AI

core/admin.py

@@ -1,3 +1,12 @@
 from django.contrib import admin
 
-# Register your models here.
+from .models import ThreatScan
+
+
+@admin.register(ThreatScan)
+class ThreatScanAdmin(admin.ModelAdmin):
+    list_display = ("id", "scan_type", "risk_score", "risk_level", "target_preview", "model_version", "created_at")
+    list_filter = ("scan_type", "risk_level", "model_version", "created_at")
+    search_fields = ("target_preview", "content_hash", "verdict")
+    readonly_fields = ("created_at", "content_hash")
+    ordering = ("-created_at",)

core/forms.py

@@ -0,0 +1,49 @@
+from django import forms
+from django.core.validators import URLValidator
+from django.core.exceptions import ValidationError
+
+from .models import ThreatScan
+
+
+class ThreatScanForm(forms.Form):
+    scan_type = forms.ChoiceField(
+        choices=ThreatScan.ScanType.choices,
+        widget=forms.RadioSelect,
+        initial=ThreatScan.ScanType.URL,
+        label="What do you want to scan?",
+    )
+    content = forms.CharField(
+        label="URL, email, or message",
+        max_length=5000,
+        widget=forms.Textarea(attrs={
+            "rows": 6,
+            "placeholder": "Paste a suspicious URL, email, SMS, or chat message. Raw text is analyzed in-memory and not stored.",
+        }),
+    )
+    store_metadata = forms.BooleanField(
+        required=False,
+        initial=True,
+        label="Save privacy-safe metadata for my dashboard",
+        help_text="Only a short sanitized preview, hash, score, and explanation are stored — not the raw submission.",
+    )
+
+    def clean_content(self):
+        content = self.cleaned_data["content"].strip()
+        if len(content) < 6:
+            raise ValidationError("Please enter enough text to analyze.")
+        return content
+
+    def clean(self):
+        cleaned = super().clean()
+        scan_type = cleaned.get("scan_type")
+        content = cleaned.get("content")
+        if scan_type == ThreatScan.ScanType.URL and content:
+            candidate = content.strip()
+            if not candidate.startswith(("http://", "https://")):
+                candidate = f"https://{candidate}"
+            try:
+                URLValidator()(candidate)
+            except ValidationError as exc:
+                raise ValidationError("Enter a valid URL, or switch the scan type to Email / Message.") from exc
+            cleaned["content"] = candidate
+        return cleaned

core/migrations/0001_initial.py

@@ -0,0 +1,37 @@
+# Generated by Django 5.2.7 on 2026-06-13 09:41
+
+import django.utils.timezone
+from django.db import migrations, models
+
+
+class Migration(migrations.Migration):
+
+    initial = True
+
+    dependencies = [
+    ]
+
+    operations = [
+        migrations.CreateModel(
+            name='ThreatScan',
+            fields=[
+                ('id', models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
+                ('scan_type', models.CharField(choices=[('url', 'URL / Website'), ('message', 'Email / Message')], max_length=20)),
+                ('target_preview', models.CharField(help_text='Sanitized preview only; raw sensitive content is not stored.', max_length=220)),
+                ('content_hash', models.CharField(db_index=True, max_length=64)),
+                ('risk_score', models.PositiveSmallIntegerField(default=0)),
+                ('risk_level', models.CharField(choices=[('low', 'Low'), ('medium', 'Medium'), ('high', 'High'), ('critical', 'Critical')], default='low', max_length=20)),
+                ('verdict', models.CharField(max_length=160)),
+                ('explanation', models.TextField()),
+                ('indicators', models.JSONField(blank=True, default=list)),
+                ('recommended_actions', models.JSONField(blank=True, default=list)),
+                ('model_version', models.CharField(default='heuristic-nlp-v1', max_length=40)),
+                ('store_metadata', models.BooleanField(default=True)),
+                ('created_at', models.DateTimeField(db_index=True, default=django.utils.timezone.now)),
+            ],
+            options={
+                'ordering': ['-created_at'],
+                'indexes': [models.Index(fields=['scan_type', 'risk_level'], name='core_threat_scan_ty_620347_idx'), models.Index(fields=['created_at'], name='core_threat_created_e17dbf_idx')],
+            },
+        ),
+    ]

core/models.py

@@ -1,3 +1,46 @@
 from django.db import models
+from django.utils import timezone
 
-# Create your models here.
+
+class ThreatScan(models.Model):
+    class ScanType(models.TextChoices):
+        URL = "url", "URL / Website"
+        MESSAGE = "message", "Email / Message"
+
+    class RiskLevel(models.TextChoices):
+        LOW = "low", "Low"
+        MEDIUM = "medium", "Medium"
+        HIGH = "high", "High"
+        CRITICAL = "critical", "Critical"
+
+    scan_type = models.CharField(max_length=20, choices=ScanType.choices)
+    target_preview = models.CharField(max_length=220, help_text="Sanitized preview only; raw sensitive content is not stored.")
+    content_hash = models.CharField(max_length=64, db_index=True)
+    risk_score = models.PositiveSmallIntegerField(default=0)
+    risk_level = models.CharField(max_length=20, choices=RiskLevel.choices, default=RiskLevel.LOW)
+    verdict = models.CharField(max_length=160)
+    explanation = models.TextField()
+    indicators = models.JSONField(default=list, blank=True)
+    recommended_actions = models.JSONField(default=list, blank=True)
+    model_version = models.CharField(max_length=40, default="heuristic-nlp-v1")
+    store_metadata = models.BooleanField(default=True)
+    created_at = models.DateTimeField(default=timezone.now, db_index=True)
+
+    class Meta:
+        ordering = ["-created_at"]
+        indexes = [
+            models.Index(fields=["scan_type", "risk_level"]),
+            models.Index(fields=["created_at"]),
+        ]
+
+    def __str__(self):
+        return f"{self.get_scan_type_display()} · {self.risk_score}/100 · {self.target_preview[:50]}"
+
+    @property
+    def risk_badge_class(self):
+        return {
+            self.RiskLevel.LOW: "success",
+            self.RiskLevel.MEDIUM: "warning",
+            self.RiskLevel.HIGH: "danger",
+            self.RiskLevel.CRITICAL: "critical",
+        }.get(self.risk_level, "secondary")

