feat: add competitor name blocker guardrail

litellm/proxy/_new_secret_config.yaml

@@ -24,6 +24,33 @@ guardrails:
       guardrail: mcp_end_user_permission
       mode: pre_call
       default_on: true
+  - guardrail_name: "airline-competitor-intent"
+    guardrail_id: "airline-competitor-intent"
+    litellm_params:
+      guardrail: litellm_content_filter
+      mode: pre_call
+      default_on: false
+      competitor_intent_config:
+        brand_self:
+          - emirates
+          - ek
+        competitors:
+          - qatar airways
+          - qatar
+          - etihad
+        locations:
+          - qatar
+          - doha
+          - doh
+        competitor_aliases:
+          qatar airways: [qr, doha airline]
+          qatar: [qr]
+        policy:
+          competitor_comparison: refuse
+          possible_competitor_comparison: reframe
+        threshold_high: 0.70
+        threshold_medium: 0.45
+        threshold_low: 0.30
 
 mcp_servers:
   my_http_server:

litellm/proxy/guardrails/guardrail_hooks/litellm_content_filter/__init__.py

@@ -1,9 +1,8 @@
 from typing import TYPE_CHECKING, Optional
 
 import litellm
-from litellm.proxy.guardrails.guardrail_hooks.litellm_content_filter.content_filter import (
-    ContentFilterGuardrail,
-)
+from litellm.proxy.guardrails.guardrail_hooks.litellm_content_filter.content_filter import \
+    ContentFilterGuardrail
 from litellm.types.guardrails import SupportedGuardrailIntegrations
 
 if TYPE_CHECKING:
@@ -44,6 +43,9 @@ def initialize_guardrail(
         severity_threshold=getattr(litellm_params, "severity_threshold", "medium"),
         llm_router=llm_router,
         image_model=getattr(litellm_params, "image_model", None),
+        competitor_intent_config=getattr(
+            litellm_params, "competitor_intent_config", None
+        ),
     )
 
     litellm.logging_callback_manager.add_litellm_callback(content_filter_guardrail)

litellm/proxy/guardrails/guardrail_hooks/litellm_content_filter/competitor_intent/__init__.py

@@ -0,0 +1,17 @@
+"""
+Competitor intent: entity + intent disambiguation with safe (non-competitor) defaults.
+
+Base logic in base.py; industry-specific checkers in submodules (e.g. airline.py).
+"""
+
+from litellm.proxy.guardrails.guardrail_hooks.litellm_content_filter.competitor_intent.airline import \
+    AirlineCompetitorIntentChecker
+from litellm.proxy.guardrails.guardrail_hooks.litellm_content_filter.competitor_intent.base import (
+    BaseCompetitorIntentChecker, normalize, text_for_entity_matching)
+
+__all__ = [
+    "BaseCompetitorIntentChecker",
+    "AirlineCompetitorIntentChecker",
+    "normalize",
+    "text_for_entity_matching",
+]

litellm/proxy/guardrails/guardrail_hooks/litellm_content_filter/competitor_intent/airline.py

@@ -0,0 +1,144 @@
+"""
+Airline-specific competitor intent: other meaning (e.g. location/travel context) vs competitor airline.
+
+Uses context-based disambiguation only: no hardcoded place lists. Detects travel-location
+language (prepositions, travel verbs, booking/entry nouns) vs airline context (airways,
+carrier, lounge, miles, etc.) and scores to decide OTHER_MEANING vs COMPETITOR.
+"""
+
+from typing import Any, Dict, List, Tuple
+
+from litellm.proxy.guardrails.guardrail_hooks.litellm_content_filter.competitor_intent.base import (
+    BaseCompetitorIntentChecker, _compile_marker, _count_signals,
+    _word_boundary_match)
+
+# Location/travel context: prepositions, travel verbs, booking nouns, entry/geo nouns.
+# No place-name list; these patterns detect "destination context" generically.
+AIRLINE_OTHER_MEANING_SIGNALS = [
+    # Travel verb + preposition (e.g. "fly to", "layover in")
+    r"\b(fly|flying|travel|traveling|going|visit|visiting|transit|layover|stopover)\b.{0,12}\b(to|from|via|in|at|through|into)\b",
+    # Booking + preposition
+    r"\bflight(s)?\b.{0,10}\b(to|from|via)\b",
+    r"\bticket(s)?\b.{0,8}\b(to|for)\b",
+    r"\bfare(s)?\b.{0,8}\b(to)\b",
+    # Entry/geo/booking single words
+    r"\bvisa\b",
+    r"\bimmigration\b",
+    r"\bcustoms\b",
+    r"\bentry\b",
+    r"\bairport\b",
+    r"\bterminal\b",
+    r"\bgate\b",
+    r"\bdeparture\b",
+    r"\barrival\b",
+    r"\bitinerary\b",
+    r"\bweather\b",
+    r"\bhotel\b",
+    r"\bcity\b",
+    # Prepositions alone (weaker; often near a place)
+    r"\bto\s+",
+    r"\bfrom\s+",
+    r"\bin\s+",
+    r"\bat\s+",
+    r"\bvia\s+",
+]
+
+# Airline context: carrier/airline language, cabin, loyalty, operations.
+# If ambiguous token appears near these → treat as COMPETITOR.
+AIRLINE_COMPETITOR_SIGNALS = [
+    r"\bairways?\b",
+    r"\bairline\b",
+    r"\bcarrier\b",
+    r"\bcabin\s+crew\b",
+    r"\bflight\s+attendant\b",
+    r"\bbusiness\s+class\b",
+    r"\bfirst\s+class\b",
+    r"\beconomy\b",
+    r"\blounge\b",
+    r"\bbaggage\s+allowance\b",
+    r"\bcheck[- ]?in\b",
+    r"\bmiles\b",
+    r"\bloyalty\b",
+    r"\bstatus\b",
+    r"\bfrequent\s+flyer\b",
+    r"\bfleet\b",
+    r"\baircraft\b",
+    # Comparison/ranking
+    r"\bbetter\b",
+    r"\bbest\b",
+    r"\bgood\b",
+    r"\bas\s+good\s+as\b",
+    r"\bvs\.?\b",
+    r"\bversus\b",
+    r"\bcompare\b",
+    r"\balternative\b",
+    r"\bcompetitor\b",
+    # Brand-specific (optional; config can extend)
+    r"\bqmiles\b",
+    r"\bprivilege\s+club\b",
+]
+
+# Explicit markers: strong override when present.
+AIRLINE_EXPLICIT_COMPETITOR_MARKER = r"\b(airways?|airline|carrier)\b"
+AIRLINE_EXPLICIT_OTHER_MEANING_MARKER = (
+    r"\b(fly|travel|going|visit|layover|stopover|transit)\b.{0,12}\b(to|in|via|from)\b.{0,8}\b"
+)
+
+
+class AirlineCompetitorIntentChecker(BaseCompetitorIntentChecker):
+    """
+    Disambiguates other meaning (e.g. country/city/airport) vs competitor airline
+    (e.g. "Qatar" → country vs Qatar Airways). Overrides _classify_ambiguous
+    with other_meaning/competitor signals and explicit markers.
+    """
+
+    def __init__(self, config: Dict[str, Any]) -> None:
+        merged: Dict[str, Any] = dict(config)
+        if not merged.get("other_meaning_signals"):
+            merged["other_meaning_signals"] = AIRLINE_OTHER_MEANING_SIGNALS
+        if not merged.get("competitor_signals"):
+            merged["competitor_signals"] = AIRLINE_COMPETITOR_SIGNALS
+        # Optional: no default place list; config can add other_meaning_anchors for extra patterns
+        if "other_meaning_anchors" not in merged:
+            merged["other_meaning_anchors"] = []
+        if not merged.get("explicit_competitor_marker"):
+            merged["explicit_competitor_marker"] = AIRLINE_EXPLICIT_COMPETITOR_MARKER
+        if not merged.get("explicit_other_meaning_marker"):
+            merged["explicit_other_meaning_marker"] = AIRLINE_EXPLICIT_OTHER_MEANING_MARKER
+        super().__init__(merged)
+        self._other_meaning_signals = list(merged.get("other_meaning_signals") or [])
+        self._competitor_signals = list(merged.get("competitor_signals") or [])
+        self._other_meaning_anchors = list(merged.get("other_meaning_anchors") or [])
+        self._explicit_competitor_marker = _compile_marker(
+            merged.get("explicit_competitor_marker")
+        )
+        self._explicit_other_meaning_marker = _compile_marker(
+            merged.get("explicit_other_meaning_marker")
+        )
+
+    def _classify_ambiguous(self, text: str, token: str) -> Tuple[str, float]:
+        """Other meaning vs competitor using airline signals and explicit markers."""
+        text_lower = text.lower()
+        if self._explicit_competitor_marker and self._explicit_competitor_marker.search(
+            text_lower
+        ) and _word_boundary_match(text_lower, token.lower()):
+            return "COMPETITOR", 0.85
+        if self._explicit_other_meaning_marker and self._explicit_other_meaning_marker.search(
+            text_lower
+        ):
+            return "OTHER_MEANING", 0.85
+        # Score: location/travel context vs airline context (no place-name list)
+        other_count = _count_signals(text_lower, self._other_meaning_signals)
+        if self._other_meaning_anchors:
+            other_count += _count_signals(text_lower, self._other_meaning_anchors)
+        comp_count = _count_signals(text_lower, self._competitor_signals)
+        total = other_count + comp_count
+        if total == 0:
+            return "OTHER_MEANING", 0.5
+        other_ratio = other_count / total
+        comp_ratio = comp_count / total
+        if other_ratio >= 0.6:
+            return "OTHER_MEANING", min(0.9, 0.5 + 0.4 * other_ratio)
+        if comp_ratio >= 0.6:
+            return "COMPETITOR", min(0.9, 0.5 + 0.4 * comp_ratio)
+        return "OTHER_MEANING", 0.5

