diff --git a/backend-compliance/compliance/services/dse_matcher.py b/backend-compliance/compliance/services/dse_matcher.py
new file mode 100644
index 0000000..d802672
--- /dev/null
+++ b/backend-compliance/compliance/services/dse_matcher.py
@@ -0,0 +1,202 @@
+"""
+DSE Matcher — matches detected services against DSE sections and
+generates TextReferences with original text, position, and corrections.
+"""
+
+import logging
+import re
+from dataclasses import dataclass
+
+from compliance.services.dse_parser import DSESection, find_section_by_content, find_section_by_category
+
+logger = logging.getLogger(__name__)
+
+# Category → typical DSE section heading keywords
+CATEGORY_SECTION_MAP = {
+    "tracking": ["cookie", "tracking", "webanalyse", "analytics", "statistik", "reichweitenmessung"],
+    "marketing": ["marketing", "werbung", "newsletter", "remarketing", "werbe"],
+    "payment": ["zahlung", "payment", "bezahl", "zahlungsabwicklung", "zahlungsdienst"],
+    "chatbot": ["chat", "kommunikation", "kundenservice", "kontakt", "livechat"],
+    "cdn": ["hosting", "bereitstellung", "technisch", "infrastruktur", "content delivery"],
+    "other": ["sonstig", "weitere", "dritte", "extern", "dienstleister"],
+}
+
+
+@dataclass
+class TextReference:
+    """Reference to a specific text block in the DSE."""
+    found: bool
+    source_url: str = ""
+    document_type: str = "Datenschutzerklaerung"
+    section_heading: str = ""
+    section_number: str = ""
+    parent_section: str = ""
+    paragraph_index: int = 0
+    original_text: str = ""
+    issue: str = ""  # "missing", "incomplete", "incorrect"
+    correction_type: str = ""  # "insert", "replace", "append"
+    correction_text: str = ""
+    insert_after: str = ""
+
+
+def match_service_to_dse(
+    service_name: str,
+    service_category: str,
+    sections: list[DSESection],
+    url: str = "",
+) -> TextReference:
+    """Find where a service is mentioned in the DSE and build a TextReference."""
+    # Step 1: Search for exact service name
+    section = find_section_by_content(sections, service_name)
+
+    if section:
+        # Found — extract the relevant paragraph
+        original = _extract_relevant_paragraph(section.content, service_name)
+        return TextReference(
+            found=True,
+            source_url=url,
+            section_heading=section.heading,
+            section_number=section.section_number,
+            parent_section=section.parent_heading,
+            paragraph_index=_find_paragraph_index(section.content, service_name),
+            original_text=original,
+            issue="",  # Found and present — caller determines if complete
+        )
+
+    # Step 2: Search for provider name (e.g., "Google" for "Google Analytics")
+    # But only if the provider name is specific enough — avoid "Google" matching YouTube
+    provider = service_name.split()[0] if " " in service_name else service_name
+    if len(provider) < 4 or provider.lower() in ("the", "a", "an"):
+        provider = service_name  # Too short/generic, use full name
+
+    section = find_section_by_content(sections, provider)
+    # Verify: the section must actually be about THIS service, not just mention the provider
+    if section and provider.lower() != service_name.lower():
+        # Check if the full service name or a close variant is in the section
+        content_lower = section.content.lower()
+        service_words = service_name.lower().split()
+        # At least 2 words of the service name must match (not just "Google")
+        matching_words = sum(1 for w in service_words if w in content_lower)
+        if matching_words < 2 and service_name.lower() not in content_lower:
+            section = None  # False match — provider name found but wrong context
+
+    if section:
+        original = _extract_relevant_paragraph(section.content, provider)
+        return TextReference(
+            found=True,
+            source_url=url,
+            section_heading=section.heading,
+            section_number=section.section_number,
+            parent_section=section.parent_heading,
+            paragraph_index=_find_paragraph_index(section.content, provider),
+            original_text=original,
+            issue="incomplete",  # Provider mentioned but not specific service
+        )
+
+    # Step 3: Not found — suggest insertion point
+    insert_section = find_section_by_category(sections, service_category)
+    insert_after = insert_section.heading if insert_section else ""
+
+    # If no category match, find the last "Cookies"/"Tracking" or "Sonstiges" section
+    if not insert_after:
+        for s in reversed(sections):
+            h = s.heading.lower()
+            if any(kw in h for kw in ["cookie", "datenschutz", "daten"]):
+                insert_after = s.heading
+                break
+
+    return TextReference(
+        found=False,
+        source_url=url,
+        document_type="Datenschutzerklaerung",
+        issue="missing",
+        correction_type="insert",
+        insert_after=insert_after,
+    )
+
+
+def build_text_references(
+    detected_services: list[dict],
+    dse_services: list[dict],
+    sections: list[DSESection],
+    url: str = "",
+) -> dict[str, TextReference]:
+    """Build TextReferences for all detected services.