core/scanner.py

@@ -0,0 +1,168 @@
+import hashlib
+import math
+import re
+from dataclasses import dataclass
+from urllib.parse import urlparse
+
+from .models import ThreatScan
+
+SUSPICIOUS_TLDS = {"zip", "mov", "click", "country", "gq", "tk", "ml", "cf"}
+BRAND_TERMS = {"paypal", "microsoft", "google", "apple", "amazon", "bank", "chase", "wellsfargo", "office365"}
+URGENCY_TERMS = {"urgent", "immediately", "verify", "suspended", "locked", "limited", "expire", "password", "invoice", "wire", "gift card", "crypto"}
+CREDENTIAL_TERMS = {"login", "signin", "sign in", "password", "2fa", "otp", "account", "credentials", "ssn"}
+URL_SHORTENERS = {"bit.ly", "tinyurl.com", "t.co", "goo.gl", "ow.ly", "is.gd", "buff.ly", "cutt.ly"}
+
+
+@dataclass
+class ScanResult:
+    risk_score: int
+    risk_level: str
+    verdict: str
+    explanation: str
+    indicators: list[dict]
+    recommended_actions: list[str]
+    target_preview: str
+    content_hash: str
+
+
+def _hash_content(content: str) -> str:
+    return hashlib.sha256(content.encode("utf-8")).hexdigest()
+
+
+def _preview(content: str, limit: int = 180) -> str:
+    clean = re.sub(r"\s+", " ", content).strip()
+    clean = re.sub(r"([A-Za-z0-9._%+-])[A-Za-z0-9._%+-]*(@)", r"
•••", clean)
+    return clean[:limit] + ("…" if len(clean) > limit else "")
+
+
+def _add(indicators: list[dict], label: str, weight: int, detail: str):
+    indicators.append({"label": label, "weight": weight, "detail": detail})
+
+
+def _risk_level(score: int) -> str:
+    if score >= 85:
+        return ThreatScan.RiskLevel.CRITICAL
+    if score >= 65:
+        return ThreatScan.RiskLevel.HIGH
+    if score >= 35:
+        return ThreatScan.RiskLevel.MEDIUM
+    return ThreatScan.RiskLevel.LOW
+
+
+def _verdict(score: int) -> str:
+    if score >= 85:
+        return "Likely malicious — isolate and do not interact"
+    if score >= 65:
+        return "High-risk suspicious content"
+    if score >= 35:
+        return "Needs review before trusting"
+    return "Low risk based on current signals"
+
+
+def _actions(level: str) -> list[str]:
+    if level in {ThreatScan.RiskLevel.CRITICAL, ThreatScan.RiskLevel.HIGH}:
+        return [
+            "Do not click links, download attachments, or enter credentials.",
+            "Report this item to your security team or service provider.",
+            "If you already interacted, rotate passwords and review account activity.",
+        ]
+    if level == ThreatScan.RiskLevel.MEDIUM:
+        return [
+            "Verify the sender/domain through an independent channel.",
+            "Hover or inspect links before opening them.",
+            "Avoid sharing credentials or payment details until confirmed.",
+        ]
+    return [
+        "No strong malicious signals were found, but continue to verify unexpected requests.",
+        "Keep software and browser protections enabled.",
+    ]
+
+
+def scan_content(scan_type: str, content: str) -> ScanResult:
+    indicators: list[dict] = []
+    score = 5
+    lowered = content.lower()
+
+    if scan_type == ThreatScan.ScanType.URL:
+        parsed = urlparse(content)
+        host = (parsed.netloc or parsed.path).lower().split(":")[0]
+        path = parsed.path.lower()
+        labels = [part for part in host.split(".") if part]
+        tld = labels[-1] if labels else ""
+
+        if parsed.scheme == "http":
+            score += 18
+            _add(indicators, "Unencrypted HTTP", 18, "The URL uses http:// instead of https://.")
+        if host.replace(".", "").isdigit() or re.match(r"^\d+\.\d+\.\d+\.\d+$", host):
+            score += 22
+            _add(indicators, "IP address host", 22, "Phishing links often hide behind raw IP addresses.")
+        if host in URL_SHORTENERS:
+            score += 20
+            _add(indicators, "Shortened URL", 20, "Shorteners hide the final destination until opened.")
+        if tld in SUSPICIOUS_TLDS:
+            score += 14
+            _add(indicators, "Higher-risk TLD", 14, f".{tld} domains are frequently abused in commodity phishing.")
+        if len(host) > 38 or len(content) > 120:
+            score += 10
+            _add(indicators, "Long destination", 10, "Very long hosts/URLs can hide deceptive tracking or redirect chains.")
+        if "@" in content:
+            score += 18
+            _add(indicators, "@ symbol in URL", 18, "The @ character can disguise the actual destination host.")
+        if sum(1 for ch in host if ch == "-") >= 2:
+            score += 8
+            _add(indicators, "Hyphen-heavy domain", 8, "Multiple hyphens can imitate legitimate brand domains.")
+        matched_brands = [brand for brand in BRAND_TERMS if brand in host and not host.endswith(f"{brand}.com")]
+        if matched_brands:
+            score += 16
+            _add(indicators, "Brand impersonation pattern", 16, f"The host contains sensitive brand terms: {', '.join(matched_brands[:3])}.")
+        if any(term in path for term in CREDENTIAL_TERMS):
+            score += 12
+            _add(indicators, "Credential-themed path", 12, "The path references login, password, or account actions.")
+    else:
+        urgent_hits = [term for term in URGENCY_TERMS if term in lowered]
+        credential_hits = [term for term in CREDENTIAL_TERMS if term in lowered]
+        money_hits = re.findall(r"\$\s?\d+|wire transfer|gift card|bitcoin|crypto", lowered)
+        url_count = len(re.findall(r"https?://|www\.", lowered))
+
+        if urgent_hits:
+            weight = min(25, 8 + len(urgent_hits) * 4)
+            score += weight
+            _add(indicators, "Urgency and pressure language", weight, f"Found terms such as {', '.join(urgent_hits[:5])}.")
+        if credential_hits:
+            weight = min(24, 10 + len(credential_hits) * 3)
+            score += weight
+            _add(indicators, "Credential request", weight, f"The message asks about {', '.join(credential_hits[:5])}.")
+        if money_hits:
+            score += 16
+            _add(indicators, "Payment or transfer request", 16, "The message references money movement or irreversible payments.")
+        if url_count:
+            score += min(20, url_count * 7)
+            _add(indicators, "Embedded link", min(20, url_count * 7), f"Detected {url_count} link-like item(s) in the message.")
+        if re.search(r"dear (customer|user|client)|kindly|act now|final notice", lowered):
+            score += 10
+            _add(indicators, "Common scam phrasing", 10, "The wording resembles common phishing templates.")
+        if len(content) < 40 and any(term in lowered for term in ["click", "verify", "login"]):
+            score += 8
+            _add(indicators, "Sparse context", 8, "Short messages with action links are harder to verify safely.")
+
+    # Normalize so a pile-up of weak signals does not instantly max out risk.
+    score = min(100, max(0, round(100 * (1 - math.exp(-score / 85)))))
+    if not indicators:
+        _add(indicators, "No strong threat indicators", 0, "The scanner did not find obvious phishing markers in this sample.")
+
+    level = _risk_level(score)
+    explanation = (
+        "This first MVP uses a local heuristic/NLP-style rules engine designed to be replaced or blended "
+        "with a trained Scikit-learn model. It does not store the raw submission; the dashboard saves only "
+        "a sanitized preview, SHA-256 hash, score, and explanation."
+    )
+    return ScanResult(
+        risk_score=score,
+        risk_level=level,
+        verdict=_verdict(score),
+        explanation=explanation,
+        indicators=sorted(indicators, key=lambda item: item["weight"], reverse=True),
+        recommended_actions=_actions(level),
+        target_preview=_preview(content),
+        content_hash=_hash_content(content),
+    )

core/templates/base.html

@@ -1,11 +1,13 @@
+{% load static %}
 <!DOCTYPE html>
 <html lang="en">
 
 <head>
   <meta charset="UTF-8">
-  <title>{% block title %}Knowledge Base{% endblock %}</title>
+  <meta name="viewport" content="width=device-width, initial-scale=1">
+  <title>{% block title %}{{ project_name|default:"SentinelAI Cyber Assistant" }}{% endblock %}</title>
+  <meta name="description" content="{% block meta_description %}{{ meta_description|default:project_description|default:'Privacy-first AI cybersecurity assistant for phishing and scam risk scoring.' }}{% endblock %}">
   {% if project_description %}
-  <meta name="description" content="{{ project_description }}">
   <meta property="og:description" content="{{ project_description }}">
   <meta property="twitter:description" content="{{ project_description }}">
   {% endif %}
@@ -13,13 +15,45 @@
   <meta property="og:image" content="{{ project_image_url }}">
   <meta property="twitter:image" content="{{ project_image_url }}">
   {% endif %}
-  {% load static %}
+  <link rel="preconnect" href="https://fonts.googleapis.com">
+  <link rel="preconnect" href="https://fonts.gstatic.com" crossorigin>
+  <link href="https://fonts.googleapis.com/css2?family=Inter:wght@400;500;600;700;800&family=Space+Grotesk:wght@600;700&display=swap" rel="stylesheet">
+  <link href="https://cdn.jsdelivr.net/npm/bootstrap@5.3.3/dist/css/bootstrap.min.css" rel="stylesheet">
   <link rel="stylesheet" href="{% static 'css/custom.css' %}?v={{ deployment_timestamp }}">
   {% block head %}{% endblock %}
 </head>
 
 <body>
-  {% block content %}{% endblock %}
+  <a class="skip-link" href="#main-content">Skip to content</a>
+  <nav class="navbar navbar-expand-lg app-nav sticky-top" aria-label="Primary navigation">
+    <div class="container">
+      <a class="navbar-brand d-flex align-items-center gap-2" href="{% url 'home' %}">
+        <span class="brand-mark" aria-hidden="true">◆</span>
+        <span>SentinelAI</span>
+      </a>
+      <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#mainNav" aria-controls="mainNav" aria-expanded="false" aria-label="Toggle navigation">
+        <span class="navbar-toggler-icon"></span>
+      </button>
+      <div class="collapse navbar-collapse" id="mainNav">
+        <ul class="navbar-nav ms-auto align-items-lg-center gap-lg-2">
+          <li class="nav-item"><a class="nav-link" href="{% url 'home' %}#scanner">Scan</a></li>
+          <li class="nav-item"><a class="nav-link" href="{% url 'scan_history' %}">Dashboard</a></li>
+          <li class="nav-item"><a class="nav-link" href="{% url 'home' %}#privacy">Privacy</a></li>
+          <li class="nav-item"><a class="btn btn-sm btn-admin" href="/admin/">Admin</a></li>
+        </ul>
+      </div>
+    </div>
+  </nav>
+  <main id="main-content">
+    {% block content %}{% endblock %}
+  </main>
+  <footer class="site-footer py-4">
+    <div class="container d-flex flex-column flex-md-row justify-content-between gap-2">
+      <span>SentinelAI Cyber Assistant · Explainable risk scoring</span>
+      <span>Privacy-first MVP: raw submissions are analyzed in-memory only.</span>
+    </div>
+  </footer>
+  <script src="https://cdn.jsdelivr.net/npm/bootstrap@5.3.3/dist/js/bootstrap.bundle.min.js" defer></script>
 </body>
 