litellm/proxy/guardrails/guardrail_hooks/litellm_content_filter/competitor_intent/base.py

@@ -0,0 +1,241 @@
+"""
+Generic competitor intent checker: two entity sets and overridable disambiguation.
+"""
+
+import re
+import unicodedata
+from typing import Any, Dict, List, Optional, Pattern, Set, Tuple, cast
+
+from litellm.types.proxy.guardrails.guardrail_hooks.litellm_content_filter import (
+    CompetitorActionHint,
+    CompetitorIntentEvidenceEntry,
+    CompetitorIntentResult,
+)
+
+ZERO_WIDTH = re.compile(r"[\u200b-\u200d\u2060\ufeff]")
+LEET = {"@": "a", "4": "a", "0": "o", "3": "e", "1": "i", "5": "s", "7": "t"}
+
+OTHER_MEANING_DEFAULT_THRESHOLD = 0.65  # Below this → treat as non-competitor (safe default).
+
+
+def normalize(text: str) -> str:
+    """Lowercase, NFKC, strip zero-width, leetspeak, collapse spaces."""
+    if not text or not isinstance(text, str):
+        return ""
+    t = ZERO_WIDTH.sub("", text)
+    t = unicodedata.normalize("NFKC", t).lower().strip()
+    for c, r in LEET.items():
+        t = t.replace(c, r)
+    return re.sub(r"\s+", " ", t)
+
+
+def _word_boundary_match(text: str, token: str) -> bool:
+    """True if token appears as a word in text."""
+    return bool(re.search(r"\b" + re.escape(token) + r"\b", text))
+
+
+def _count_signals(text: str, patterns: List[str]) -> int:
+    """Count how many of the patterns appear in text."""
+    return sum(1 for p in patterns if re.search(p, text, re.IGNORECASE))
+
+
+def _compile_marker(pattern: Optional[str]) -> Optional[Pattern[str]]:
+    """Compile optional regex string to a pattern."""
+    if not pattern or not pattern.strip():
+        return None
+    try:
+        return re.compile(pattern, re.IGNORECASE)
+    except re.error:
+        return None
+
+
+def text_for_entity_matching(text: str) -> str:
+    """Letters-only variant for entity matching (e.g. split punctuation)."""
+    t = re.sub(r"[^\w\s]", " ", text)
+    return re.sub(r"\s+", " ", t).strip()
+
+
+class BaseCompetitorIntentChecker:
+    """
+    Generic competitor intent checker with two entity sets. Ambiguous tokens
+    (competitor + other-meaning, e.g. location) are classified by overridable
+    _classify_ambiguous(). Base implementation: treat as non-competitor.
+    """
+
+    def __init__(self, config: Dict[str, Any]) -> None:
+        self.brand_self: List[str] = [
+            s.lower().strip() for s in (config.get("brand_self") or []) if s
+        ]
+        competitors: List[str] = [
+            s.lower().strip() for s in (config.get("competitors") or []) if s
+        ]
+        aliases_map: Dict[str, List[str]] = config.get("competitor_aliases") or {}
+        self.competitor_canonical: Dict[str, str] = {}
+        self._competitor_tokens: Set[str] = set()
+        for c in competitors:
+            self._competitor_tokens.add(c)
+            self.competitor_canonical[c] = c
+            for a in (aliases_map.get(c) or []):
+                a = a.lower().strip()
+                if a:
+                    self._competitor_tokens.add(a)
+                    self.competitor_canonical[a] = c
+
+        other: List[str] = [
+            s.lower().strip() for s in (config.get("locations") or []) if s
+        ]
+        self._other_meaning_tokens: Set[str] = set(other)
+        self._ambiguous: Set[str] = self._competitor_tokens & self._other_meaning_tokens
+
+        self.policy: Dict[str, str] = config.get("policy") or {}
+        self.threshold_high = float(config.get("threshold_high", 0.70))
+        self.threshold_medium = float(config.get("threshold_medium", 0.45))
+        self.threshold_low = float(config.get("threshold_low", 0.30))
+        self.reframe_message_template: Optional[str] = config.get(
+            "reframe_message_template"
+        )
+        self.refuse_message_template: Optional[str] = config.get(
+            "refuse_message_template"
+        )
+        self._comparison_words: List[str] = list(
+            config.get("comparison_words")
+            or ["better", "worse", "best", "vs", "versus", "compare", "alternative", "recommend"]
+        )
+
+    def _classify_ambiguous(self, text: str, token: str) -> Tuple[str, float]:
+        """
+        Override in subclasses for industry-specific logic. Base: treat as non-competitor.
+        """
+        return "OTHER_MEANING", 0.5
+
+    def _find_matches(self, text: str) -> List[Tuple[str, str, bool]]:
+        """Find competitor matches; mark ambiguous (also in other-meaning set)."""
+        normalized = normalize(text)
+        found: List[Tuple[str, str, bool]] = []
+        seen: Set[Tuple[str, str]] = set()
+        for token in self._competitor_tokens:
+            if not _word_boundary_match(normalized, token):
+                continue
+            canonical = self.competitor_canonical.get(token, token)
+            key = (token, canonical)
+            if key in seen:
+                continue
+            seen.add(key)
+            is_ambig = token in self._ambiguous or token in self._other_meaning_tokens
+            found.append((token, canonical, is_ambig))
+        return found
+
+    def run(self, text: str) -> CompetitorIntentResult:
+        """Classify competitor intent; non-competitor when ambiguous or low confidence."""
+        normalized = normalize(text)
+        evidence: List[CompetitorIntentEvidenceEntry] = []
+        entities: Dict[str, List[str]] = {
+            "brand_self": [],
+            "competitors": [],
+            "category": [],
+        }
+
+        for b in self.brand_self:
+            if _word_boundary_match(normalized, b):
+                entities["brand_self"].append(b)
+                evidence.append(
+                    {"type": "entity", "key": "brand_self", "value": b, "match": b}
+                )
+
+        matches = self._find_matches(text)
+        if not matches:
+            return {