+
+    Returns dict: service_id → TextReference
+    """
+    refs: dict[str, TextReference] = {}
+
+    for svc in detected_services:
+        service_id = svc.get("id", svc.get("name", ""))
+        service_name = svc.get("name", "")
+        category = svc.get("category", "other")
+
+        ref = match_service_to_dse(service_name, category, sections, url)
+
+        # Check if service is in the DSE SOLL list
+        dse_match = _find_in_dse_list(service_name, dse_services)
+
+        if ref.found and dse_match:
+            ref.issue = ""  # All good — documented and present
+        elif ref.found and not dse_match:
+            # Found in text but not in LLM extraction — still OK
+            ref.issue = ""
+        elif not ref.found:
+            ref.issue = "missing"
+            ref.correction_type = "insert"
+
+        refs[service_id] = ref
+
+    return refs
+
+
+def _extract_relevant_paragraph(content: str, search_term: str) -> str:
+    """Extract the paragraph containing the search term."""
+    search_lower = search_term.lower()
+    content_lower = content.lower()
+
+    # Find position of search term
+    pos = content_lower.find(search_lower)
+    if pos == -1:
+        return content[:300]
+
+    # Find sentence/paragraph boundaries
+    # Look backwards for paragraph break
+    start = max(0, content.rfind(".", 0, pos))
+    if start > 0:
+        start += 2  # Skip ". "
+    else:
+        start = max(0, pos - 100)
+
+    # Look forward for end of paragraph
+    end = content.find(".", pos + len(search_term))
+    if end == -1 or end - pos > 500:
+        end = min(len(content), pos + 300)
+    else:
+        end += 1  # Include the period
+
+    return content[start:end].strip()
+
+
+def _find_paragraph_index(content: str, search_term: str) -> int:
+    """Find which paragraph (1-based) contains the search term."""
+    paragraphs = re.split(r"\n\n|\n(?=[A-Z])", content)
+    search_lower = search_term.lower()
+    for i, para in enumerate(paragraphs, 1):
+        if search_lower in para.lower():
+            return i
+    return 0
+
+
+def _find_in_dse_list(service_name: str, dse_services: list[dict]) -> dict | None:
+    """Check if a service appears in the LLM-extracted DSE service list."""
+    name_lower = service_name.lower()
+    for svc in dse_services:
+        dse_name = svc.get("name", "").lower()
+        if name_lower in dse_name or dse_name in name_lower:
+            return svc
+        # Check first word (provider match)
+        if name_lower.split()[0] in dse_name:
+            return svc
+    return None
diff --git a/backend-compliance/compliance/services/dse_parser.py b/backend-compliance/compliance/services/dse_parser.py
new file mode 100644
index 0000000..f10a201
--- /dev/null
+++ b/backend-compliance/compliance/services/dse_parser.py
@@ -0,0 +1,224 @@
+"""
+DSE Parser — parses privacy policy HTML into structured sections.
+
+Extracts headings, section numbers, content blocks and builds a
+hierarchical structure that enables precise text references.
+"""
+
+import logging
+import re
+from dataclasses import dataclass, field
+from html.parser import HTMLParser
+
+logger = logging.getLogger(__name__)
+
+
+@dataclass
+class DSESection:
+    """A section in a privacy policy."""
+    heading: str
+    heading_level: int  # 1-4
+    section_number: str  # "2.5" or "" if no number
+    content: str  # Plain text content
+    html: str  # Original HTML content
+    parent_heading: str = ""
+    url: str = ""
+    element_id: str = ""
+    paragraph_count: int = 0
+
+
+class _HeadingExtractor(HTMLParser):
+    """Extract headings and their content from HTML."""