 </html>

core/templates/core/index.html

@@ -1,145 +1,150 @@
 {% extends "base.html" %}
 
-{% block title %}{{ project_name }}{% endblock %}
+{% block title %}SentinelAI Cyber Assistant — Phishing & Scam Risk Scanner{% endblock %}
-
+{% block meta_description %}Paste a URL, email, or message to receive a privacy-safe 0–100 phishing risk score with clear explanations.{% endblock %}
-{% block head %}
-<link rel="preconnect" href="https://fonts.googleapis.com">
-<link rel="preconnect" href="https://fonts.gstatic.com" crossorigin>
-<link href="https://fonts.googleapis.com/css2?family=Inter:wght@400;700&display=swap" rel="stylesheet">
-<style>
-  :root {
-    --bg-color-start: #6a11cb;
-    --bg-color-end: #2575fc;
-    --text-color: #ffffff;
-    --card-bg-color: rgba(255, 255, 255, 0.01);
-    --card-border-color: rgba(255, 255, 255, 0.1);
-  }
-
-  * {
-    box-sizing: border-box;
-  }
-
-  body {
-    margin: 0;
-    font-family: 'Inter', sans-serif;
-    background: linear-gradient(45deg, var(--bg-color-start), var(--bg-color-end));
-    color: var(--text-color);
-    display: flex;
-    justify-content: center;
-    align-items: center;
-    min-height: 100vh;
-    text-align: center;
-    overflow: hidden;
-    position: relative;
-  }
-
-  body::before {
-    content: '';
-    position: absolute;
-    inset: 0;
-    background-image: url("data:image/svg+xml,<svg xmlns='http://www.w3.org/2000/svg' width='100' height='100' viewBox='0 0 100 100'><path d='M-10 10L110 10M10 -10L10 110' stroke-width='1' stroke='rgba(255,255,255,0.05)'/></svg>");
-    animation: bg-pan 20s linear infinite;
-    z-index: -1;
-  }
-
-  @keyframes bg-pan {
-    0% {
-      background-position: 0% 0%;
-    }
-
-    100% {
-      background-position: 100% 100%;
-    }
-  }
-
-  main {
-    padding: 2rem;
-  }
-
-  .card {
-    background: var(--card-bg-color);
-    border: 1px solid var(--card-border-color);
-    border-radius: 16px;
-    padding: 2.5rem 2rem;
-    backdrop-filter: blur(20px);
-    -webkit-backdrop-filter: blur(20px);
-    box-shadow: 0 12px 36px rgba(0, 0, 0, 0.25);
-  }
-
-  h1 {
-    font-size: clamp(2.2rem, 3vw + 1.2rem, 3.2rem);
-    font-weight: 700;
-    margin: 0 0 1.2rem;
-    letter-spacing: -0.02em;
-  }
-
-  p {
-    margin: 0.5rem 0;
-    font-size: 1.1rem;
-    opacity: 0.92;
-  }
-
-  .loader {
-    margin: 1.5rem auto;
-    width: 56px;
-    height: 56px;
-    border: 4px solid rgba(255, 255, 255, 0.25);
-    border-top-color: #fff;
-    border-radius: 50%;
-    animation: spin 1s linear infinite;
-  }
-
-  @keyframes spin {
-    to {
-      transform: rotate(360deg);
-    }
-  }
-
-  .runtime code {
-    background: rgba(0, 0, 0, 0.25);
-    padding: 0.15rem 0.45rem;
-    border-radius: 4px;
-    font-family: ui-monospace, SFMono-Regular, Menlo, Consolas, monospace;
-  }
-
-  .sr-only {
-    position: absolute;
-    width: 1px;
-    height: 1px;
-    padding: 0;
-    margin: -1px;
-    overflow: hidden;
-    clip: rect(0, 0, 0, 0);
-    border: 0;
-  }
-
-  footer {
-    position: absolute;
-    bottom: 1rem;
-    width: 100%;
-    text-align: center;
-    font-size: 0.85rem;
-    opacity: 0.75;
-  }
-</style>
-{% endblock %}
 