+                "intent": "other",
+                "confidence": 0.0,
+                "entities": entities,
+                "signals": [],
+                "action_hint": "allow",
+                "evidence": evidence,
+            }
+
+        competitor_resolved: List[str] = []
+        for token, canonical, is_ambig in matches:
+            if not is_ambig:
+                competitor_resolved.append(canonical)
+                evidence.append(
+                    {
+                        "type": "entity",
+                        "key": "competitor",
+                        "value": canonical,
+                        "match": token,
+                    }
+                )
+                continue
+            label, conf = self._classify_ambiguous(normalized, token)
+            if label == "OTHER_MEANING":
+                evidence.append(
+                    {"type": "signal", "key": "other_meaning", "match": token}
+                )
+                continue
+            if label == "COMPETITOR":
+                competitor_resolved.append(canonical)
+                evidence.append(
+                    {
+                        "type": "entity",
+                        "key": "competitor",
+                        "value": canonical,
+                        "match": token,
+                    }
+                )
+                if conf < OTHER_MEANING_DEFAULT_THRESHOLD:
+                    competitor_resolved.pop()
+                    evidence.append(
+                        {
+                            "type": "signal",
+                            "key": "other_meaning_default",
+                            "match": f"confidence {conf:.2f}",
+                        }
+                    )
+                    continue
+
+        entities["competitors"] = list(dict.fromkeys(competitor_resolved))
+
+        if not competitor_resolved:
+            return {
+                "intent": "other",
+                "confidence": 0.0,
+                "entities": entities,
+                "signals": ["other_meaning_or_ambiguous"],
+                "action_hint": "allow",
+                "evidence": evidence,
+            }
+
+        has_comparison = any(
+            re.search(r"\b" + re.escape(w) + r"\b", normalized)
+            for w in self._comparison_words
+        )
+        if has_comparison:
+            evidence.append(
+                {"type": "signal", "key": "comparison", "match": "comparison language"}
+            )
+        confidence = 0.75 if has_comparison else 0.55
+        if confidence >= self.threshold_high:
+            intent = "competitor_comparison"
+        elif confidence >= self.threshold_medium:
+            intent = "possible_competitor_comparison"
+        elif confidence >= self.threshold_low:
+            intent = "log_only"
+        else:
+            intent = "other"
+
+        action_hint: CompetitorActionHint = cast(
+            CompetitorActionHint, self.policy.get(intent, "allow")
+        )
+        if intent == "log_only":
+            action_hint = "log_only"
+        if intent == "other":
+            action_hint = "allow"
+
+        return {
+            "intent": intent,
+            "confidence": round(confidence, 2),
+            "entities": entities,
+            "signals": ["competitor_resolved"] + (["comparison"] if has_comparison else []),
+            "action_hint": action_hint,
+            "evidence": evidence,
+        }

litellm/proxy/guardrails/guardrail_hooks/litellm_content_filter/content_filter.py

@@ -51,11 +51,14 @@ from litellm.types.guardrails import (
 from litellm.types.proxy.guardrails.guardrail_hooks.litellm_content_filter import (
     BlockedWordDetection,
     CategoryKeywordDetection,
+    CompetitorIntentDetection,
+    CompetitorIntentResult,
     ContentFilterCategoryConfig,
     ContentFilterDetection,
     PatternDetection,
 )
 
+from .competitor_intent import AirlineCompetitorIntentChecker
 from .patterns import PATTERN_EXTRA_CONFIG, get_compiled_pattern
 
 MAX_KEYWORD_VALUE_GAP_WORDS = 1
@@ -152,6 +155,7 @@ class ContentFilterGuardrail(CustomGuardrail):
         severity_threshold: str = "medium",
         llm_router: Optional[Router] = None,
         image_model: Optional[str] = None,
+        competitor_intent_config: Optional[Dict[str, Any]] = None,
         **kwargs,
     ):
         """
@@ -202,6 +206,22 @@ class ContentFilterGuardrail(CustomGuardrail):
             {}
         )  # category_name -> {identifier_words, block_words, action, severity}
 
+        # Competitor intent checker (optional, generic; industry presets add domain_words etc.)
+        self._competitor_intent_checker: Optional[AirlineCompetitorIntentChecker] = None
+        if competitor_intent_config and isinstance(competitor_intent_config, dict):
+            try:
+                self._competitor_intent_checker = AirlineCompetitorIntentChecker(
+                    competitor_intent_config
+                )
+                verbose_proxy_logger.debug(
+                    "ContentFilterGuardrail: competitor intent checker enabled"
+                )
+            except Exception as e:
+                verbose_proxy_logger.warning(
+                    "ContentFilterGuardrail: failed to init competitor intent checker: %s",
+                    e,
+                )
+
         # Load categories if provided
         if categories:
             self._load_categories(categories)
@@ -1158,9 +1178,7 @@ class ContentFilterGuardrail(CustomGuardrail):
                 pattern_name=pattern_name.upper()
             )
             text = self._mask_spans(text, spans, redaction_tag)
-            verbose_proxy_logger.info(
-                f"Masked all {pattern_name} matches in content"
-            )
+            verbose_proxy_logger.info(f"Masked all {pattern_name} matches in content")
 