+
+    def __init__(self):
+        super().__init__()
+        self.sections: list[dict] = []
+        self._current_tag = ""
+        self._in_heading = False
+        self._heading_level = 0
+        self._heading_text = ""
+        self._heading_id = ""
+        self._content_parts: list[str] = []
+        self._html_parts: list[str] = []
+        self._skip_tags = {"script", "style", "nav", "footer", "header"}
+        self._skip_depth = 0
+        self._p_count = 0
+
+    def handle_starttag(self, tag, attrs):
+        attrs_dict = dict(attrs)
+        if tag in self._skip_tags:
+            self._skip_depth += 1
+            return
+        if self._skip_depth > 0:
+            return
+
+        if tag in ("h1", "h2", "h3", "h4"):
+            # Save previous section
+            if self._heading_text:
+                self._save_section()
+            self._in_heading = True
+            self._heading_level = int(tag[1])
+            self._heading_text = ""
+            self._heading_id = attrs_dict.get("id", "")
+            self._content_parts = []
+            self._html_parts = []
+            self._p_count = 0
+
+        if tag == "p":
+            self._p_count += 1
+
+        # Reconstruct HTML
+        attr_str = " ".join(f'{k}="{v}"' for k, v in attrs)
+        self._html_parts.append(f"<{tag}{' ' + attr_str if attr_str else ''}>")
+
+    def handle_endtag(self, tag):
+        if tag in self._skip_tags and self._skip_depth > 0:
+            self._skip_depth -= 1
+            return
+        if self._skip_depth > 0:
+            return
+
+        if tag in ("h1", "h2", "h3", "h4"):
+            self._in_heading = False
+
+        self._html_parts.append(f"</{tag}>")
+
+    def handle_data(self, data):
+        if self._skip_depth > 0:
+            return
+        if self._in_heading:
+            self._heading_text += data.strip()
+        else:
+            self._content_parts.append(data)
+        self._html_parts.append(data)
+
+    def _save_section(self):
+        if not self._heading_text:
+            return
+        content = " ".join(self._content_parts)
+        content = re.sub(r"\s+", " ", content).strip()
+        self.sections.append({
+            "heading": self._heading_text.strip(),
+            "heading_level": self._heading_level,
+            "element_id": self._heading_id,
+            "content": content,
+            "html": "".join(self._html_parts),
+            "paragraph_count": self._p_count,
+        })
+
+    def finalize(self):
+        """Call after feeding all data to save the last section."""
+        if self._heading_text:
+            self._save_section()
+
+
+def parse_dse(html: str, url: str = "") -> list[DSESection]:
+    """Parse privacy policy HTML into structured sections."""
+    extractor = _HeadingExtractor()
+    try:
+        extractor.feed(html)
+        extractor.finalize()
+    except Exception as e:
+        logger.warning("HTML parsing failed, falling back to regex: %s", e)
+        return _regex_fallback(html, url)
+
+    if not extractor.sections:
+        return _regex_fallback(html, url)
+
+    # Build parent hierarchy
+    sections: list[DSESection] = []
+    parent_stack: list[str] = [""]  # Stack of parent headings by level
+
+    for raw in extractor.sections:
+        heading = raw["heading"]
+        level = raw["heading_level"]
+
+        # Extract section number (e.g., "2.5" from "2.5 Webanalyse")
+        num_match = re.match(r"^(\d+(?:\.\d+)*)\s*[.:]?\s*", heading)
+        section_number = num_match.group(1) if num_match else ""
+
+        # Track parent headings
+        while len(parent_stack) > level:
+            parent_stack.pop()
+        parent = parent_stack[-1] if parent_stack else ""
+        parent_stack.append(heading)
+
+        sections.append(DSESection(
+            heading=heading,
+            heading_level=level,
+            section_number=section_number,
+            content=raw["content"][:2000],  # Cap content length
+            html=raw["html"][:3000],
+            parent_heading=parent,
+            url=url,
+            element_id=raw["element_id"],
+            paragraph_count=raw["paragraph_count"],
+        ))
+
+    logger.info("Parsed DSE: %d sections from %s", len(sections), url)
+    return sections
+
+
+def _regex_fallback(html: str, url: str) -> list[DSESection]:
+    """Fallback parser using regex when HTML parsing fails."""
+    # Strip scripts and styles
+    clean = re.sub(r"<(script|style)[^>]*>.*?</\1>", "", html, flags=re.DOTALL | re.IGNORECASE)
+
+    sections = []
+    # Find all headings
+    for match in re.finditer(r"<h([1-4])[^>]*(?:id=[\"']([^\"']*)[\"'])?[^>]*>(.*?)</h\1>", clean, re.DOTALL | re.IGNORECASE):
+        level = int(match.group(1))
+        elem_id = match.group(2) or ""
+        heading = re.sub(r"<[^>]+>", "", match.group(3)).strip()
+
+        # Get content until next heading
+        start = match.end()
+        next_heading = re.search(r"<h[1-4]", clean[start:], re.IGNORECASE)
+        end = start + next_heading.start() if next_heading else start + 2000
+        content = clean[start:end]
+        content = re.sub(r"<[^>]+>", " ", content)
+        content = re.sub(r"\s+", " ", content).strip()
+
+        num_match = re.match(r"^(\d+(?:\.\d+)*)", heading)
+
+        sections.append(DSESection(
+            heading=heading,
+            heading_level=level,
+            section_number=num_match.group(1) if num_match else "",
+            content=content[:2000],
+            html="",
+            url=url,
+            element_id=elem_id,
+        ))
+
+    return sections
+
+
+def find_section_by_content(sections: list[DSESection], search_text: str) -> DSESection | None:
+    """Find the section that contains specific text."""