 {% block content %}
-<main>
+<section class="hero-section position-relative overflow-hidden">
-  <div class="card">
+  <div class="orb orb-one" aria-hidden="true"></div>
-    <h1>Analyzing your requirements and generating your app…</h1>
+  <div class="orb orb-two" aria-hidden="true"></div>
-    <div class="loader" role="status" aria-live="polite" aria-label="Applying initial changes">
+  <div class="container position-relative">
-      <span class="sr-only">Loading…</span>
+    <div class="row align-items-center g-5 py-5">
+      <div class="col-lg-6">
+        <span class="eyebrow">Privacy-first cyber defense</span>
+        <h1 class="display-title mt-3">Detect phishing URLs and scam messages before they reach people.</h1>
+        <p class="hero-copy mt-3">SentinelAI gives every submission a 0–100 risk score, explains the strongest signals, and stores only privacy-safe metadata for your dashboard.</p>
+        <div class="d-flex flex-wrap gap-3 mt-4">
+          <a href="#scanner" class="btn btn-primary-neo btn-lg">Run a scan</a>
+          <a href="{% url 'scan_history' %}" class="btn btn-outline-light btn-lg">View dashboard</a>
+        </div>
+        <div class="trust-row mt-4" aria-label="MVP capabilities">
+          <span>URL phishing detection</span>
+          <span>Scam message NLP</span>
+          <span>Explainable AI</span>
+        </div>
+      </div>
+      <div class="col-lg-6">
+        <div class="hero-panel glass-card">
+          <div class="panel-header d-flex justify-content-between align-items-center mb-4">
+            <span class="status-dot"></span>
+            <span class="small text-uppercase letter-spaced">Live risk console</span>
+          </div>
+          <div class="risk-meter mx-auto" aria-label="Average risk score">
+            <span>{{ avg_score }}</span>
+            <small>avg risk</small>
+          </div>
+          <div class="row g-3 mt-4">
+            <div class="col-4"><div class="metric-card"><strong>{{ total_scans }}</strong><span>Scans</span></div></div>
+            <div class="col-4"><div class="metric-card"><strong>{{ high_risk_count }}</strong><span>High risk</span></div></div>
+            <div class="col-4"><div class="metric-card"><strong>v1</strong><span>Model</span></div></div>
+          </div>
+          <div class="signal-list mt-4">
+            <div><span class="signal good"></span>Local in-memory analysis</div>
+            <div><span class="signal warn"></span>False-positive review dashboard</div>
+            <div><span class="signal danger"></span>Threat explanations included</div>
+          </div>
+        </div>
+      </div>
     </div>
-    <p class="hint">AppWizzy AI is collecting your requirements and applying the first changes.</p>
-    <p class="hint">This page will refresh automatically as the plan is implemented.</p>
-    <p class="runtime">
-      Runtime: Django <code>{{ django_version }}</code> · Python <code>{{ python_version }}</code>
-      — UTC <code>{{ current_time|date:"Y-m-d H:i:s" }}</code>
-    </p>
   </div>
-</main>
+</section>
-<footer>
+
-  Page updated: {{ current_time|date:"Y-m-d H:i:s" }} (UTC)
+<section id="scanner" class="section-pad scanner-section">
-</footer>
+  <div class="container">
-{% endblock %}
+    <div class="row g-4 align-items-stretch">
+      <div class="col-lg-7">
+        <div class="surface-card p-4 p-md-5 h-100">
+          <div class="section-kicker">First workflow</div>
+          <h2>Scan a suspicious URL, email, or message</h2>
+          <p class="text-muted-soft">This MVP uses a local heuristic/NLP engine as the safe baseline before adding trained Scikit-learn models and public cybersecurity datasets.</p>
+          <form method="post" action="{% url 'create_scan' %}" class="scan-form mt-4" novalidate>
+            {% csrf_token %}
+            {% if form.non_field_errors %}
+            <div class="alert alert-danger">{{ form.non_field_errors }}</div>
+            {% endif %}
+            <fieldset class="mb-4">
+              <legend class="form-label">{{ form.scan_type.label }}</legend>
+              <div class="scan-choice-grid">
+                {% for radio in form.scan_type %}
+                <label class="scan-choice" for="{{ radio.id_for_label }}">
+                  {{ radio.tag }}
+                  <span>{{ radio.choice_label }}</span>
+                </label>
+                {% endfor %}
+              </div>
+              {% for error in form.scan_type.errors %}<div class="invalid-copy">{{ error }}</div>{% endfor %}
+            </fieldset>
+            <div class="mb-3">
+              <label class="form-label" for="{{ form.content.id_for_label }}">{{ form.content.label }}</label>
+              {{ form.content }}
+              {% for error in form.content.errors %}<div class="invalid-copy">{{ error }}</div>{% endfor %}
+            </div>
+            <div class="form-check metadata-check mb-4">
+              {{ form.store_metadata }}
+              <label class="form-check-label" for="{{ form.store_metadata.id_for_label }}">{{ form.store_metadata.label }}</label>
+              <div class="form-text">{{ form.store_metadata.help_text }}</div>
+            </div>
+            <button type="submit" class="btn btn-primary-neo btn-lg w-100">Analyze risk now</button>
+          </form>
+        </div>
+      </div>
+      <div class="col-lg-5">
+        <div class="surface-card p-4 p-md-5 h-100" id="privacy">
+          <div class="section-kicker">Security posture</div>
+          <h2>Built for sensitive submissions</h2>
+          <div class="privacy-stack mt-4">
+            <article>
+              <span>01</span>
+              <h3>Raw content stays out of storage</h3>
+              <p>Only a sanitized preview, SHA-256 hash, risk score, and explanation are persisted.</p>
+            </article>
+            <article>
+              <span>02</span>
+              <h3>Explainable decisions</h3>
+              <p>Every result lists weighted indicators so users can understand what triggered the score.</p>
+            </article>
+            <article>
+              <span>03</span>
+              <h3>ML-ready pipeline</h3>
+              <p>The scanner interface is ready to blend in trained models, evaluation metrics, and safe updates.</p>
+            </article>
+          </div>
+        </div>
+      </div>
+    </div>
+  </div>
+</section>
+
+<section class="section-pad pt-0">
+  <div class="container">
+    <div class="d-flex flex-column flex-md-row justify-content-between align-items-md-end gap-3 mb-4">
+      <div>
+        <div class="section-kicker">Threat dashboard</div>
+        <h2 class="mb-0">Recent detections</h2>
+      </div>
+      <a href="{% url 'scan_history' %}" class="btn btn-ghost">Open full history</a>
+    </div>
+    {% if recent_scans %}
+    <div class="row g-3">
+      {% for scan in recent_scans %}
+      <div class="col-md-6 col-xl-4">
+        <a class="scan-card" href="{% url 'scan_detail' scan.pk %}">
+          <span class="badge risk-{{ scan.risk_badge_class }}">{{ scan.get_risk_level_display }}</span>
+          <strong>{{ scan.risk_score }}/100</strong>
+          <p>{{ scan.target_preview }}</p>
+          <small>{{ scan.get_scan_type_display }} · {{ scan.created_at|date:"M j, Y H:i" }}</small>
+        </a>
+      </div>
+      {% endfor %}
+    </div>
+    {% else %}
+    <div class="empty-state text-center p-5">
+      <div class="empty-icon" aria-hidden="true">◇</div>
+      <h3>No scans yet</h3>
+      <p>Run your first URL or message scan to populate the dashboard.</p>
+      <a href="#scanner" class="btn btn-primary-neo">Start scanning</a>
+    </div>
+    {% endif %}
+  </div>
+</section>
+{% endblock %}

core/templates/core/scan_detail.html

@@ -0,0 +1,70 @@
+{% extends "base.html" %}
+
+{% block title %}Scan Result #{{ scan.pk }} — SentinelAI{% endblock %}
+{% block meta_description %}Explainable AI cybersecurity result with risk score, flagged indicators, and recommended next actions.{% endblock %}
+
+{% block content %}
+<section class="page-hero section-pad-sm">
+  <div class="container">
+    <div class="d-flex flex-column flex-lg-row justify-content-between gap-4 align-items-lg-end">
+      <div>
+        <span class="eyebrow">Scan confirmation</span>
+        <h1 class="page-title mt-3">{{ scan.verdict }}</h1>
+        <p class="hero-copy">Result created {{ scan.created_at|date:"M j, Y H:i" }} using {{ scan.model_version }}.</p>
+      </div>
+      <a class="btn btn-primary-neo" href="{% url 'home' %}#scanner">Scan another item</a>
+    </div>
+  </div>
+</section>
+<section class="section-pad">
+  <div class="container">
+    <div class="row g-4">
+      <div class="col-lg-5">
+        <div class="surface-card p-4 p-md-5 text-center h-100">
+          <div class="risk-meter detail mx-auto risk-ring-{{ scan.risk_badge_class }}">
+            <span>{{ scan.risk_score }}</span>
+            <small>risk / 100</small>
+          </div>
+          <span class="badge risk-{{ scan.risk_badge_class }} mt-4">{{ scan.get_risk_level_display }} risk</span>
+          <dl class="scan-meta mt-4 text-start">
+            <dt>Scan type</dt><dd>{{ scan.get_scan_type_display }}</dd>
+            <dt>Sanitized preview</dt><dd>{{ scan.target_preview }}</dd>
+            <dt>Content hash</dt><dd><code>{{ scan.content_hash|slice:":16" }}…</code></dd>
+          </dl>
+        </div>
+      </div>
+      <div class="col-lg-7">
+        <div class="surface-card p-4 p-md-5 mb-4">
+          <div class="section-kicker">Why it was flagged</div>
+          <h2>Explainable indicators</h2>
+          <p class="text-muted-soft">{{ scan.explanation }}</p>
+          <div class="indicator-list mt-4">
+            {% for indicator in scan.indicators %}
+            <article>
+              <div>
+                <strong>{{ indicator.label }}</strong>
+                <p>{{ indicator.detail }}</p>
+              </div>
+              <span>+{{ indicator.weight }}</span>
+            </article>
+            {% endfor %}
+          </div>
+        </div>
+        <div class="surface-card p-4 p-md-5">
+          <div class="section-kicker">Recommended response</div>
+          <h2>Next actions</h2>
+          <ul class="action-list mt-3">
+            {% for action in scan.recommended_actions %}
+            <li>{{ action }}</li>
+            {% endfor %}
+          </ul>
+          <div class="d-flex flex-wrap gap-3 mt-4">
+            <a class="btn btn-ghost" href="{% url 'scan_history' %}">Back to dashboard</a>
+            <a class="btn btn-primary-neo" href="{% url 'home' %}#scanner">New scan</a>
+          </div>
+        </div>
+      </div>
+    </div>
+  </div>
+</section>
+{% endblock %}

