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DCCONSTRUCTIONS
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# Copyright (c) 2023-present Plane Software, Inc. and contributors
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# SPDX-License-Identifier: AGPL-3.0-only
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# See the LICENSE file for details.
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# Python imports
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import base64
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import nh3
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from plane.utils.exception_logger import log_exception
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from bs4 import BeautifulSoup
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from collections import defaultdict
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import logging
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logger = logging.getLogger("plane.api")
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# Maximum allowed size for binary data (10MB)
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MAX_SIZE = 10 * 1024 * 1024
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# Suspicious patterns for binary data content
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SUSPICIOUS_BINARY_PATTERNS = [
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"<html",
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"<!doctype",
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"<script",
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"javascript:",
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"data:",
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"<iframe",
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]
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def validate_binary_data(data):
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"""
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Validate that binary data appears to be a valid document format
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and doesn't contain malicious content.
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Args:
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data (bytes or str): The binary data to validate, or base64-encoded string
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Returns:
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tuple: (is_valid: bool, error_message: str or None)
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"""
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if not data:
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return True, None # Empty is OK
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# Handle base64-encoded strings by decoding them first
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if isinstance(data, str):
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try:
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binary_data = base64.b64decode(data)
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except Exception:
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return False, "Invalid base64 encoding"
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else:
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binary_data = data
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# Size check - 10MB limit
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if len(binary_data) > MAX_SIZE:
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return False, "Binary data exceeds maximum size limit (10MB)"
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# Basic format validation
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if len(binary_data) < 4:
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return False, "Binary data too short to be valid document format"
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# Check for suspicious text patterns (HTML/JS)
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try:
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decoded_text = binary_data.decode("utf-8", errors="ignore")[:200]
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if any(pattern in decoded_text.lower() for pattern in SUSPICIOUS_BINARY_PATTERNS):
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return False, "Binary data contains suspicious content patterns"
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except Exception:
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pass # Binary data might not be decodable as text, which is fine
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return True, None
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# Combine custom components and editor-specific nodes into a single set of tags
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CUSTOM_TAGS = {
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# editor node/tag names
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"mention-component",
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"label",
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"input",
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"image-component",
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}
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ALLOWED_TAGS = nh3.ALLOWED_TAGS | CUSTOM_TAGS
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# Merge nh3 defaults with all attributes used across our custom components
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ATTRIBUTES = {
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"*": {
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"class",
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"id",
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"title",
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"role",
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"aria-label",
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"aria-hidden",
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"style",
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"start",
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"type",
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"xmlns",
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# common editor data-* attributes seen in stored HTML
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# (wildcards like data-* are NOT supported by nh3; we add known keys
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# here and dynamically include all data-* seen in the input below)
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"data-tight",
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"data-node-type",
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"data-type",
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"data-checked",
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"data-background-color",
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"data-text-color",
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"data-name",
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"data-id",
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# callout attributes
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"data-icon-name",
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"data-icon-color",
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"data-background",
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"data-emoji-unicode",
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"data-emoji-url",
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"data-logo-in-use",
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"data-block-type",
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},
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"a": {"href", "target"},
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# editor node/tag attributes
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"image-component": {
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"id",
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"width",
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"height",
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"aspectRatio",
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"aspectratio",
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"src",
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"alignment",
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"status",
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},
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"img": {
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"width",
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"height",
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"aspectRatio",
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"aspectratio",
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"alignment",
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"src",
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"alt",
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"title",
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},
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"mention-component": {"id", "entity_identifier", "entity_name"},
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"th": {
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"colspan",
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"rowspan",
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"colwidth",
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"background",
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"style",
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},
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"td": {
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"colspan",
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"rowspan",
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"colwidth",
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"background",
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"textColor",
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"textcolor",
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"style",
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},
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"tr": {"background", "textColor", "textcolor", "style"},
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"pre": {"language"},
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"code": {"language", "spellcheck"},
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"input": {"type", "checked"},
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}
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SAFE_PROTOCOLS = {"http", "https", "mailto", "tel"}
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def _compute_html_sanitization_diff(before_html: str, after_html: str):
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"""
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Compute a coarse diff between original and sanitized HTML.
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Returns a dict with:
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- removed_tags: mapping[tag] -> removed_count
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- removed_attributes: mapping[tag] -> sorted list of attribute names removed
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"""
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try:
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def collect(soup):
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tag_counts = defaultdict(int)
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attrs_by_tag = defaultdict(set)
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for el in soup.find_all(True):
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tag_name = (el.name or "").lower()
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if not tag_name:
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continue
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tag_counts[tag_name] += 1
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for attr_name in list(el.attrs.keys()):
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if isinstance(attr_name, str) and attr_name:
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attrs_by_tag[tag_name].add(attr_name.lower())
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return tag_counts, attrs_by_tag
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soup_before = BeautifulSoup(before_html or "", "html.parser")
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soup_after = BeautifulSoup(after_html or "", "html.parser")
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counts_before, attrs_before = collect(soup_before)
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counts_after, attrs_after = collect(soup_after)
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removed_tags = {}
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for tag, cnt_before in counts_before.items():
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cnt_after = counts_after.get(tag, 0)
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if cnt_after < cnt_before:
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removed = cnt_before - cnt_after
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removed_tags[tag] = removed
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removed_attributes = {}
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for tag, before_set in attrs_before.items():
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after_set = attrs_after.get(tag, set())
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removed = before_set - after_set
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if removed:
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removed_attributes[tag] = sorted(list(removed))
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return {"removed_tags": removed_tags, "removed_attributes": removed_attributes}
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except Exception:
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# Best-effort only; if diffing fails we don't block the request
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return {"removed_tags": {}, "removed_attributes": {}}
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def validate_html_content(html_content: str):
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"""
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Sanitize HTML content using nh3.
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Returns a tuple: (is_valid, error_message, clean_html)
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"""
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if not html_content:
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return True, None, None
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# Size check - 10MB limit (consistent with binary validation)
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if len(html_content.encode("utf-8")) > MAX_SIZE:
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return False, "HTML content exceeds maximum size limit (10MB)", None
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try:
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clean_html = nh3.clean(
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html_content,
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tags=ALLOWED_TAGS,
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attributes=ATTRIBUTES,
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url_schemes=SAFE_PROTOCOLS,
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)
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# Report removals to logger (Sentry) if anything was stripped
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diff = _compute_html_sanitization_diff(html_content, clean_html)
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if diff.get("removed_tags") or diff.get("removed_attributes"):
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try:
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import json
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summary = json.dumps(diff)
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except Exception:
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summary = str(diff)
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logger.warning(f"HTML sanitization removals: {summary}")
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return True, None, clean_html
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except Exception as e:
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log_exception(e)
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return False, "Failed to sanitize HTML", None
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