+    search_lower = search_text.lower()
+    for section in sections:
+        if search_lower in section.content.lower():
+            return section
+    return None
+
+
+def find_section_by_category(sections: list[DSESection], category: str) -> DSESection | None:
+    """Find the section most likely to contain a service category."""
+    category_keywords = {
+        "tracking": ["cookie", "tracking", "webanalyse", "analytics", "statistik"],
+        "marketing": ["marketing", "werbung", "newsletter", "remarketing"],
+        "payment": ["zahlung", "payment", "bezahlung", "zahlungsabwicklung"],
+        "chatbot": ["chat", "kommunikation", "kundenservice", "kontakt"],
+        "cdn": ["hosting", "bereitstellung", "technisch", "infrastruktur", "cdn"],
+        "other": ["sonstig", "weitere", "dritte", "extern"],
+    }
+    keywords = category_keywords.get(category, category_keywords["other"])
+
+    for section in sections:
+        heading_lower = section.heading.lower()
+        content_lower = section.content.lower()[:500]
+        for kw in keywords:
+            if kw in heading_lower or kw in content_lower:
+                return section
+    return None
diff --git a/backend-compliance/compliance/services/legal_basis_validator.py b/backend-compliance/compliance/services/legal_basis_validator.py
new file mode 100644
index 0000000..bf75d8a
--- /dev/null
+++ b/backend-compliance/compliance/services/legal_basis_validator.py
@@ -0,0 +1,179 @@
+"""
+Legal Basis Validator — checks if the correct DSGVO legal basis (lit. a-f)
+is used for each processing purpose in the privacy policy.
+
+⚠️  TECHNISCHE SCHULD / HARDCODED KNOWLEDGE:
+Dieses Modul enthält hartkodierte Rechtsgrundlagen-Zuordnungen (CORRECT_BASIS dict).
+Das ist ein TEMPORAERER Fallback bis die Control Library entsprechende Controls hat.
+
+MITTELFRISTIGES ZIEL: Dieses Dict durch RAG/Control-Library-Abfragen ersetzen.
+Neue Controls sollten in der Pipeline generiert werden, z.B.:
+  "Cookie-Tracking erfordert Art. 6(1)(a) Einwilligung (EuGH C-673/17 Planet49)"
+  → canonical_controls mit scope_conditions + legal_ref
+
+BIS DAHIN: Dieses Dict wird als Fallback genutzt mit einem Warning-Log wenn
+es herangezogen wird. Bei jedem neuen Gesetz/Urteil muss SOWOHL die Pipeline
+als auch dieses Dict aktualisiert werden — oder besser: das Dict entfernen und
+nur noch Controls nutzen.
+
+Erstellt: 2026-04-29 | Review-Datum: 2026-07-01 | Owner: Agent-Team
+
+Common mistakes detected:
+- Cookie tracking on lit. f (legitimate interest) instead of lit. a (consent)
+- Marketing emails on lit. f instead of lit. a
+- Analytics on lit. b (contract) — incorrect overextension
+- Klarna credit check without Art. 22 reference
+"""
+
+import logging
+import re
+from dataclasses import dataclass
+
+logger = logging.getLogger(__name__)
+
+
+@dataclass
+class LitFinding:
+    purpose: str
+    stated_basis: str
+    correct_basis: str
+    severity: str
+    text: str
+    legal_ref: str
+    original_text: str = ""
+
+
+# Purpose → correct legal basis mapping
+# Based on: DSK Kurzpapiere, Planet49 (EuGH C-673/17), BGH Cookie-Urteil
+CORRECT_BASIS: dict[str, dict] = {
+    "cookie_tracking": {
+        "correct": "lit. a (Einwilligung)",
+        "wrong_patterns": ["berechtigtes interesse", "lit. f", "lit.f", "legitimate interest"],
+        "detect_patterns": ["cookie", "tracking", "pixel", "analytics.*cookie"],
+        "ref": "EuGH C-673/17 (Planet49), §25 TDDDG",
+    },
+    "web_analytics": {
+        "correct": "lit. a (Einwilligung)",
+        "wrong_patterns": ["berechtigtes interesse", "lit. f", "lit.f", "vertragserfuellung", "lit. b", "lit.b"],
+        "detect_patterns": ["google analytics", "webanalyse", "web analytics", "reichweitenmessung",
+                            "nutzungsanalyse", "hotjar", "matomo"],
+        "ref": "DSK Orientierungshilfe Telemedien, §25 TDDDG",
+    },
+    "marketing_email": {
+        "correct": "lit. a (Einwilligung)",
+        "wrong_patterns": ["berechtigtes interesse", "lit. f", "lit.f"],
+        "detect_patterns": ["newsletter", "marketing.*mail", "werbe.*mail", "werbe.*email",
+                            "marketing.*email", "werbliche.*kommunikation"],
+        "ref": "Art. 7 DSGVO, §7 UWG (Double Opt-In)",
+    },
+    "remarketing": {
+        "correct": "lit. a (Einwilligung)",
+        "wrong_patterns": ["berechtigtes interesse", "lit. f", "lit.f"],
