
st.sidebar.metric("Calculated Invariant (Omega_n)", f"{omega_n:.6f}")

# Multi-Tab Layout
tab_regulatory, tab_geodesic = st.tabs(["SEC/FTC Regulatory Risk", "Spacetime Geodesic Vector"])

with tab_regulatory:
    st.markdown("### SEC / FTC / FCC Risk Assessment (Quantum Scaled)")
    st.latex(r"\Omega_n(D_f) = h_0 \left(\frac{l}{l_P}\right)^{D_f - 1} (2\pi)^{-n}")
    
    base_cvss = [9.8, 8.5, 7.2, 6.1, 4.3]
    cve_ids = ["CVE-2026-0012", "CVE-2026-1194", "CVE-2026-3301", "CVE-2026-4410", "CVE-2026-8890"]
    adjusted_risk = [min(10.0, score * (1 + omega_n)) for score in base_cvss]

    fig_bar = px.bar(
        x=cve_ids, 
        y=adjusted_risk, 
        labels={'x': 'Vulnerability ID', 'y': 'Quantum-Adjusted Impact Score'},
        title=f"Severity Matrix Scaled by Omega_n = {omega_n:.4f}",
        color=adjusted_risk,
        color_continuous_scale="Reds"
    )
    st.plotly_chart(fig_bar, use_container_width=True)

with tab_geodesic:
    st.markdown("### Physical Geodesic vs. Ideal Vector Trajectory")
    st.write("Visualizing real trajectory curvature under gravitational lensing and scale invariant phase shifts.")
    
    t = np.linspace(0, 12, 300)
    x = t
    y = mass_curvature * np.sin(t / (1 + omega_n)) * np.exp(-0.08 * t)
    z = mass_curvature * np.cos(t / (1 + omega_n)) * np.exp(-0.08 * t)

    fig_geo = go.Figure()
    fig_geo.add_trace(go.Scatter3d(
        x=x, y=y, z=z,
        mode='lines',
        name='Physical Path (Curved Geodesic)',
        line=dict(color=t, colorscale='Plasma', width=6)
    ))
    fig_geo.add_trace(go.Scatter3d(
        x=x, y=np.zeros_like(x), z=np.zeros_like(x),
        mode='lines',
        name='Ideal Flat Vector (Reference)',
        line=dict(color='white', width=3, dash='dash')
    ))

    fig_geo.update_layout(
        title="Spacetime Trajectory Perturbation",
        scene=dict(
            xaxis_title="Propagation (X)",
            yaxis_title="Transverse Deflection (Y)",
            zaxis_title="Orthogonal Shift (Z)"
        ),
        margin=dict(l=0, r=0, b=0, t=40)
    )
    st.plotly_chart(fig_geo, use_container_width=True)
EOF

kill -9 $(pgrep -f "streamlit") 2>/dev/null
PYTHONUNBUFFERED=1 nohup /root/venv/bin/python3 -m streamlit run /root/CISA-Vulnerability-Regulatory-Compliance-Tracker/SEC-FTC-FCC/app.py --server.port 8501 --server.address 0.0.0.0 --server.headless true > streamlit.log 2>&1 &
sleep 4
ps aux | grep streamlit && cat streamlit.log