revert: restore simple O(n*m) proximity check

The input lists are bounded by the number of phrase patterns (5+5),
so the sorted-scan optimization added complexity for no practical
benefit.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

bot_bottle/dlp_detectors.py

@@ -112,33 +112,18 @@ JAILBREAK_PHRASES: tuple[re.Pattern[str], ...] = (
 PROXIMITY_CHARS = 500
 
 
-def _nearby(
+def _min_distance(
     a_matches: list[re.Match[str]],
     b_matches: list[re.Match[str]],
-    threshold: int,
 ) -> int | None:
-    """Return the smallest char gap between any a–b pair, or None if
-    both lists are empty.  O(n log n) via sort + linear scan."""
     if not a_matches or not b_matches:
         return None
-    events = sorted(
+    best = None
-        [(m.start(), m.end(), "a") for m in a_matches]
+    for a in a_matches:
-        + [(m.start(), m.end(), "b") for m in b_matches],
+        for b in b_matches:
-    )
+            gap = max(0, max(a.start(), b.start()) - min(a.end(), b.end()))
-    best: int | None = None
-    prev_end: int | None = None
-    prev_tag: str | None = None
-    for start, end, tag in events:
-        if prev_tag is not None and prev_tag != tag and prev_end is not None:
-            gap = max(0, start - prev_end)
             if best is None or gap < best:
                 best = gap
-                if best == 0:
-                    return 0
-                if best <= threshold:
-                    return best
-        prev_end = end if prev_end is None else max(prev_end, end)
-        prev_tag = tag
     return best
 
 
@@ -147,7 +132,7 @@ def scan_naive_injection(text: str) -> ScanResult | None:
     jailbreak_hits = [m for p in JAILBREAK_PHRASES for m in p.finditer(text)]
 
     if disclosure_hits and jailbreak_hits:
-        dist = _nearby(disclosure_hits, jailbreak_hits, PROXIMITY_CHARS)
+        dist = _min_distance(disclosure_hits, jailbreak_hits)
         if dist is not None and dist <= PROXIMITY_CHARS:
             return ScanResult(
                 severity="block",