core/templates/core/scan_history.html

@@ -0,0 +1,60 @@
+{% extends "base.html" %}
+
+{% block title %}Threat Dashboard — SentinelAI{% endblock %}
+{% block meta_description %}Review privacy-safe phishing and scam scan results by risk level, score, and explanation.{% endblock %}
+
+{% block content %}
+<section class="page-hero section-pad-sm">
+  <div class="container">
+    <span class="eyebrow">Dashboard</span>
+    <h1 class="page-title mt-3">Threat scan history</h1>
+    <p class="hero-copy">Monitor risk levels, review explanations, and identify items that need human verification.</p>
+  </div>
+</section>
+<section class="section-pad">
+  <div class="container">
+    <div class="row g-3 mb-4">
+      <div class="col-md-4"><div class="metric-tile"><span>Total scans</span><strong>{{ total_scans }}</strong></div></div>
+      <div class="col-md-4"><div class="metric-tile"><span>Average risk</span><strong>{{ avg_score }}/100</strong></div></div>
+      <div class="col-md-4"><div class="metric-tile"><span>High-risk items</span><strong>{{ high_risk_count }}</strong></div></div>
+    </div>
+    <div class="surface-card p-0 overflow-hidden">
+      {% if scans %}
+      <div class="table-responsive">
+        <table class="table table-dark table-hover align-middle mb-0 app-table">
+          <thead>
+            <tr>
+              <th>Risk</th>
+              <th>Type</th>
+              <th>Preview</th>
+              <th>Verdict</th>
+              <th>Created</th>
+              <th></th>
+            </tr>
+          </thead>
+          <tbody>
+            {% for scan in scans %}
+            <tr>
+              <td><span class="badge risk-{{ scan.risk_badge_class }}">{{ scan.risk_score }}/100</span></td>
+              <td>{{ scan.get_scan_type_display }}</td>
+              <td class="preview-cell">{{ scan.target_preview }}</td>
+              <td>{{ scan.verdict }}</td>
+              <td>{{ scan.created_at|date:"M j, Y H:i" }}</td>
+              <td><a class="btn btn-sm btn-ghost" href="{% url 'scan_detail' scan.pk %}">Review</a></td>
+            </tr>
+            {% endfor %}
+          </tbody>
+        </table>
+      </div>
+      {% else %}
+      <div class="empty-state text-center p-5">
+        <div class="empty-icon" aria-hidden="true">◇</div>
+        <h2>No detections yet</h2>
+        <p>Use the scanner to create your first privacy-safe result.</p>
+        <a class="btn btn-primary-neo" href="{% url 'home' %}#scanner">Run first scan</a>
+      </div>
+      {% endif %}
+    </div>
+  </div>
+</section>
+{% endblock %}

core/tests.py

@@ -1,3 +1,24 @@
 from django.test import TestCase
+from django.urls import reverse
 
-# Create your tests here.
+from .models import ThreatScan
+from .scanner import scan_content
+
+
+class ThreatScanWorkflowTests(TestCase):
+    def test_scanner_flags_suspicious_url(self):
+        result = scan_content("url", "http://paypal-login-security.example.click/account/verify-password")
+        self.assertGreaterEqual(result.risk_score, 35)
+        self.assertTrue(result.indicators)
+
+    def test_post_scan_creates_privacy_safe_record_and_redirects(self):
+        response = self.client.post(reverse("create_scan"), {
+            "scan_type": "message",
+            "content": "Urgent: verify your password now or your bank account will be suspended. Click https://example.com",
+            "store_metadata": "on",
+        })
+        self.assertEqual(response.status_code, 302)
+        scan = ThreatScan.objects.get()
+        self.assertNotIn("Urgent:", scan.content_hash)
+        self.assertGreater(scan.risk_score, 0)
+        self.assertTrue(scan.explanation)

core/urls.py

@@ -1,7 +1,10 @@
 from django.urls import path
 
-from .views import home
+from .views import create_scan, home, scan_detail, scan_history
 
 urlpatterns = [
     path("", home, name="home"),
+    path("scan/", create_scan, name="create_scan"),
+    path("scans/", scan_history, name="scan_history"),
+    path("scans/<int:pk>/", scan_detail, name="scan_detail"),
 ]

core/views.py

@@ -1,25 +1,80 @@
-import os
+from django.db.models import Avg, Count, Max
-import platform
+from django.shortcuts import get_object_or_404, redirect, render
 
-from django import get_version as django_version
+from .forms import ThreatScanForm
-from django.shortcuts import render
+from .models import ThreatScan
-from django.utils import timezone
+from .scanner import scan_content
+
+
+def _dashboard_context():
+    scans = ThreatScan.objects.all()
+    totals = scans.aggregate(total=Count("id"), avg_score=Avg("risk_score"), latest=Max("created_at"))
+    high_risk_count = scans.filter(risk_level__in=[ThreatScan.RiskLevel.HIGH, ThreatScan.RiskLevel.CRITICAL]).count()
+    return {
+        "total_scans": totals["total"] or 0,
+        "avg_score": round(totals["avg_score"] or 0),
+        "latest_scan_at": totals["latest"],
+        "high_risk_count": high_risk_count,
+        "recent_scans": scans[:6],
+    }
 
 
 def home(request):
-    """Render the landing screen with loader and environment details."""
+    form = ThreatScanForm()
-    host_name = request.get_host().lower()
-    agent_brand = "AppWizzy" if host_name == "appwizzy.com" else "Flatlogic"
-    now = timezone.now()
-
     context = {
-        "project_name": "New Style",
+        "project_name": "SentinelAI Cyber Assistant",
-        "agent_brand": agent_brand,
+        "meta_description": "Privacy-first AI cybersecurity assistant for phishing URL and scam message risk scoring with clear explanations.",
-        "django_version": django_version(),
+        "form": form,
-        "python_version": platform.python_version(),
+        **_dashboard_context(),
-        "current_time": now,
-        "host_name": host_name,
-        "project_description": os.getenv("PROJECT_DESCRIPTION", ""),
-        "project_image_url": os.getenv("PROJECT_IMAGE_URL", ""),
     }
     return render(request, "core/index.html", context)
+
+
+def create_scan(request):
+    if request.method != "POST":
+        return redirect("home")
+    form = ThreatScanForm(request.POST)
+    if not form.is_valid():
+        context = {
+            "project_name": "SentinelAI Cyber Assistant",
+            "meta_description": "Scan a suspicious URL, email, or message for phishing risk.",
+            "form": form,
+            **_dashboard_context(),
+        }
+        return render(request, "core/index.html", context, status=422)
+
+    result = scan_content(form.cleaned_data["scan_type"], form.cleaned_data["content"])
+    scan = ThreatScan.objects.create(
+        scan_type=form.cleaned_data["scan_type"],
+        target_preview=result.target_preview,
+        content_hash=result.content_hash,
+        risk_score=result.risk_score,
+        risk_level=result.risk_level,
+        verdict=result.verdict,
+        explanation=result.explanation,
+        indicators=result.indicators,
+        recommended_actions=result.recommended_actions,
+        store_metadata=form.cleaned_data["store_metadata"],
+    )
+    return redirect("scan_detail", pk=scan.pk)
+
+
+def scan_history(request):
+    scans = ThreatScan.objects.all()
+    context = {
+        "project_name": "Scan History",
+        "meta_description": "Review privacy-safe cybersecurity scan results and risk levels.",
+        "scans": scans,
+        **_dashboard_context(),
+    }
+    return render(request, "core/scan_history.html", context)
+
+
+def scan_detail(request, pk):
+    scan = get_object_or_404(ThreatScan, pk=pk)
+    context = {
+        "project_name": f"Scan Result #{scan.pk}",
+        "meta_description": "Detailed phishing and scam risk result with explainable AI indicators.",
+        "scan": scan,
+    }
+    return render(request, "core/scan_detail.html", context)