+        "detect_patterns": ["remarketing", "retargeting", "personalisierte werbung",
+                            "personalized advertising", "custom audience"],
+        "ref": "§25 TDDDG, EuGH C-673/17",
+    },
+    "credit_check": {
+        "correct": "lit. b/f + Art. 22 DSGVO Hinweis",
+        "wrong_patterns": [],  # Not about wrong basis, but missing Art. 22
+        "detect_patterns": ["bonitaet", "bonität", "kreditprüfung", "kreditpruefung",
+                            "schufa", "auskunftei", "klarna.*rechnung", "ratenzahlung"],
+        "ref": "Art. 22 DSGVO (automatisierte Einzelentscheidung)",
+        "must_contain": ["art. 22", "art.22", "automatisierte entscheidung",
+                         "automated decision", "einzelentscheidung"],
+    },
+    "social_media_embed": {
+        "correct": "lit. a (Einwilligung)",
+        "wrong_patterns": ["berechtigtes interesse", "lit. f", "lit.f"],
+        "detect_patterns": ["facebook.*plugin", "social.*plugin", "like.*button",
+                            "share.*button", "instagram.*embed", "twitter.*embed"],
+        "ref": "EuGH C-40/17 (Fashion ID), 2-Klick-Loesung",
+    },
+    "session_recording": {
+        "correct": "lit. a (Einwilligung)",
+        "wrong_patterns": ["berechtigtes interesse", "lit. f", "lit.f"],
+        "detect_patterns": ["session.?recording", "session.?replay", "heatmap",
+                            "mouseflow", "hotjar.*recording", "clarity.*recording",
+                            "fullstory", "lucky orange"],
+        "ref": "§25 TDDDG, Aufzeichnung von Nutzerverhalten",
+    },
+}
+
+
+def validate_legal_bases(dse_text: str) -> list[LitFinding]:
+    """Check if correct legal bases are used in the privacy policy.
+
+    ⚠️  Uses HARDCODED CORRECT_BASIS dict as fallback.
+    TODO: Replace with RAG/Control Library query when lit-mapping Controls exist.
+    """
+    logger.warning(
+        "legal_basis_validator: Using HARDCODED rules (CORRECT_BASIS dict). "
+        "This should be replaced with Control Library queries. Review date: 2026-07-01"
+    )
+    findings = []
+    text_lower = dse_text.lower()
+
+    for purpose_id, rules in CORRECT_BASIS.items():
+        # Step 1: Is this purpose mentioned in the DSE?
+        purpose_found = False
+        matched_text = ""
+        for pattern in rules["detect_patterns"]:
+            match = re.search(pattern, text_lower)
+            if match:
+                purpose_found = True
+                # Extract surrounding context (200 chars)
+                start = max(0, match.start() - 100)
+                end = min(len(text_lower), match.end() + 200)
+                matched_text = dse_text[start:end].strip()
+                break
+
+        if not purpose_found:
+            continue
+
+        context_lower = matched_text.lower()
+
+        # Step 2: Check if wrong legal basis is stated
+        for wrong in rules["wrong_patterns"]:
+            if wrong in context_lower:
+                findings.append(LitFinding(
+                    purpose=purpose_id,
+                    stated_basis=wrong,
+                    correct_basis=rules["correct"],
+                    severity="HIGH",
+                    text=f"Falsche Rechtsgrundlage: '{_purpose_label(purpose_id)}' nutzt "
+                         f"'{wrong}' statt '{rules['correct']}'",
+                    legal_ref=rules["ref"],
+                    original_text=matched_text[:300],
+                ))
+                break
+
+        # Step 3: Special check — must_contain (e.g., Art. 22 for credit checks)
+        if "must_contain" in rules:
+            has_required = any(req in context_lower for req in rules["must_contain"])
+            if not has_required:
+                findings.append(LitFinding(
+                    purpose=purpose_id,
+                    stated_basis="(fehlt)",
+                    correct_basis=rules["correct"],
+                    severity="HIGH",
+                    text=f"Pflichthinweis fehlt: '{_purpose_label(purpose_id)}' erwaehnt "
+                         f"keine automatisierte Entscheidungsfindung ({rules['ref']})",
+                    legal_ref=rules["ref"],
+                    original_text=matched_text[:300],
+                ))
+
+    return findings
+
+
+def _purpose_label(purpose_id: str) -> str:
+    """German label for purpose ID."""