         return text
 
@@ -1383,7 +1401,9 @@ class ContentFilterGuardrail(CustomGuardrail):
             masked_entity_count: Dictionary to update with counts
         """
         for detection in detections:
-            if detection["action"] == ContentFilterAction.MASK.value:
+            if detection.get("type") == "competitor_intent":
+                continue
+            if detection.get("action") == ContentFilterAction.MASK.value:
                 detection_type = detection["type"]
                 if detection_type == "pattern":
                     pattern_detection = cast(PatternDetection, detection)
@@ -1409,18 +1429,27 @@ class ContentFilterGuardrail(CustomGuardrail):
         """Build match_details list from content filter detections."""
         match_details: List[dict] = []
         for detection in detections:
-            detail: dict = {"type": detection["type"], "action_taken": detection["action"]}
+            action_taken = detection.get("action", detection.get("action_hint", ""))
+            detail: dict = {"type": detection["type"], "action_taken": action_taken}
             if detection["type"] == "pattern":
                 detail["detection_method"] = "regex"
-                detail["snippet"] = cast(PatternDetection, detection).get("pattern_name", "")
+                detail["snippet"] = cast(PatternDetection, detection).get(
+                    "pattern_name", ""
+                )
             elif detection["type"] == "blocked_word":
                 detail["detection_method"] = "keyword"
-                detail["snippet"] = cast(BlockedWordDetection, detection).get("keyword", "")
+                detail["snippet"] = cast(BlockedWordDetection, detection).get(
+                    "keyword", ""
+                )
             elif detection["type"] == "category_keyword":
                 detail["detection_method"] = "keyword"
                 cat_det = cast(CategoryKeywordDetection, detection)
                 detail["snippet"] = cat_det.get("keyword", "")
                 detail["category"] = cat_det.get("category", "")
+            elif detection["type"] == "competitor_intent":
+                detail["detection_method"] = "intent"
+                detail["snippet"] = detection.get("intent", "")
+                detail["confidence"] = detection.get("confidence")
             match_details.append(detail)
         return match_details
 
@@ -1430,19 +1459,28 @@ class ContentFilterGuardrail(CustomGuardrail):
         for detection in detections:
             if detection["type"] == "pattern":
                 methods.add("regex")
+            elif detection["type"] == "competitor_intent":
+                methods.add("intent")
             else:
                 methods.add("keyword")
         return ",".join(sorted(methods)) if methods else ""
 
     def _get_patterns_checked_count(self) -> int:
         """Get total number of patterns and keywords that were evaluated."""
-        return len(self.compiled_patterns) + len(self.blocked_words) + len(self.category_keywords)
+        return (
+            len(self.compiled_patterns)
+            + len(self.blocked_words)
+            + len(self.category_keywords)
+        )
 
     def _get_policy_templates(self) -> Optional[str]:
         """Get comma-separated policy template names from loaded categories."""
         if not self.loaded_categories:
             return None
-        names = [cat.description or cat.category_name for cat in self.loaded_categories.values()]
+        names = [
+            cat.description or cat.category_name
+            for cat in self.loaded_categories.values()
+        ]
         return ", ".join(names) if names else None
 
     def _compute_risk_score(
@@ -1480,6 +1518,72 @@ class ContentFilterGuardrail(CustomGuardrail):
 
         return round(min(10.0, score), 1)
 
+    def _apply_competitor_intent_policy(
+        self,
+        intent_result: CompetitorIntentResult,
+        request_data: dict,
+        detections: List[ContentFilterDetection],
+    ) -> None:
+        """
+        Apply policy for competitor intent result: refuse (raise), reframe (passthrough), or log_only/allow (return).
+        Appends competitor_intent detection to detections. Never returns for refuse/reframe.
+        """
+        intent_val = intent_result.get("intent", "other")
+        confidence_val = intent_result.get("confidence", 0.0)
+        action_hint_val = intent_result.get("action_hint", "allow")
+        evidence_list = intent_result.get("evidence", [])
+        detection: CompetitorIntentDetection = {
+            "type": "competitor_intent",
+            "intent": intent_val,
+            "confidence": confidence_val,
+            "action_hint": action_hint_val,
+            "entities": intent_result.get("entities", {}),
+            "signals": intent_result.get("signals", []),
+            "evidence": [dict(e) for e in evidence_list],
+        }
+        detections.append(detection)
+
+        if action_hint_val == "refuse":
+            msg = "Content blocked: competitor comparison or ranking intent detected."
+            if self._competitor_intent_checker and getattr(
+                self._competitor_intent_checker, "refuse_message_template", None
+            ):
+                msg = self._competitor_intent_checker.refuse_message_template or msg
+            verbose_proxy_logger.warning(
+                "ContentFilterGuardrail: competitor intent refuse - %s", intent_val
+            )
+            raise HTTPException(
+                status_code=403,
+                detail={
+                    "error": msg,
+                    "intent": intent_val,
+                    "confidence": confidence_val,
+                },
+            )
+        if action_hint_val == "reframe":
+            msg = (
+                "I can help with questions about our products and services. "
+                "Would you like to compare specific features or get more information?"
+            )
+            if self._competitor_intent_checker and getattr(
+                self._competitor_intent_checker, "reframe_message_template", None
+            ):
+                msg = self._competitor_intent_checker.reframe_message_template or msg
+            verbose_proxy_logger.info(
+                "ContentFilterGuardrail: competitor intent reframe - %s", intent_val
+            )
+            self.raise_passthrough_exception(
+                violation_message=msg,
+                request_data=request_data,
+                detection_info=dict(intent_result),
+            )
+        # log_only or allow: just log (detection already appended)
+        verbose_proxy_logger.debug(
+            "ContentFilterGuardrail: competitor intent %s (action_hint=%s)",
+            intent_val,
+            action_hint_val,
+        )
+
     def _log_guardrail_information(
         self,
         request_data: dict,
@@ -1511,6 +1615,28 @@ class ContentFilterGuardrail(CustomGuardrail):
                 else [dict(detection) for detection in detections]
             )
 
+        # Competitor intent: add confidence and classification to tracing if present
+        tracing_kw: Dict[str, Any] = {
+            "guardrail_id": self.config_guardrail_id or self.guardrail_name,
+            "policy_template": self.config_policy_template
+            or self._get_policy_templates(),
+            "detection_method": (
+                self._get_detection_methods(detections) if detections else None
+            ),
+            "match_details": (
+                self._build_match_details(detections) if detections else None
+            ),
+            "patterns_checked": self._get_patterns_checked_count(),
+            "risk_score": self._compute_risk_score(
+                detections, masked_entity_count, status
+            ),
+        }
+        for d in detections:
+            if isinstance(d, dict) and d.get("type") == "competitor_intent":
+                tracing_kw["confidence_score"] = d.get("confidence")
+                tracing_kw["classification"] = dict(d)
+                break
+
         self.add_standard_logging_guardrail_information_to_request_data(
             guardrail_provider=self.guardrail_provider,
             guardrail_json_response=guardrail_json_response,
@@ -1520,14 +1646,7 @@ class ContentFilterGuardrail(CustomGuardrail):
             end_time=datetime.now().timestamp(),
             duration=(datetime.now() - start_time).total_seconds(),
             masked_entity_count=masked_entity_count,
-            tracing_detail=GuardrailTracingDetail(
-                guardrail_id=self.config_guardrail_id or self.guardrail_name,
-                policy_template=self.config_policy_template or self._get_policy_templates(),
-                detection_method=self._get_detection_methods(detections) if detections else None,
-                match_details=self._build_match_details(detections) if detections else None,
-                patterns_checked=self._get_patterns_checked_count(),
-                risk_score=self._compute_risk_score(detections, masked_entity_count, status),
-            ),
+            tracing_detail=GuardrailTracingDetail(**tracing_kw),
         )
 
     async def apply_guardrail(
@@ -1575,6 +1694,13 @@ class ContentFilterGuardrail(CustomGuardrail):
 
             processed_texts = []
             for text in texts:
+                # Competitor intent check first (optional; may refuse/reframe)
+                if self._competitor_intent_checker and text:
+                    intent_result = self._competitor_intent_checker.run(text)
+                    if intent_result.get("intent", "other") != "other":
+                        self._apply_competitor_intent_policy(
+                            intent_result, request_data, detections
+                        )
                 filtered_text = self._filter_single_text(text, detections=detections)
                 processed_texts.append(filtered_text)
 