static/css/custom.css

@@ -1,4 +1,287 @@
-/* Custom styles for the application */
+/* SentinelAI custom theme */
-body {
+:root {
-    font-family: system-ui, -apple-system, sans-serif;
+    --bg: #06111f;
+    --bg-2: #0b1f33;
+    --surface: rgba(15, 34, 54, 0.82);
+    --surface-strong: #10263d;
+    --line: rgba(163, 205, 255, 0.16);
+    --text: #eef7ff;
+    --muted: #9fb6ca;
+    --primary: #10e5b9;
+    --primary-dark: #08a98a;
+    --secondary: #28c2ff;
+    --accent: #ffb020;
+    --danger: #ff4d6d;
+    --success: #2ee59d;
+    --shadow: 0 24px 80px rgba(0, 0, 0, 0.35);
+    --radius-xl: 28px;
+    --radius-lg: 20px;
+}
+
+* { box-sizing: border-box; }
+
+html { scroll-behavior: smooth; }
+
+body {
+    margin: 0;
+    font-family: "Inter", system-ui, -apple-system, BlinkMacSystemFont, "Segoe UI", sans-serif;
+    background:
+        radial-gradient(circle at 10% 5%, rgba(16, 229, 185, 0.16), transparent 28rem),
+        radial-gradient(circle at 88% 20%, rgba(40, 194, 255, 0.14), transparent 24rem),
+        linear-gradient(135deg, var(--bg), #081827 54%, #03101d);
+    color: var(--text);
+    min-height: 100vh;
+}
+
+h1, h2, h3, .navbar-brand {
+    font-family: "Space Grotesk", "Inter", sans-serif;
+    letter-spacing: -0.04em;
+}
+
+a { color: inherit; }
+
+a:hover { color: var(--primary); }
+
+.skip-link {
+    position: absolute;
+    left: -999px;
+    top: 0;
+    background: var(--primary);
+    color: #03101d;
+    padding: .75rem 1rem;
+    z-index: 9999;
+}
+
+.skip-link:focus { left: 1rem; top: 1rem; }
+
+.app-nav {
+    background: rgba(6, 17, 31, 0.78);
+    border-bottom: 1px solid var(--line);
+    backdrop-filter: blur(18px);
+}
+
+.navbar-brand { color: var(--text); font-weight: 700; }
+.navbar-brand:hover, .nav-link:hover { color: var(--primary); }
+.nav-link { color: var(--muted); font-weight: 600; }
+.navbar-toggler { border-color: var(--line); }
+.navbar-toggler-icon { filter: invert(1); }
+.brand-mark { color: var(--primary); text-shadow: 0 0 24px rgba(16, 229, 185, .75); }
+
+.btn {
+    border-radius: 999px;
+    font-weight: 700;
+    letter-spacing: -0.01em;
+}
+
+.btn-primary-neo {
+    color: #02111d;
+    background: linear-gradient(135deg, var(--primary), var(--secondary));
+    border: 0;
+    box-shadow: 0 16px 36px rgba(16, 229, 185, 0.24);
+}
+
+.btn-primary-neo:hover, .btn-primary-neo:focus {
+    color: #02111d;
+    transform: translateY(-1px);
+    box-shadow: 0 20px 44px rgba(40, 194, 255, 0.28);
+}
+
+.btn-ghost, .btn-admin {
+    color: var(--text);
+    border: 1px solid var(--line);
+    background: rgba(255, 255, 255, 0.04);
+}
+
+.btn-ghost:hover, .btn-admin:hover { border-color: var(--primary); background: rgba(16, 229, 185, 0.1); }
+
+.hero-section { padding: 4rem 0 2rem; }
+.section-pad { padding: 5rem 0; }
+.section-pad-sm { padding: 4rem 0 2rem; }
+
+.display-title {
+    font-size: clamp(3rem, 8vw, 6.6rem);
+    line-height: .92;
+    max-width: 12ch;
+}
+
+.page-title { font-size: clamp(2.4rem, 5vw, 4.8rem); line-height: 1; max-width: 12ch; }
+.hero-copy { color: #c7d8e8; font-size: clamp(1.05rem, 2vw, 1.25rem); max-width: 43rem; }
+.eyebrow, .section-kicker {
+    display: inline-flex;
+    align-items: center;
+    gap: .5rem;
+    color: var(--primary);
+    text-transform: uppercase;
+    font-size: .78rem;
+    font-weight: 800;
+    letter-spacing: .14em;
+}
+
+.eyebrow::before, .section-kicker::before {
+    content: "";
+    width: .55rem;
+    height: .55rem;
+    border-radius: 50%;
+    background: var(--primary);
+    box-shadow: 0 0 24px rgba(16, 229, 185, .85);
+}
+
+.text-muted-soft { color: var(--muted); }
+.letter-spaced { letter-spacing: .16em; color: var(--muted); }
+
+.orb {
+    position: absolute;
+    border-radius: 999px;
+    filter: blur(6px);
+    opacity: .7;
+    pointer-events: none;
+}
+.orb-one { width: 18rem; height: 18rem; right: -4rem; top: 6rem; background: radial-gradient(circle, rgba(16,229,185,.28), transparent 62%); }
+.orb-two { width: 12rem; height: 12rem; left: 45%; bottom: 1rem; background: radial-gradient(circle, rgba(255,176,32,.18), transparent 62%); }
+
+.glass-card, .surface-card, .metric-tile {
+    background: linear-gradient(145deg, rgba(16, 38, 61, .9), rgba(9, 24, 40, .82));
+    border: 1px solid var(--line);
+    border-radius: var(--radius-xl);
+    box-shadow: var(--shadow);
+    backdrop-filter: blur(22px);
+}
+
+.hero-panel { padding: clamp(1.5rem, 4vw, 2.5rem); position: relative; overflow: hidden; }
+.hero-panel::after {
+    content: "";
+    position: absolute;
+    inset: auto -4rem -5rem auto;
+    width: 14rem;
+    height: 14rem;
+    background: linear-gradient(135deg, rgba(16,229,185,.22), rgba(40,194,255,.16));
+    transform: rotate(20deg);
+    border-radius: 2.5rem;
+}
+.status-dot { width: .85rem; height: .85rem; background: var(--primary); border-radius: 50%; box-shadow: 0 0 22px var(--primary); }
+
+.risk-meter {
+    width: 12.5rem;
+    height: 12.5rem;
+    border-radius: 50%;
+    display: grid;
+    place-items: center;
+    background:
+        radial-gradient(circle at center, #10263d 58%, transparent 59%),
+        conic-gradient(var(--primary), var(--secondary), var(--accent), var(--primary));
+    position: relative;
+}
+.risk-meter span { display: block; font: 700 3.5rem/1 "Space Grotesk"; }
+.risk-meter small { display: block; color: var(--muted); margin-top: .25rem; text-transform: uppercase; letter-spacing: .12em; font-weight: 800; font-size: .72rem; }
+.risk-meter.detail { width: 15rem; height: 15rem; }
+.risk-ring-warning { background: radial-gradient(circle at center, #10263d 58%, transparent 59%), conic-gradient(var(--accent), #ffd166, var(--accent)); }
+.risk-ring-danger, .risk-ring-critical { background: radial-gradient(circle at center, #10263d 58%, transparent 59%), conic-gradient(var(--danger), var(--accent), var(--danger)); }
+
+.metric-card, .metric-tile {
+    padding: 1rem;
+    background: rgba(255,255,255,.045);
+    border: 1px solid var(--line);
+    border-radius: var(--radius-lg);
+}
+.metric-card strong, .metric-tile strong { display: block; font: 700 1.8rem/1 "Space Grotesk"; }
+.metric-card span, .metric-tile span { color: var(--muted); font-size: .86rem; }
+.metric-tile { padding: 1.4rem; }
+.metric-tile strong { margin-top: .5rem; font-size: 2.2rem; }
+
+.trust-row { display: flex; flex-wrap: wrap; gap: .75rem; }
+.trust-row span { padding: .5rem .8rem; border: 1px solid var(--line); border-radius: 999px; color: #d7e8f7; background: rgba(255,255,255,.04); }
+.signal-list { display: grid; gap: .8rem; color: #d7e8f7; }
+.signal { display: inline-block; width: .65rem; height: .65rem; border-radius: 50%; margin-right: .55rem; }
+.signal.good { background: var(--success); } .signal.warn { background: var(--accent); } .signal.danger { background: var(--danger); }
+
+.scan-form textarea, .scan-form input[type="text"], .form-control {
+    width: 100%;
+    color: var(--text);
+    background: rgba(3, 16, 29, 0.72);
+    border: 1px solid var(--line);
+    border-radius: 18px;
+    padding: 1rem;
+}
+.scan-form textarea:focus, .form-control:focus {
+    color: var(--text);
+    background: rgba(3, 16, 29, .9);
+    border-color: var(--primary);
+    box-shadow: 0 0 0 .25rem rgba(16, 229, 185, .12);
+}
+.form-label { color: #dcecff; font-weight: 800; }
+.form-text { color: var(--muted); }
+.invalid-copy { color: #ff8ba0; font-weight: 700; margin-top: .5rem; }
+
+.scan-choice-grid { display: grid; grid-template-columns: repeat(2, minmax(0, 1fr)); gap: .75rem; }
+.scan-choice {
+    display: flex;
+    align-items: center;
+    gap: .65rem;
+    padding: .9rem 1rem;
+    border: 1px solid var(--line);
+    border-radius: 18px;
+    background: rgba(255,255,255,.04);
+    cursor: pointer;
+    font-weight: 800;
+}
+.scan-choice:has(input:checked) { border-color: var(--primary); background: rgba(16,229,185,.12); }
+.scan-choice input, .metadata-check input { accent-color: var(--primary); }
+
+.privacy-stack { display: grid; gap: 1rem; }
+.privacy-stack article { padding: 1.2rem; border-radius: var(--radius-lg); border: 1px solid var(--line); background: rgba(255,255,255,.035); }
+.privacy-stack span { color: var(--primary); font-weight: 900; }
+.privacy-stack h3 { font-size: 1.15rem; margin: .4rem 0; }
+.privacy-stack p { color: var(--muted); margin: 0; }
+
+.scan-card {
+    display: block;
+    min-height: 13rem;
+    padding: 1.35rem;
+    text-decoration: none;
+    border-radius: var(--radius-lg);
+    border: 1px solid var(--line);
+    background: linear-gradient(145deg, rgba(16,38,61,.86), rgba(9,24,40,.72));
+    transition: transform .2s ease, border-color .2s ease;
+}
+.scan-card:hover { transform: translateY(-3px); border-color: var(--primary); color: var(--text); }
+.scan-card strong { display: block; font: 700 2.2rem/1 "Space Grotesk"; margin: 1rem 0 .75rem; }
+.scan-card p { color: #d6e7f6; }
+.scan-card small { color: var(--muted); }
+
+.badge { border-radius: 999px; padding: .45rem .7rem; }
+.risk-success { background: rgba(46,229,157,.15); color: #7dffc8; border: 1px solid rgba(46,229,157,.28); }
+.risk-warning { background: rgba(255,176,32,.15); color: #ffd68a; border: 1px solid rgba(255,176,32,.3); }
+.risk-danger, .risk-critical { background: rgba(255,77,109,.16); color: #ff9aad; border: 1px solid rgba(255,77,109,.34); }
+
+.empty-state { border: 1px dashed var(--line); border-radius: var(--radius-xl); background: rgba(255,255,255,.035); }
+.empty-icon { font-size: 3rem; color: var(--primary); }
+
+.page-hero { background: linear-gradient(180deg, rgba(16,229,185,.07), transparent); border-bottom: 1px solid var(--line); }
+.app-table { --bs-table-bg: transparent; --bs-table-border-color: var(--line); color: var(--text); }
+.app-table th { color: var(--muted); text-transform: uppercase; font-size: .78rem; letter-spacing: .08em; }
+.preview-cell { max-width: 24rem; color: #d7e8f7; }
+
+.scan-meta dt { color: var(--muted); text-transform: uppercase; letter-spacing: .08em; font-size: .75rem; margin-top: 1rem; }
+.scan-meta dd { color: var(--text); margin-bottom: 0; word-break: break-word; }
+.scan-meta code { color: var(--primary); }
+.indicator-list { display: grid; gap: .8rem; }
+.indicator-list article {
+    display: flex;
+    justify-content: space-between;
+    gap: 1rem;
+    padding: 1rem;
+    border-radius: 18px;
+    border: 1px solid var(--line);
+    background: rgba(255,255,255,.04);
+}
+.indicator-list p { color: var(--muted); margin: .25rem 0 0; }
+.indicator-list span { color: var(--accent); font-weight: 900; }
+.action-list { color: #d7e8f7; display: grid; gap: .7rem; }
+.site-footer { color: var(--muted); border-top: 1px solid var(--line); background: rgba(3,16,29,.72); }
+
+@media (max-width: 767px) {
+    .hero-section { padding-top: 2.5rem; }
+    .scan-choice-grid { grid-template-columns: 1fr; }
+    .risk-meter { width: 10.5rem; height: 10.5rem; }
+    .display-title { max-width: 100%; }
 }