+    labels = {
+        "cookie_tracking": "Cookie-Tracking",
+        "web_analytics": "Webanalyse",
+        "marketing_email": "Marketing-Emails/Newsletter",
+        "remarketing": "Remarketing/Retargeting",
+        "credit_check": "Bonitaetspruefung",
+        "social_media_embed": "Social Media Einbindung",
+        "session_recording": "Session Recording/Heatmaps",
+    }
+    return labels.get(purpose_id, purpose_id)
diff --git a/backend-compliance/compliance/services/mandatory_content_checker.py b/backend-compliance/compliance/services/mandatory_content_checker.py
new file mode 100644
index 0000000..021a264
--- /dev/null
+++ b/backend-compliance/compliance/services/mandatory_content_checker.py
@@ -0,0 +1,302 @@
+"""
+Mandatory Content Checker — verifies that legally required content
+is present on a website. Checks for missing documents, sections,
+and mandatory information within documents.
+
+Knows what MUST be there (not just what IS there).
+"""
+
+import logging
+import re
+from dataclasses import dataclass, field
+
+from compliance.services.dse_parser import DSESection
+
+logger = logging.getLogger(__name__)
+
+
+@dataclass
+class MandatoryFinding:
+    code: str
+    severity: str  # "HIGH", "MEDIUM", "LOW"
+    category: str  # "document_missing", "section_missing", "info_missing"
+    text: str
+    legal_ref: str
+    expected: str  # What should be there
+    suggestion: str = ""  # How to fix
+
+
+# ═══════════════════════════════════════════════════════════════
+# MANDATORY DOCUMENTS (must exist as pages/links on the website)
+# ═══════════════════════════════════════════════════════════════
+
+MANDATORY_DOCUMENTS = [
+    {
+        "id": "impressum",
+        "name": "Impressum",
+        "legal_ref": "§5 TMG, §18 MStV",
+        "patterns": [r"impressum", r"imprint", r"legal.?notice"],
+        "severity": "HIGH",
+    },
+    {
+        "id": "datenschutz",
+        "name": "Datenschutzerklaerung",
+        "legal_ref": "Art. 13/14 DSGVO",
+        "patterns": [r"datenschutz", r"privacy", r"dsgvo"],
+        "severity": "HIGH",
+    },
+    {
+        "id": "agb",
+        "name": "AGB / Nutzungsbedingungen",
+        "legal_ref": "§305 BGB (bei Vertragsschluss)",
+        "patterns": [r"agb", r"nutzungsbedingung", r"terms"],
+        "severity": "MEDIUM",
+        "only_ecommerce": True,  # Nur bei Shops/Buchungsseiten
+    },
+    {
+        "id": "widerruf",
+        "name": "Widerrufsbelehrung",
+        "legal_ref": "§355 BGB, Art. 246a §1 EGBGB (nur Fernabsatz)",
+        "patterns": [r"widerruf", r"cancellation.?policy", r"right.?of.?withdrawal"],
+        "severity": "MEDIUM",
+        "only_ecommerce": True,  # Nur bei Fernabsatzvertraegen
+    },
+]
+
+
+# ═══════════════════════════════════════════════════════════════
+# MANDATORY DSE SECTIONS (Art. 13 DSGVO Pflichtangaben)
+# ═══════════════════════════════════════════════════════════════
+
+MANDATORY_DSE_CONTENT = [
+    {
+        "id": "verantwortlicher",
+        "name": "Name und Kontakt des Verantwortlichen",
+        "legal_ref": "Art. 13 Abs. 1 lit. a DSGVO",
+        "keywords": ["verantwortlich", "responsible", "controller", "betreiber"],
+        "severity": "HIGH",
+    },
+    {
+        "id": "dsb_kontakt",
+        "name": "Kontaktdaten des Datenschutzbeauftragten",
+        "legal_ref": "Art. 13 Abs. 1 lit. b DSGVO",
+        "keywords": ["datenschutzbeauftragt", "data protection officer", "dsb", "dpo",
+                      "behördlichen datenschutz", "behoerdlichen datenschutz",
+                      "datenschutz@", "datenschutzbeauftragter"],
+        "severity": "HIGH",
+    },
+    {
+        "id": "zwecke",
+        "name": "Zwecke der Datenverarbeitung",
+        "legal_ref": "Art. 13 Abs. 1 lit. c DSGVO",
+        "keywords": ["zweck", "purpose", "verarbeitungszweck", "verarbeitungszwecke",
+                      "wozu", "wofuer", "zu welchem zweck", "nutzungszweck",
+                      "zweck und rechtsgrundlage", "zwecke der verarbeitung"],
+        "severity": "HIGH",
+    },
+    {
+        "id": "rechtsgrundlage",