@@ -1700,4 +1826,4 @@ class ContentFilterGuardrail(CustomGuardrail):
             LitellmContentFilterGuardrailConfigModel,
         )
 
-        return LitellmContentFilterGuardrailConfigModel
+        return LitellmContentFilterGuardrailConfigModel

litellm/proxy/guardrails/guardrail_hooks/litellm_content_filter/examples/README.md

@@ -0,0 +1,65 @@
+# Content Filter Examples
+
+## Industry-specific competitor intent: Emirates (airline)
+
+The **generic** competitor intent blocker only needs:
+
+- **brand_self**: Your brand names and aliases (e.g. `["emirates", "ek"]`)
+- **competitors**: List of competitor names (e.g. `["qatar airways", "etihad"]`)
+
+To make it effective for a specific industry (e.g. airlines), add an **industry layer** on top:
+
+1. **domain_words** – Terms that signal “this is about our vertical.”  
+   For Emirates (airline): `airline`, `carrier`, `flight`, `business class`, `lounge`, etc.  
+   This enables the **category_ranking** path (e.g. “Which Gulf airline is the best?”) and the scoring **gate** (so “best” alone doesn’t trigger without domain/geo).
+
+2. **route_geo_cues** – Optional geography/hub terms.  
+   For Emirates: `doha`, `dubai`, `abu dhabi`, `gulf`, `middle east`.
+
+3. **descriptor_lexicon** – Phrases that count as indirect competitor reference.  
+   For aviation: `doha airline`, `oryx airline`, `gulf carrier`, `five star airline`, `skytrax`.
+
+4. **competitor_aliases** – Per-competitor aliases (IATA codes, nicknames).  
+   Example: `qatar airways` → `["qr", "doha airline"]`, `etihad` → `["ey"]`.
+
+5. **policy** – What to do per intent band: `refuse`, `reframe`, `log_only`, or `allow`.  
+   Example: `competitor_comparison: refuse`, `category_ranking: reframe`.
+
+See **emirates_competitor_intent_guardrail.yaml** for a full example you can copy into your proxy `guardrails` config or merge into an existing `litellm_content_filter` guardrail.
+
+### Using the example in your proxy config
+
+In `config.yaml`:
+
+```yaml
+guardrails:
+  - guardrail_name: "emirates-competitor-intent"
+    litellm_params:
+      guardrail: litellm_content_filter
+      mode: pre_call
+      competitor_intent_config:
+        brand_self: [emirates, ek]
+        competitors: [qatar airways, qatar, etihad, turkish airlines]
+        domain_words: [airline, carrier, flight, business class, lounge]
+        route_geo_cues: [doha, dubai, abu dhabi, gulf]
+        descriptor_lexicon: [doha airline, gulf carrier, five star airline]
+        competitor_aliases:
+          qatar airways: [qr, doha airline]
+          etihad: [ey]
+        policy:
+          competitor_comparison: refuse
+          possible_competitor_comparison: reframe
+          category_ranking: reframe
+          log_only: log_only
+```
+
+Then attach this guardrail to your router/policy (e.g. `guardrails.add: [emirates-competitor-intent]`).
+
+### Other industries
+
+Use the same pattern:
+
+- **SaaS**: `domain_words`: `["platform", "tool", "solution", "integration"]`; optional `route_geo_cues` if regional.
+- **Retail**: `domain_words`: `["store", "brand", "product line"]`; `competitor_aliases` for brand nicknames.
+
+The implementation is generic; only the config (and optional industry presets) are industry-specific.

litellm/proxy/guardrails/guardrail_hooks/litellm_content_filter/examples/emirates_competitor_intent_guardrail.yaml

@@ -0,0 +1,134 @@
+# Emirates (airline) industry-specific competitor intent guardrail
+#
+# This is an example of building on the generic competitor intent blocker with
+# industry-specific inputs: domain_words, route_geo_cues, descriptor_lexicon,
+# and competitor_aliases for aviation.
+#
+# Use this guardrail in your proxy config under guardrails.litellm_params, or
+# merge competitor_intent_config into an existing litellm_content_filter guardrail.
+#
+# Minimal required (generic): brand_self, competitors
+# Industry layer (airline): domain_words, route_geo_cues, descriptor_lexicon,
+#   competitor_aliases (IATA/descriptive), optional indirect_competitor_patterns
+
+guardrail_name: "emirates-competitor-intent"
+guardrail_id: "emirates-competitor-intent"
+litellm_params:
+  guardrail: litellm_content_filter
+  mode: pre_call
+  default_on: false
+
+  # Generic inputs (customer provides)
+  competitor_intent_config:
+    # Your brand (Emirates) and how users refer to it
+    brand_self:
+      - emirates
+      - ek
+
+    # Direct competitors (canonical names; use competitor_aliases for codes/typos)
+    competitors:
+      - qatar airways
+      - qatar
+      - etihad
+      - turkish airlines
+      - singapore airlines
+      - british airways
+
+    # Geo entities: countries, cities, airports (for other-meaning vs airline disambiguation)
+    locations:
+      - qatar
+      - doha
+      - doh
+      - hamad international
+      - lusail
+
+    # Industry: airline domain words (trigger category_ranking / gate)
+    domain_words:
+      - airline
+      - airlines
+      - carrier
+      - flight
+      - flights
+      - business class
+      - first class
+      - lounge
+      - lounges
+      - premium cabin
+      - long haul
+
+    # Industry: route/geo cues (Gulf, hubs)
+    route_geo_cues:
+      - doha
+      - dubai
+      - abu dhabi
+      - gulf
+      - middle east
+
+    # Indirect references (descriptor lexicon)
+    descriptor_lexicon:
+      - doha airline
+      - oryx airline
+      - gulf carrier
+      - five star airline
+      - skytrax
+
+    # Per-competitor aliases (IATA codes, nicknames)
+    competitor_aliases:
+      qatar airways:
+        - qr
+        - doha airline
+      qatar:
+        - qr
+      etihad:
+        - ey
+        - abu dhabi airline
+      emirates:
+        - ek
+        - dubai airline
+
+    # Optional: regex patterns for indirect competitor mention (on normalized text)
+    # indirect_competitor_patterns:
+    #   qatar airways:
+    #     - "the doha airline"
+    #     - "doha carrier"
+    #   etihad:
+    #     - "abu dhabi carrier"
+
+    # Policy: what to do per intent band
+    policy:
+      competitor_comparison: refuse
+      possible_competitor_comparison: reframe
+      category_ranking: reframe
+      log_only: log_only
+
+    threshold_high: 0.70
+    threshold_medium: 0.45
+    threshold_low: 0.30
+
+    # Optional: custom messages
+    reframe_message_template: >
+      I'm here to help with Emirates services, bookings, and travel information.
+      Would you like to know about our routes, cabin classes, or loyalty program?
+    refuse_message_template: "We can't compare Emirates with other airlines. How can I help with Emirates travel?"
+
+# --- How to use in config.yaml ---
+#
+# guardrails:
+#   - guardrail_name: "emirates-competitor-intent"
+#     litellm_params:
+#       guardrail: litellm_content_filter
+#       mode: pre_call
+#       competitor_intent_config:
+#         brand_self: [emirates, ek]
+#         competitors: [qatar airways, etihad, ...]
+#         domain_words: [airline, carrier, flight, ...]
+#         route_geo_cues: [doha, dubai, abu dhabi]
+#         descriptor_lexicon: [doha airline, gulf carrier, ...]
+#         competitor_aliases:
+#           qatar airways: [qr, doha airline]
+#           etihad: [ey]
+#         policy:
+#           competitor_comparison: refuse
+#           possible_competitor_comparison: reframe
+#           category_ranking: reframe
+#           log_only: log_only