staticfiles/css/custom.css

@@ -1,21 +1,287 @@
-
+/* SentinelAI custom theme */
 :root {
-    --bg-color-start: #6a11cb;
+    --bg: #06111f;
-    --bg-color-end: #2575fc;
+    --bg-2: #0b1f33;
-    --text-color: #ffffff;
+    --surface: rgba(15, 34, 54, 0.82);
-    --card-bg-color: rgba(255, 255, 255, 0.01);
+    --surface-strong: #10263d;
-    --card-border-color: rgba(255, 255, 255, 0.1);
+    --line: rgba(163, 205, 255, 0.16);
+    --text: #eef7ff;
+    --muted: #9fb6ca;
+    --primary: #10e5b9;
+    --primary-dark: #08a98a;
+    --secondary: #28c2ff;
+    --accent: #ffb020;
+    --danger: #ff4d6d;
+    --success: #2ee59d;
+    --shadow: 0 24px 80px rgba(0, 0, 0, 0.35);
+    --radius-xl: 28px;
+    --radius-lg: 20px;
 }
+
+* { box-sizing: border-box; }
+
+html { scroll-behavior: smooth; }
+
 body {
     margin: 0;
-    font-family: 'Inter', sans-serif;
+    font-family: "Inter", system-ui, -apple-system, BlinkMacSystemFont, "Segoe UI", sans-serif;
-    background: linear-gradient(45deg, var(--bg-color-start), var(--bg-color-end));
+    background:
-    color: var(--text-color);
+        radial-gradient(circle at 10% 5%, rgba(16, 229, 185, 0.16), transparent 28rem),
-    display: flex;
+        radial-gradient(circle at 88% 20%, rgba(40, 194, 255, 0.14), transparent 24rem),
-    justify-content: center;
+        linear-gradient(135deg, var(--bg), #081827 54%, #03101d);
-    align-items: center;
+    color: var(--text);
     min-height: 100vh;
-    text-align: center;
+}
-    overflow: hidden;
+
+h1, h2, h3, .navbar-brand {
+    font-family: "Space Grotesk", "Inter", sans-serif;
+    letter-spacing: -0.04em;
+}
+
+a { color: inherit; }
+
+a:hover { color: var(--primary); }
+
+.skip-link {
+    position: absolute;
+    left: -999px;
+    top: 0;
+    background: var(--primary);
+    color: #03101d;
+    padding: .75rem 1rem;
+    z-index: 9999;
+}
+
+.skip-link:focus { left: 1rem; top: 1rem; }
+
+.app-nav {
+    background: rgba(6, 17, 31, 0.78);
+    border-bottom: 1px solid var(--line);
+    backdrop-filter: blur(18px);
+}
+
+.navbar-brand { color: var(--text); font-weight: 700; }
+.navbar-brand:hover, .nav-link:hover { color: var(--primary); }
+.nav-link { color: var(--muted); font-weight: 600; }
+.navbar-toggler { border-color: var(--line); }
+.navbar-toggler-icon { filter: invert(1); }
+.brand-mark { color: var(--primary); text-shadow: 0 0 24px rgba(16, 229, 185, .75); }
+
+.btn {
+    border-radius: 999px;
+    font-weight: 700;
+    letter-spacing: -0.01em;
+}
+
+.btn-primary-neo {
+    color: #02111d;
+    background: linear-gradient(135deg, var(--primary), var(--secondary));
+    border: 0;
+    box-shadow: 0 16px 36px rgba(16, 229, 185, 0.24);
+}
+
+.btn-primary-neo:hover, .btn-primary-neo:focus {
+    color: #02111d;
+    transform: translateY(-1px);
+    box-shadow: 0 20px 44px rgba(40, 194, 255, 0.28);
+}
+
+.btn-ghost, .btn-admin {
+    color: var(--text);
+    border: 1px solid var(--line);
+    background: rgba(255, 255, 255, 0.04);
+}
+
+.btn-ghost:hover, .btn-admin:hover { border-color: var(--primary); background: rgba(16, 229, 185, 0.1); }
+
+.hero-section { padding: 4rem 0 2rem; }
+.section-pad { padding: 5rem 0; }
+.section-pad-sm { padding: 4rem 0 2rem; }
+
+.display-title {
+    font-size: clamp(3rem, 8vw, 6.6rem);
+    line-height: .92;
+    max-width: 12ch;
+}
+
+.page-title { font-size: clamp(2.4rem, 5vw, 4.8rem); line-height: 1; max-width: 12ch; }
+.hero-copy { color: #c7d8e8; font-size: clamp(1.05rem, 2vw, 1.25rem); max-width: 43rem; }
+.eyebrow, .section-kicker {
+    display: inline-flex;
+    align-items: center;
+    gap: .5rem;
+    color: var(--primary);
+    text-transform: uppercase;
+    font-size: .78rem;
+    font-weight: 800;
+    letter-spacing: .14em;
+}
+
+.eyebrow::before, .section-kicker::before {
+    content: "";
+    width: .55rem;
+    height: .55rem;
+    border-radius: 50%;
+    background: var(--primary);
+    box-shadow: 0 0 24px rgba(16, 229, 185, .85);
+}
+
+.text-muted-soft { color: var(--muted); }
+.letter-spaced { letter-spacing: .16em; color: var(--muted); }
+
+.orb {
+    position: absolute;
+    border-radius: 999px;
+    filter: blur(6px);
+    opacity: .7;
+    pointer-events: none;
+}
+.orb-one { width: 18rem; height: 18rem; right: -4rem; top: 6rem; background: radial-gradient(circle, rgba(16,229,185,.28), transparent 62%); }
+.orb-two { width: 12rem; height: 12rem; left: 45%; bottom: 1rem; background: radial-gradient(circle, rgba(255,176,32,.18), transparent 62%); }
+
+.glass-card, .surface-card, .metric-tile {
+    background: linear-gradient(145deg, rgba(16, 38, 61, .9), rgba(9, 24, 40, .82));
+    border: 1px solid var(--line);
+    border-radius: var(--radius-xl);
+    box-shadow: var(--shadow);
+    backdrop-filter: blur(22px);
+}
+
+.hero-panel { padding: clamp(1.5rem, 4vw, 2.5rem); position: relative; overflow: hidden; }
+.hero-panel::after {
+    content: "";
+    position: absolute;
+    inset: auto -4rem -5rem auto;
+    width: 14rem;
+    height: 14rem;
+    background: linear-gradient(135deg, rgba(16,229,185,.22), rgba(40,194,255,.16));
+    transform: rotate(20deg);
+    border-radius: 2.5rem;
+}
+.status-dot { width: .85rem; height: .85rem; background: var(--primary); border-radius: 50%; box-shadow: 0 0 22px var(--primary); }
+
+.risk-meter {
+    width: 12.5rem;
+    height: 12.5rem;
+    border-radius: 50%;
+    display: grid;
+    place-items: center;
+    background:
+        radial-gradient(circle at center, #10263d 58%, transparent 59%),
+        conic-gradient(var(--primary), var(--secondary), var(--accent), var(--primary));
     position: relative;
 }
+.risk-meter span { display: block; font: 700 3.5rem/1 "Space Grotesk"; }
