{% extends "base.html" %}

{% block title %}False Positive Analysis — {{ project_filter or folder_name or recipe_name }}{% endblock %}

{% block content %}
<style>
  .kpi-row { display: flex; gap: 16px; margin-bottom: 28px; flex-wrap: wrap; }
  .kpi-card {
    flex: 1; min-width: 140px; background: #fff; border: 1px solid #dee2e6;
    border-radius: 8px; padding: 18px 16px; text-align: center;
  }
  .kpi-card.border-blue   { border-top: 4px solid #1976d2; }
  .kpi-card.border-green  { border-top: 4px solid #388e3c; }
  .kpi-card.border-orange { border-top: 4px solid #f57c00; }
  .kpi-card.border-purple { border-top: 4px solid #6a1b9a; }
  .kpi-value { font-size: 2em; font-weight: 700; line-height: 1.2; }
  .kpi-label { font-size: 0.8em; color: #666; margin-top: 4px; }

  .badge { display: inline-block; padding: 2px 8px; border-radius: 4px; font-size: 0.75em; font-weight: 600; }
  .badge-HIGH   { background: #d32f2f; color: #fff; }
  .badge-MEDIUM { background: #f57c00; color: #fff; }
  .badge-LOW    { background: #fbc02d; color: #333; }

  .badge-sev-CRITICAL { background: #d32f2f; color: #fff; }
  .badge-sev-HIGH     { background: #f57c00; color: #fff; }
  .badge-sev-MEDIUM   { background: #fbc02d; color: #333; }
  .badge-sev-LOW      { background: #388e3c; color: #fff; }
  .badge-sev-INFO     { background: #0288d1; color: #fff; }

  .pill { display: inline-block; padding: 2px 7px; border-radius: 10px; font-size: 0.7em; font-weight: 600; }
  .pill-signal { background: #e3f2fd; color: #1565c0; margin-right: 4px; }

  section.report-section { margin-bottom: 32px; }
  section.report-section h2 { font-size: 1.15em; color: #2c3e50; border-bottom: 2px solid #e9ecef; padding-bottom: 6px; margin-bottom: 14px; }

  table.review-queue { width: 100%; border-collapse: collapse; font-size: 0.85em; }
  table.review-queue th { background: #f8f9fa; border-bottom: 2px solid #dee2e6; padding: 8px 10px; text-align: left; font-weight: 600; }
  table.review-queue td { border-bottom: 1px solid #eee; padding: 7px 10px; vertical-align: top; }
  table.review-queue tr:hover { background: #f5f5f5; }
  .reason-cell { max-width: 350px; font-size: 0.9em; color: #555; }
</style>

<script>
function copyPrompt(btn) {
  var pre = btn.parentElement.querySelector('pre');
  navigator.clipboard.writeText(pre.textContent).then(function() {
    btn.textContent = 'Copied!';
    setTimeout(function() { btn.textContent = 'Copy'; }, 2000);
  });
}
</script>

<!-- Summary Cards -->
<section class="report-section">
  <div class="kpi-row">
    <div class="kpi-card border-blue">
      <div class="kpi-value">{{ summary.total_open_findings if summary else 0 }}</div>
      <div class="kpi-label">Open Findings</div>
    </div>
    <div class="kpi-card border-green">
      <div class="kpi-value">{{ summary.fp_candidates_found if summary else 0 }}</div>
      <div class="kpi-label">FP Candidates</div>
    </div>
    <div class="kpi-card border-orange">
      <div class="kpi-value">{{ summary.mechanical_detections if summary else 0 }}</div>
      <div class="kpi-label">Mechanical Detections</div>
    </div>
    <div class="kpi-card border-purple">
      <div class="kpi-value">{{ summary.ai_detections if summary else 0 }}</div>
      <div class="kpi-label">AI Detections</div>
    </div>
  </div>
</section>

<!-- Component Identity Assertions -->
{% if identity_assertions and identity_assertions|length > 0 %}
<section class="report-section">
  <h2>Component Identity Assertions</h2>
  <p style="color: #6c757d;">
    {{ identity_assertions|length }} component(s) detected as misidentified relative
    to NVD. Each assertion groups the CVEs attributed to the scanned component and
    classifies whether they apply to the actual product.
  </p>
  {% for a in identity_assertions %}
  <details open style="margin-bottom: 18px; border: 1px solid #dee2e6; border-radius: 6px; padding: 12px;">
    <summary style="cursor:pointer; font-weight: 600;">
      {{ a.component_name }} {{ a.component_version }} —
      scanned as <code>{{ a.likely_product or '?' }}</code>, NVD expected
      <code>{{ a.nvd_product or '?' }}</code>
      <span class="badge badge-HIGH" style="margin-left: 8px;">MISMATCHED</span>
      <span class="pill pill-signal" style="margin-left: 6px;">confidence: {{ a.confidence or 'medium' }}</span>
    </summary>
    <div style="margin-top: 10px;">
      <p><strong>Evidence:</strong> {{ a.evidence or '—' }}</p>
      <table class="review-queue">
        <thead>
          <tr>
            <th>CVE</th>
            <th>Verdict</th>
            <th>Rationale</th>
            <th>Recommended VEX</th>
          </tr>
        </thead>
        <tbody>
          {% for cv in a.cve_verdicts %}
          <tr>
            <td><strong>{{ cv.cve_id }}</strong></td>
            <td>
              {% if cv.verdict == 'does_not_apply' %}
                <span class="badge badge-HIGH">does_not_apply</span>
              {% else %}
                <span class="badge badge-MEDIUM">might_still_apply</span>
              {% endif %}
            </td>
            <td class="reason-cell">{{ cv.rationale or '—' }}</td>
            <td>
              {% if cv.verdict == 'does_not_apply' %}
                NOT_AFFECTED / CODE_NOT_PRESENT
              {% else %}
                Review individually
              {% endif %}
            </td>
          </tr>
          {% endfor %}
        </tbody>
      </table>
    </div>
  </details>
  {% endfor %}
</section>
{% endif %}