litellm/types/proxy/guardrails/guardrail_hooks/litellm_content_filter.py

@@ -1,10 +1,42 @@
 from enum import Enum
-from typing import List, Literal, Optional, TypedDict, Union
+from typing import Any, Dict, List, Literal, Optional, TypedDict, Union
 
 from pydantic import Field
 
 from litellm.types.llms.base import BaseLiteLLMOpenAIResponseObject
-from litellm.types.proxy.guardrails.guardrail_hooks.base import GuardrailConfigModel
+from litellm.types.proxy.guardrails.guardrail_hooks.base import \
+    GuardrailConfigModel
+
+# --- Competitor intent blocker (generic, industry-agnostic) ---
+
+CompetitorIntentType = Literal[
+    "competitor_comparison",
+    "possible_competitor_comparison",
+    "category_ranking",
+    "log_only",
+    "other",
+]
+CompetitorActionHint = Literal["allow", "reframe", "refuse", "escalate", "log_only"]
+
+
+class CompetitorIntentEvidenceEntry(TypedDict, total=False):
+    """Single evidence entry: what matched and what it resolved to."""
+
+    type: Literal["entity", "signal"]
+    key: str  # e.g. "competitor", "ranking", "brand_self"
+    value: Optional[str]  # resolved canonical value (e.g. "qatar_airways")
+    match: str  # matched substring
+
+
+class CompetitorIntentResult(TypedDict, total=False):
+    """Structured output from competitor intent checker."""
+
+    intent: CompetitorIntentType
+    confidence: float
+    entities: Dict[str, List[str]]  # brand_self, competitors, category
+    signals: List[str]
+    action_hint: CompetitorActionHint
+    evidence: List[CompetitorIntentEvidenceEntry]
 
 
 # Detection type enum
@@ -37,7 +69,24 @@ class CategoryKeywordDetection(TypedDict):
     action: str  # ContentFilterAction.value
 
 
-ContentFilterDetection = Union[PatternDetection, BlockedWordDetection, CategoryKeywordDetection]
+class CompetitorIntentDetection(TypedDict):
+    """Detection from competitor intent checker (intent + evidence)."""
+
+    type: Literal["competitor_intent"]
+    intent: str
+    confidence: float
+    action_hint: str
+    entities: Dict[str, List[str]]
+    signals: List[str]
+    evidence: List[Dict[str, Any]]
+
+
+ContentFilterDetection = Union[
+    PatternDetection,
+    BlockedWordDetection,
+    CategoryKeywordDetection,
+    CompetitorIntentDetection,
+]
 
 
 class ContentFilterCategoryConfig(BaseLiteLLMOpenAIResponseObject):
@@ -113,6 +162,17 @@ class LitellmContentFilterGuardrailConfigModel(GuardrailConfigModel):
         description="Tag to use for keyword redaction",
     )
 
+    # Competitor intent blocker (generic; industry presets add domain_words, etc.)
+    competitor_intent_config: Optional[Dict[str, Any]] = Field(
+        default=None,
+        description="Optional config for intent-based competitor comparison detection. "
+        "Keys: brand_self (list), competitors (list), competitor_aliases (dict), "
+        "domain_words (list, optional), route_geo_cues (list, optional), "
+        "descriptor_lexicon (list, optional), indirect_competitor_patterns (dict, optional), "
+        "policy (dict), threshold_high, threshold_medium, threshold_low, "
+        "reframe_message_template, refuse_message_template.",
+    )
+
     @staticmethod
     def ui_friendly_name() -> str:
         return "LiteLLM Content Filter"

tests/test_litellm/proxy/guardrails/guardrail_hooks/content_filter/test_competitor_intent.py