+.risk-meter small { display: block; color: var(--muted); margin-top: .25rem; text-transform: uppercase; letter-spacing: .12em; font-weight: 800; font-size: .72rem; }
+.risk-meter.detail { width: 15rem; height: 15rem; }
+.risk-ring-warning { background: radial-gradient(circle at center, #10263d 58%, transparent 59%), conic-gradient(var(--accent), #ffd166, var(--accent)); }
+.risk-ring-danger, .risk-ring-critical { background: radial-gradient(circle at center, #10263d 58%, transparent 59%), conic-gradient(var(--danger), var(--accent), var(--danger)); }
+
+.metric-card, .metric-tile {
+    padding: 1rem;
+    background: rgba(255,255,255,.045);
+    border: 1px solid var(--line);
+    border-radius: var(--radius-lg);
+}
+.metric-card strong, .metric-tile strong { display: block; font: 700 1.8rem/1 "Space Grotesk"; }
+.metric-card span, .metric-tile span { color: var(--muted); font-size: .86rem; }
+.metric-tile { padding: 1.4rem; }
+.metric-tile strong { margin-top: .5rem; font-size: 2.2rem; }
+
+.trust-row { display: flex; flex-wrap: wrap; gap: .75rem; }
+.trust-row span { padding: .5rem .8rem; border: 1px solid var(--line); border-radius: 999px; color: #d7e8f7; background: rgba(255,255,255,.04); }
+.signal-list { display: grid; gap: .8rem; color: #d7e8f7; }
+.signal { display: inline-block; width: .65rem; height: .65rem; border-radius: 50%; margin-right: .55rem; }
+.signal.good { background: var(--success); } .signal.warn { background: var(--accent); } .signal.danger { background: var(--danger); }
+
+.scan-form textarea, .scan-form input[type="text"], .form-control {
+    width: 100%;
+    color: var(--text);
+    background: rgba(3, 16, 29, 0.72);
+    border: 1px solid var(--line);
+    border-radius: 18px;
+    padding: 1rem;
+}
+.scan-form textarea:focus, .form-control:focus {
+    color: var(--text);
+    background: rgba(3, 16, 29, .9);
+    border-color: var(--primary);
+    box-shadow: 0 0 0 .25rem rgba(16, 229, 185, .12);
+}
+.form-label { color: #dcecff; font-weight: 800; }
+.form-text { color: var(--muted); }
+.invalid-copy { color: #ff8ba0; font-weight: 700; margin-top: .5rem; }
+
+.scan-choice-grid { display: grid; grid-template-columns: repeat(2, minmax(0, 1fr)); gap: .75rem; }
+.scan-choice {
+    display: flex;
+    align-items: center;
+    gap: .65rem;
+    padding: .9rem 1rem;
+    border: 1px solid var(--line);
+    border-radius: 18px;
+    background: rgba(255,255,255,.04);
+    cursor: pointer;
+    font-weight: 800;
+}
+.scan-choice:has(input:checked) { border-color: var(--primary); background: rgba(16,229,185,.12); }
+.scan-choice input, .metadata-check input { accent-color: var(--primary); }
+
+.privacy-stack { display: grid; gap: 1rem; }
+.privacy-stack article { padding: 1.2rem; border-radius: var(--radius-lg); border: 1px solid var(--line); background: rgba(255,255,255,.035); }
+.privacy-stack span { color: var(--primary); font-weight: 900; }
+.privacy-stack h3 { font-size: 1.15rem; margin: .4rem 0; }
+.privacy-stack p { color: var(--muted); margin: 0; }
+
+.scan-card {
+    display: block;
+    min-height: 13rem;
+    padding: 1.35rem;
+    text-decoration: none;
+    border-radius: var(--radius-lg);
+    border: 1px solid var(--line);
+    background: linear-gradient(145deg, rgba(16,38,61,.86), rgba(9,24,40,.72));
+    transition: transform .2s ease, border-color .2s ease;
+}
+.scan-card:hover { transform: translateY(-3px); border-color: var(--primary); color: var(--text); }
+.scan-card strong { display: block; font: 700 2.2rem/1 "Space Grotesk"; margin: 1rem 0 .75rem; }
+.scan-card p { color: #d6e7f6; }
+.scan-card small { color: var(--muted); }
+
+.badge { border-radius: 999px; padding: .45rem .7rem; }
+.risk-success { background: rgba(46,229,157,.15); color: #7dffc8; border: 1px solid rgba(46,229,157,.28); }
+.risk-warning { background: rgba(255,176,32,.15); color: #ffd68a; border: 1px solid rgba(255,176,32,.3); }
+.risk-danger, .risk-critical { background: rgba(255,77,109,.16); color: #ff9aad; border: 1px solid rgba(255,77,109,.34); }
+
+.empty-state { border: 1px dashed var(--line); border-radius: var(--radius-xl); background: rgba(255,255,255,.035); }
+.empty-icon { font-size: 3rem; color: var(--primary); }
+
+.page-hero { background: linear-gradient(180deg, rgba(16,229,185,.07), transparent); border-bottom: 1px solid var(--line); }
+.app-table { --bs-table-bg: transparent; --bs-table-border-color: var(--line); color: var(--text); }
+.app-table th { color: var(--muted); text-transform: uppercase; font-size: .78rem; letter-spacing: .08em; }
+.preview-cell { max-width: 24rem; color: #d7e8f7; }
+
+.scan-meta dt { color: var(--muted); text-transform: uppercase; letter-spacing: .08em; font-size: .75rem; margin-top: 1rem; }
+.scan-meta dd { color: var(--text); margin-bottom: 0; word-break: break-word; }
+.scan-meta code { color: var(--primary); }
+.indicator-list { display: grid; gap: .8rem; }
+.indicator-list article {
+    display: flex;
+    justify-content: space-between;
+    gap: 1rem;
+    padding: 1rem;
+    border-radius: 18px;
+    border: 1px solid var(--line);
+    background: rgba(255,255,255,.04);
+}
+.indicator-list p { color: var(--muted); margin: .25rem 0 0; }
+.indicator-list span { color: var(--accent); font-weight: 900; }
+.action-list { color: #d7e8f7; display: grid; gap: .7rem; }
+.site-footer { color: var(--muted); border-top: 1px solid var(--line); background: rgba(3,16,29,.72); }
+
+@media (max-width: 767px) {
+    .hero-section { padding-top: 2.5rem; }
+    .scan-choice-grid { grid-template-columns: 1fr; }
+    .risk-meter { width: 10.5rem; height: 10.5rem; }
+    .display-title { max-width: 100%; }
+}