<!-- Residual FP Candidates (finding-level fallback) -->
<section class="report-section">
  <h2>Residual FP Candidates</h2>
  <p style="color: #6c757d;">
    Findings on components whose identity was confirmed or ambiguous, flagged as
    likely FP by finding-level applicability analysis.
  </p>
  {% if candidates and candidates|length > 0 %}
  <table class="review-queue">
    <thead>
      <tr>
        <th>CVE</th>
        <th>Component</th>
        <th>Severity</th>
        <th>Confidence</th>
        <th>Signals</th>
        <th>Reason / AI Rationale</th>
        <th>Action</th>
      </tr>
    </thead>
    <tbody>
      {% for row in candidates %}
      <tr>
        <td><strong>{{ row.cve_id or row.finding_id or '—' }}</strong></td>
        <td>{{ row.component_name or '—' }} {{ row.component_version or '' }}</td>
        <td><span class="badge badge-sev-{{ row.severity or 'INFO' }}">{{ row.severity or 'UNKNOWN' }}</span></td>
        <td>{{ row.fp_confidence or '—' }}</td>
        <td>
          {% if row.fp_signals %}
            {% if row.fp_signals is string %}
              {% for sig in row.fp_signals.split(',') %}
                <span class="pill pill-signal">{{ sig.strip() }}</span>
              {% endfor %}
            {% else %}
              {% for sig in row.fp_signals %}
                <span class="pill pill-signal">{{ sig }}</span>
              {% endfor %}
            {% endif %}
          {% endif %}
        </td>
        <td class="reason-cell">
          {{ row.primary_reason or '—' }}
          {% if row.ai_rationale %}
          <details style="margin-top: 4px;">
            <summary style="cursor:pointer;color:#007bff;font-size:0.85em;">AI details</summary>
            <div style="margin-top:4px;padding:8px;background:#f8f9fa;border-radius:4px;font-size:0.85em;">
              <strong>Verdict:</strong> {{ row.ai_verdict }}<br>
              {{ row.ai_rationale }}
            </div>
          </details>
          {% endif %}
        </td>
        <td>{{ row.recommended_action or 'Review' }}</td>
      </tr>
      {% endfor %}
    </tbody>
  </table>
  {% else %}
  <p style="color: #888;">No residual FP candidates.</p>
  {% endif %}
</section>

<!-- Component Identity Prompts (air-gapped --ai-prompts workflow) -->
{% if ai_component_prompts and ai_component_prompts|length > 0 %}
<section class="report-section">
  <h2>Component Identity Prompts</h2>
  <p style="color: #6c757d;">
    {{ ai_component_prompts|length }} prompt(s) for offline LLM review. Paste each
    into an external model; if the answer is <code>IDENTITY: mismatched</code>,
    run the per-CVE applicability fan-out using the <code>LIKELY_PRODUCT</code>
    and <code>NVD_PRODUCT</code> values. These prompts are also written to
    <code>False Positive Analysis_prompts.md</code> alongside this report.
  </p>
  {% for p in ai_component_prompts %}
  <details style="margin-bottom: 8px;">
    <summary style="cursor:pointer;color:#007bff;font-weight:600;font-size:0.9em;">{{ p.component }}</summary>
    <div style="position:relative;margin-top:6px;">
      <button onclick="copyPrompt(this)" style="position:absolute;top:5px;right:5px;padding:4px 10px;font-size:0.8em;cursor:pointer;border:1px solid #dee2e6;border-radius:4px;background:#f8f9fa;">Copy</button>
      <pre style="background:#f8f9fa;padding:15px;border-radius:6px;font-size:0.8em;white-space:pre-wrap;word-wrap:break-word;max-height:400px;overflow-y:auto;">{{ p.prompt }}</pre>
    </div>
  </details>
  {% endfor %}
</section>
{% endif %}

<!-- Signal Distribution -->
{% if summary and summary.by_signal_type %}
<section class="report-section">
  <h2>Detection by Signal Type</h2>
  <table class="review-queue" style="max-width: 500px;">
    <thead><tr><th>Signal</th><th>Count</th></tr></thead>
    <tbody>
      {% for sig, count in summary.by_signal_type.items() %}
      <tr><td>{{ sig }}</td><td>{{ count }}</td></tr>
      {% endfor %}
    </tbody>
  </table>
</section>
{% endif %}

{% endblock %}