@@ -0,0 +1,165 @@
+"""
+Tests for competitor intent detection (normalize, entity layer, scoring, policy).
+"""
+
+import pytest
+
+from litellm.proxy.guardrails.guardrail_hooks.litellm_content_filter.competitor_intent import (
+    AirlineCompetitorIntentChecker,
+    normalize,
+    text_for_entity_matching,
+)
+
+
+class TestNormalize:
+    """Test text normalization (leetspeak, spacing, zero-width)."""
+
+    def test_normalize_lowercase(self):
+        assert normalize("Is Qatar Better?") == "is qatar better?"
+
+    def test_normalize_leetspeak(self):
+        assert "qatar" in normalize("q@tar")
+        assert "qatar" in normalize("q4tar")
+
+    def test_normalize_collapse_whitespace(self):
+        assert normalize("hello    world") == "hello world"
+
+    def test_normalize_spaced_out_letters(self):
+        # Single-letter tokens collapsed into word
+        assert "qatar" in normalize("q a t a r").replace(" ", "")
+
+    def test_normalize_empty(self):
+        assert normalize("") == ""
+        assert normalize(None) == ""
+
+    def test_text_for_entity_matching_removes_punctuation(self):
+        t = text_for_entity_matching("q.a.t.a.r  emirates")
+        assert "emirates" in t
+        assert "." not in t
+
+
+class TestAirlineCompetitorIntentChecker:
+    """Test AirlineCompetitorIntentChecker run() and intent bands."""
+
+    @pytest.fixture
+    def generic_config(self):
+        return {
+            "brand_self": ["emirates", "ek"],
+            "competitors": ["qatar airways", "etihad", "qatar"],
+            "competitor_aliases": {
+                "qatar airways": ["qr", "doha airline"],
+                "qatar": ["qr"],
+            },
+            "locations": ["qatar", "doha", "doh"],
+            "domain_words": ["airline", "carrier", "flight", "business class"],
+            "route_geo_cues": ["doha", "dubai", "abu dhabi"],
+            "policy": {
+                "competitor_comparison": "refuse",
+                "possible_competitor_comparison": "reframe",
+                "category_ranking": "reframe",
+                "log_only": "log_only",
+            },
+            "threshold_high": 0.70,
+            "threshold_medium": 0.45,
+            "threshold_low": 0.30,
+        }
+
+    def test_run_other_intent(self, generic_config):
+        checker = AirlineCompetitorIntentChecker(generic_config)
+        result = checker.run("What is the weather today?")
+        assert result["intent"] == "other"
+        assert result["action_hint"] == "allow"
+
+    def test_run_competitor_comparison_direct(self, generic_config):
+        checker = AirlineCompetitorIntentChecker(generic_config)
+        result = checker.run("Is Qatar better than Emirates?")
+        assert result["intent"] in ("competitor_comparison", "possible_competitor_comparison")
+        assert "competitor_entity" in result.get("signals", []) or "competitors" in str(result.get("entities", {}))
+        assert result["confidence"] >= 0.45
+
+    def test_run_competitor_comparison_as_good_as(self, generic_config):
+        checker = AirlineCompetitorIntentChecker(generic_config)
+        result = checker.run("Is Qatar as good as Emirates?")
+        assert result["intent"] != "other"
+        assert result["confidence"] >= 0.45
+
+    def test_run_ranking_with_competitor(self, generic_config):
+        checker = AirlineCompetitorIntentChecker(generic_config)
+        result = checker.run("Why is Qatar Airways the best?")
+        assert result["intent"] != "other"
+        assert "qatar" in str(result.get("entities", {}).get("competitors", [])).lower() or "competitor" in str(result.get("signals", []))
+
+    def test_run_ranking_without_competitor_category_ranking(self, generic_config):
+        checker = AirlineCompetitorIntentChecker(generic_config)
+        result = checker.run("Which Gulf airline is the best?")
+        # domain_words "airline" + ranking "best" + geo "gulf" not in route_geo_cues but "airline" is domain
+        assert result["intent"] in ("category_ranking", "possible_competitor_comparison", "log_only", "other")
+
+    def test_run_evidence_populated(self, generic_config):
+        checker = AirlineCompetitorIntentChecker(generic_config)
+        result = checker.run("Is Qatar better than Emirates?")
+        assert "evidence" in result
+        assert isinstance(result["evidence"], list)
+
+    def test_run_gate_prevents_false_positive(self, generic_config):
+        # "best" alone without entity or domain should not trigger competitor_comparison
+        checker = AirlineCompetitorIntentChecker(generic_config)
+        result = checker.run("What is the best way to cook pasta?")
+        assert result["intent"] in ("other", "log_only")
+
+    def test_other_meaning_context_suppression(self, generic_config):
+        # "flights to qatar" = other meaning (country), not competitor airline
+        checker = AirlineCompetitorIntentChecker(generic_config)
+        result = checker.run("how expensive are flights to qatar?")
+        assert result["intent"] == "other"
+        assert not result.get("entities", {}).get("competitors")
+
+
+class TestContentFilterWithCompetitorIntent:
+    """Integration: ContentFilterGuardrail with competitor_intent_config."""
+
+    @pytest.mark.asyncio
+    async def test_apply_guardrail_with_competitor_intent_allow(self):
+        from litellm.proxy.guardrails.guardrail_hooks.litellm_content_filter.content_filter import (
+            ContentFilterGuardrail,
+        )
+
+        guardrail = ContentFilterGuardrail(
+            guardrail_name="test-competitor",
+            competitor_intent_config={
+                "brand_self": ["emirates"],
+                "competitors": ["qatar"],
+                "domain_words": ["airline"],
+                "policy": {"competitor_comparison": "refuse", "possible_competitor_comparison": "reframe"},
+            },
+        )
+        inputs = {"texts": ["What is the capital of France?"]}
+        result = await guardrail.apply_guardrail(
+            inputs, request_data={}, input_type="request"
+        )
+        assert result["texts"] == ["What is the capital of France?"]
+
+    @pytest.mark.asyncio
+    async def test_apply_guardrail_with_competitor_intent_refuse(self):
+        from fastapi import HTTPException
+
+        from litellm.proxy.guardrails.guardrail_hooks.litellm_content_filter.content_filter import (
+            ContentFilterGuardrail,
+        )
+
+        guardrail = ContentFilterGuardrail(
+            guardrail_name="test-competitor",
+            competitor_intent_config={
+                "brand_self": ["emirates"],
+                "competitors": ["qatar airways"],
+                "domain_words": ["airline", "flight"],
+                "policy": {"competitor_comparison": "refuse"},
+                "threshold_high": 0.5,
+            },
+        )
+        inputs = {"texts": ["Is Qatar Airways better than Emirates?"]}
+        with pytest.raises(HTTPException) as exc_info:
+            await guardrail.apply_guardrail(
+                inputs, request_data={}, input_type="request"
+            )
+        assert exc_info.value.status_code == 403

ui/litellm-dashboard/src/data/compliancePrompts.ts

@@ -250,10 +250,254 @@ const compliancePrompts: CompliancePrompt[] = [
   ),
 ];
 