+        "name": "Rechtsgrundlagen der Verarbeitung",
+        "legal_ref": "Art. 13 Abs. 1 lit. c DSGVO",
+        "keywords": ["rechtsgrundlage", "legal basis", "art. 6", "art.6",
+                      "berechtigtes interesse", "einwilligung", "vertragserfuellung",
+                      "vertragserfüllung", "rechtliche verpflichtung"],
+        "severity": "HIGH",
+    },
+    {
+        "id": "speicherdauer",
+        "name": "Speicherdauer / Loeschfristen",
+        "legal_ref": "Art. 13 Abs. 2 lit. a DSGVO",
+        "keywords": ["speicherdauer", "aufbewahrung", "loeschung", "loeschfrist",
+                      "storage period", "retention", "deletion"],
+        "severity": "HIGH",
+    },
+    {
+        "id": "betroffenenrechte",
+        "name": "Betroffenenrechte (Auskunft, Loeschung, etc.)",
+        "legal_ref": "Art. 13 Abs. 2 lit. b-d DSGVO",
+        "keywords": ["betroffenenrecht", "auskunft", "berichtigung", "loeschung",
+                      "einschraenkung", "widerspruch", "data subject rights",
+                      "right to access", "right to erasure"],
+        "severity": "HIGH",
+    },
+    {
+        "id": "beschwerderecht",
+        "name": "Beschwerderecht bei Aufsichtsbehoerde",
+        "legal_ref": "Art. 13 Abs. 2 lit. d DSGVO",
+        "keywords": ["aufsichtsbehoerde", "aufsichtsbehörde", "beschwerde",
+                      "supervisory authority", "datenschutzbehoerde",
+                      "landesbeauftragte", "bundesdatenschutz", "bfdi"],
+        "severity": "MEDIUM",
+    },
+    {
+        "id": "drittlandtransfer",
+        "name": "Drittlandtransfer-Information",
+        "legal_ref": "Art. 13 Abs. 1 lit. f DSGVO",
+        "keywords": ["drittland", "drittst", "third countr", "usa", "transfer",
+                      "standardvertragsklausel", "adequacy"],
+        "severity": "MEDIUM",
+    },
+    {
+        "id": "automatisierte_entscheidung",
+        "name": "Automatisierte Entscheidungsfindung / Profiling",
+        "legal_ref": "Art. 13 Abs. 2 lit. f DSGVO",
+        "keywords": ["automatisiert", "profiling", "automated decision", "scoring"],
+        "severity": "MEDIUM",
+    },
+]
+
+
+# ═══════════════════════════════════════════════════════════════
+# MANDATORY IMPRESSUM CONTENT (§5 TMG)
+# ═══════════════════════════════════════════════════════════════
+
+MANDATORY_IMPRESSUM_CONTENT = [
+    {
+        "id": "geschaeftsfuehrer",
+        "name": "Geschaeftsfuehrer / Vertretungsberechtigter",
+        "legal_ref": "§5 Abs. 1 Nr. 1 TMG",
+        "keywords": ["geschaeftsfuehrer", "geschäftsführer", "ceo", "managing director",
+                      "vertretungsberechtig", "vorstand"],
+        "severity": "HIGH",
+    },
+    {
+        "id": "handelsregister",
+        "name": "Handelsregisternummer",
+        "legal_ref": "§5 Abs. 1 Nr. 4 TMG",
+        "keywords": ["handelsregister", "hrb", "hra", "amtsgericht", "registergericht",
+                      "commercial register"],
+        "severity": "HIGH",
+    },
+    {
+        "id": "ust_id",
+        "name": "Umsatzsteuer-Identifikationsnummer",
+        "legal_ref": "§5 Abs. 1 Nr. 6 TMG",
+        "keywords": ["ust-id", "ust.-id", "umsatzsteuer", "vat", "de\\d{9}"],
+        "severity": "MEDIUM",
+    },
+    {
+        "id": "anschrift",
+        "name": "Anschrift (Strasse, PLZ, Ort)",
+        "legal_ref": "§5 Abs. 1 Nr. 1 TMG",
+        "keywords": ["str.", "straße", "strasse", "plz", "postleitzahl"],
+        "severity": "HIGH",
+    },
+    {
+        "id": "kontakt",
+        "name": "Kontaktmoeglichkeit (Email oder Telefon)",
+        "legal_ref": "§5 Abs. 1 Nr. 2 TMG",
+        "keywords": ["@", "telefon", "phone", "e-mail", "email", "kontakt"],
+        "severity": "HIGH",
+    },
+]
+
+
+ECOMMERCE_INDICATORS = [
+    r"warenkorb", r"cart", r"shop", r"bestell", r"order",
+    r"checkout", r"kasse", r"buy", r"kaufen", r"add.?to.?cart",
+    r"stripe|paypal|klarna|mollie|adyen",  # Payment providers
+]
+
+
+def _is_ecommerce(scanned_pages: list[str], html_content: str = "") -> bool:
+    """Detect if website is an e-commerce/transactional site."""
+    all_text = " ".join(scanned_pages).lower() + " " + html_content.lower()
+    return any(re.search(p, all_text) for p in ECOMMERCE_INDICATORS)
+
+
+def check_mandatory_documents(
+    scanned_pages: list[str], page_status: dict[str, int],
+    html_content: str = "",
+) -> list[MandatoryFinding]:
+    """Check if mandatory documents/pages exist on the website."""
+    findings = []
+    is_shop = _is_ecommerce(scanned_pages, html_content)
+
+    for doc in MANDATORY_DOCUMENTS:
+        # Skip e-commerce-only checks for non-shop websites
+        if doc.get("only_ecommerce") and not is_shop:
+            continue
+
+        found = False
+        for page in scanned_pages:
+            if any(re.search(p, page, re.IGNORECASE) for p in doc["patterns"]):
+                status = page_status.get(page, 200)
+                if status < 400:
+                    found = True
+                else:
+                    findings.append(MandatoryFinding(
+                        code=f"DOC-ERROR-{doc['id'].upper()}",
+                        severity="HIGH",
+                        category="document_error",
+                        text=f"{doc['name']} existiert aber gibt HTTP {status} zurueck (Ladefehler!)",
+                        legal_ref=doc["legal_ref"],
+                        expected=doc["name"],
+                        suggestion=f"Seite {page} ist nicht erreichbar. Pruefen ob ein Deployment-Fehler vorliegt.",
+                    ))
+                    found = True  # Exists but broken
+                break
+
+        if not found:
+            findings.append(MandatoryFinding(
+                code=f"DOC-MISSING-{doc['id'].upper()}",
+                severity=doc["severity"],
+                category="document_missing",
+                text=f"{doc['name']} nicht auf der Website gefunden ({doc['legal_ref']})",
+                legal_ref=doc["legal_ref"],
+                expected=f"Link zu {doc['name']} muss von jeder Seite erreichbar sein",
+            ))
+
+    return findings
+
+
+def check_dse_mandatory_content(
+    sections: list[DSESection], full_text: str,
+) -> list[MandatoryFinding]:
+    """Check if privacy policy contains all mandatory sections per Art. 13 DSGVO."""
+    findings = []
+    text_lower = full_text.lower()
+
+    for req in MANDATORY_DSE_CONTENT:
+        found = any(kw in text_lower for kw in req["keywords"])
+        if not found:
+            # Also check section headings
+            found = any(
+                any(kw in s.heading.lower() or kw in s.content.lower()[:200]
+                    for kw in req["keywords"])
+                for s in sections
+            )
+
+        if not found:
+            findings.append(MandatoryFinding(
+                code=f"DSE-CONTENT-{req['id'].upper()}",
+                severity=req["severity"],
+                category="section_missing",
+                text=f"Pflichtangabe fehlt: {req['name']} ({req['legal_ref']})",
+                legal_ref=req["legal_ref"],
+                expected=req["name"],
+            ))
+
+    return findings
+
+
+def check_impressum_mandatory_content(
+    impressum_text: str,
+) -> list[MandatoryFinding]:
+    """Check if Impressum contains all mandatory info per §5 TMG."""
+    findings = []
+    text_lower = impressum_text.lower()
+
+    for req in MANDATORY_IMPRESSUM_CONTENT:
+        found = any(re.search(kw, text_lower) for kw in req["keywords"])
+        if not found:
+            findings.append(MandatoryFinding(
+                code=f"IMP-CONTENT-{req['id'].upper()}",
+                severity=req["severity"],
+                category="info_missing",
+                text=f"Impressum: {req['name']} fehlt ({req['legal_ref']})",
+                legal_ref=req["legal_ref"],
+                expected=req["name"],
+            ))
+
+    return findings