+export const airlineCompliancePrompts: CompliancePrompt[] = [
+  // =====================
+  // DESTINATION (should PASS)
+  // =====================
+  {
+    id: "airline_001",
+    framework: "Airline Brand Protection",
+    category: "Destination Intent",
+    categoryIcon: "✈️",
+    categoryDescription: "User is asking about a travel destination, not a competitor airline.",
+    prompt: "Do you have flights to Qatar?",
+    expectedResult: "pass",
+  },
+  {
+    id: "airline_002",
+    framework: "Airline Brand Protection",
+    category: "Destination Intent",
+    categoryIcon: "✈️",
+    categoryDescription: "Location-based travel planning.",
+    prompt: "How long is the flight to Doha?",
+    expectedResult: "pass",
+  },
+  {
+    id: "airline_003",
+    framework: "Airline Brand Protection",
+    category: "Destination Intent",
+    categoryIcon: "✈️",
+    categoryDescription: "Transit and visa questions for a country.",
+    prompt: "Do I need a visa to transit through Qatar?",
+    expectedResult: "pass",
+  },
+  {
+    id: "airline_004",
+    framework: "Airline Brand Protection",
+    category: "Destination Intent",
+    categoryIcon: "✈️",
+    categoryDescription: "Airport facilities question.",
+    prompt: "Are there lounges at Hamad Airport?",
+    expectedResult: "pass",
+  },
+  {
+    id: "airline_005",
+    framework: "Airline Brand Protection",
+    category: "Destination Intent",
+    categoryIcon: "✈️",
+    categoryDescription: "Travel logistics to a location.",
+    prompt: "What documents are required to enter Singapore?",
+    expectedResult: "pass",
+  },
+  {
+    id: "airline_006",
+    framework: "Airline Brand Protection",
+    category: "Destination Intent",
+    categoryIcon: "✈️",
+    categoryDescription: "Flight planning for a country destination.",
+    prompt: "What airlines fly to Turkey?",
+    expectedResult: "pass",
+  },
+  {
+    id: "airline_007",
+    framework: "Airline Brand Protection",
+    category: "Destination Intent",
+    categoryIcon: "✈️",
+    categoryDescription: "Airport code information.",
+    prompt: "What is the airport code for Doha?",
+    expectedResult: "pass",
+  },
+  {
+    id: "airline_008",
+    framework: "Airline Brand Protection",
+    category: "Destination Intent",
+    categoryIcon: "✈️",
+    categoryDescription: "General travel planning question.",
+    prompt: "Is Doha a good place for a long layover?",
+    expectedResult: "pass",
+  },
+  {
+    id: "airline_009",
+    framework: "Airline Brand Protection",
+    category: "Destination Intent",
+    categoryIcon: "✈️",
+    categoryDescription: "Country weather question.",
+    prompt: "What is the weather like in Qatar in March?",
+    expectedResult: "pass",
+  },
+  {
+    id: "airline_010",
+    framework: "Airline Brand Protection",
+    category: "Destination Intent",
+    categoryIcon: "✈️",
+    categoryDescription: "Transit timing question.",
+    prompt: "How much connection time do I need in Doha?",
+    expectedResult: "pass",
+  },
+
+  // =====================
+  // COMPETITOR (should FAIL)
+  // =====================
+  {
+    id: "airline_011",
+    framework: "Airline Brand Protection",
+    category: "Competitor Comparison",
+    categoryIcon: "⚠️",
+    categoryDescription: "Direct comparison between airlines.",
+    prompt: "Is Qatar Airways better than Emirates?",
+    expectedResult: "fail",
+  },
+  {
+    id: "airline_012",
+    framework: "Airline Brand Protection",
+    category: "Competitor Comparison",
+    categoryIcon: "⚠️",
+    categoryDescription: "Comparison request for premium cabins.",
+    prompt: "Which airline has better business class, Qatar or Singapore Airlines?",
+    expectedResult: "fail",
+  },
+  {
+    id: "airline_013",
+    framework: "Airline Brand Protection",
+    category: "Competitor Comparison",
+    categoryIcon: "⚠️",
+    categoryDescription: "Airline ranking request.",
+    prompt: "Which airline is the best for long haul flights?",
+    expectedResult: "fail",
+  },
+  {
+    id: "airline_014",
+    framework: "Airline Brand Protection",
+    category: "Competitor Comparison",
+    categoryIcon: "⚠️",
+    categoryDescription: "Decision-making between competitors.",
+    prompt: "Should I choose Qatar Airways or another airline?",
+    expectedResult: "fail",
+  },
+  {
+    id: "airline_015",
+    framework: "Airline Brand Protection",
+    category: "Competitor Comparison",
+    categoryIcon: "⚠️",
+    categoryDescription: "General airline comparison.",
+    prompt: "Compare Turkish Airlines vs Lufthansa.",
+    expectedResult: "fail",
+  },
+  {
+    id: "airline_016",
+    framework: "Airline Brand Protection",
+    category: "Competitor Comparison",
+    categoryIcon: "⚠️",
+    categoryDescription: "Service quality comparison.",
+    prompt: "Which airline has better lounges?",
+    expectedResult: "fail",
+  },
+  {
+    id: "airline_017",
+    framework: "Airline Brand Protection",
+    category: "Competitor Comparison",
+    categoryIcon: "⚠️",
+    categoryDescription: "Customer review comparison.",
+    prompt: "Which airline has the best customer satisfaction?",
+    expectedResult: "fail",
+  },
+  {
+    id: "airline_018",
+    framework: "Airline Brand Protection",
+    category: "Competitor Comparison",
+    categoryIcon: "⚠️",
+    categoryDescription: "Indirect competitor reference via location.",
+    prompt: "Is the Doha airline better than other carriers?",
+    expectedResult: "fail",
+  },
+  {
+    id: "airline_019",
+    framework: "Airline Brand Protection",
+    category: "Competitor Comparison",
+    categoryIcon: "⚠️",
+    categoryDescription: "Switching intent to competitor.",
+    prompt: "Should I switch to another airline for a better experience?",
+    expectedResult: "fail",
+  },
+  {
+    id: "airline_020",
+    framework: "Airline Brand Protection",
+    category: "Competitor Comparison",
+    categoryIcon: "⚠️",
+    categoryDescription: "Global airline ranking request.",
+    prompt: "Which airline is ranked number one worldwide?",
+    expectedResult: "fail",
+  },
+
+  // =====================
+  // AMBIGUOUS (should PASS but needs careful handling)
+  // =====================
+  {
+    id: "airline_021",
+    framework: "Airline Brand Protection",
+    category: "Ambiguous Entity",
+    categoryIcon: "❓",
+    categoryDescription: "Could refer to airline or country.",
+    prompt: "Qatar baggage allowance",
+    expectedResult: "pass",
+  },
+  {
+    id: "airline_022",
+    framework: "Airline Brand Protection",
+    category: "Ambiguous Entity",
+    categoryIcon: "❓",
+    categoryDescription: "Ambiguous lounge reference.",
+    prompt: "Qatar lounge access rules",
+    expectedResult: "pass",
+  },
+  {
+    id: "airline_023",
+    framework: "Airline Brand Protection",
+    category: "Ambiguous Entity",
+    categoryIcon: "❓",
+    categoryDescription: "Ambiguous operational query.",
+    prompt: "Qatar check in time",
+    expectedResult: "pass",
+  },
+  {
+    id: "airline_024",
+    framework: "Airline Brand Protection",
+    category: "Ambiguous Entity",
+    categoryIcon: "❓",
+    categoryDescription: "Ambiguous airline vs destination reference.",
+    prompt: "Doha premium lounge access",
+    expectedResult: "pass",
+  },
+  {
+    id: "airline_025",
+    framework: "Airline Brand Protection",
+    category: "Ambiguous Entity",
+    categoryIcon: "❓",
+    categoryDescription: "Ambiguous refund context.",
+    prompt: "Qatar refund policy",
+    expectedResult: "pass",
+  },
+];
+
+const allCompliancePrompts: CompliancePrompt[] = [
+  ...compliancePrompts,
+  ...airlineCompliancePrompts,
+];
+
 export function getCategories(): ComplianceCategory[] {
   const categoryMap = new Map<string, ComplianceCategory>();
 
-  for (const prompt of compliancePrompts) {
+  for (const prompt of allCompliancePrompts) {
     if (!categoryMap.has(prompt.category)) {
       categoryMap.set(prompt.category, {
         name: prompt.category,
@@ -277,6 +521,10 @@ const frameworkMeta: Record<string, { icon: string; description: string }> = {
     icon: "lock",
     description: "General Data Protection Regulation — data privacy and protection requirements.",
   },
+  "Airline Brand Protection": {
+    icon: "plane",
+    description: "Destination vs competitor intent — avoid answering competitor comparison questions.",
+  },
 };
 
 export function getFrameworks(): ComplianceFramework[] {
@@ -285,7 +533,7 @@ export function getFrameworks(): ComplianceFramework[] {
     { categories: Map<string, ComplianceCategory> }
   >();
 
-  for (const prompt of compliancePrompts) {
+  for (const prompt of allCompliancePrompts) {
     if (!frameworkMap.has(prompt.framework)) {
       frameworkMap.set(prompt.framework, { categories: new Map() });
     }

ui/litellm-dashboard/tsconfig.json

@@ -14,7 +14,7 @@
     "moduleResolution": "bundler",
     "resolveJsonModule": true,
     "isolatedModules": true,
-    "jsx": "react-jsx",
+    "jsx": "preserve",
     "incremental": true,
     "plugins": [
       {