fix(security): CORS限制+SSRF防护+PATCH乐观锁+accounts安全cap(4 important bugs)
- main.py + config.py: CORS origins read from Settings.cors_origins (comma-separated).
Empty falls back to dev origin localhost:5173; never wildcard. Methods locked
to GET/PATCH/POST; allow_credentials=False.
- scraper/media.py: download_url now passes follow_redirects=False to httpx.
OSS URLs return 200 directly; a 3xx is treated as a download failure (caught
by existing except clauses) instead of opening an SSRF vector to internal hosts.
- routers/voice_clips.py: PATCH /voice-clips/{id}/match accepts an optional
If-Match header carrying the client's last-seen updated_at. On mismatch the
row was modified by another request and the server returns 409. Without the
header the behaviour is unchanged (backward compatible). Response now echoes
the post-update updated_at so the client can fold it into the next request.
- routers/organization.py: /api/accounts now UNION ALLs the wechat_account and
whatsapp_account projections at the SQL level and pushes COUNT + pagination
(offset/limit) down to the DB. Stable ordering on (channel, account_id).
Removes the in-memory materialization that broke at scale.
Tests: 395 passed. Added optimistic-lock coverage (If-Match accepted / stale 409 /
absent header backward-compat). Updated existing PATCH tests for the new
updated_at response field.
Co-Authored-By: Claude <noreply@anthropic.com>
This commit is contained in:
@@ -10,9 +10,10 @@ Read-only queries over the mirrored ``department``, ``staff``,
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* ``GET /api/accounts`` -> ``Page[AccountOut]`` projecting both staff-messaging
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account tables onto a unified shape (see :class:`AccountOut`). The optional
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``channel`` filter restricts to one of ``wechat`` / ``whatsapp``; when
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omitted, both tables are unioned in memory. Staff-account volumes are modest
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(tens to low hundreds of rows), so the in-memory merge is cheap and keeps
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the API contract simple.
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omitted, both tables are UNIONed at the SQL level and paginated in-database
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(no full-table Python materialization). Staff-account volumes are modest in
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practice today, but the SQL-level pagination keeps the endpoint safe if a
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tenant ever scales past thousands of rows.
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"""
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from __future__ import annotations
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@@ -91,49 +92,80 @@ async def list_accounts(
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"""List staff messaging accounts (WeChat / WhatsApp) in a unified shape.
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``channel`` optional; one of ``wechat`` / ``whatsapp``. When omitted, both
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tables are merged in memory. Pagination is applied after the merge using a
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stable ``(channel, account_id)`` ordering.
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tables are UNIONed at the SQL level. Pagination and total count are pushed
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down to the database (single ``COUNT(*)`` over the UNION subquery + a
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paginated ``SELECT`` with ``OFFSET``/``LIMIT``) so we never materialize the
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full cross-table row set in Python. Stable ordering is ``(channel,
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account_id)``.
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``AccountOut`` field mapping (identical shape from both source tables):
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* WeChat: account_id=wx_id, nickname=nick_name, user_id, user_name, phone,
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contacts_num, group_num, is_on_job, raw_json (verbatim upstream record).
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* WhatsApp: account_id=uid (+ same projection).
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"""
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selected_channels = [channel] if channel else ["wechat", "whatsapp"]
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wechat_q = sa.select(
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WechatAccount.wx_id.label("account_id"),
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sa.literal("wechat").label("channel"),
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WechatAccount.nick_name.label("nickname"),
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WechatAccount.user_id.label("user_id"),
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WechatAccount.user_name.label("user_name"),
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WechatAccount.phone.label("phone"),
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WechatAccount.contacts_num.label("contacts_num"),
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WechatAccount.group_num.label("group_num"),
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WechatAccount.is_on_job.label("is_on_job"),
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WechatAccount.raw_json.label("raw_json"),
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)
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whatsapp_q = sa.select(
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WhatsappAccount.uid.label("account_id"),
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sa.literal("whatsapp").label("channel"),
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WhatsappAccount.nick_name.label("nickname"),
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WhatsappAccount.user_id.label("user_id"),
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WhatsappAccount.user_name.label("user_name"),
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WhatsappAccount.phone.label("phone"),
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WhatsappAccount.contacts_num.label("contacts_num"),
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WhatsappAccount.group_num.label("group_num"),
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WhatsappAccount.is_on_job.label("is_on_job"),
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WhatsappAccount.raw_json.label("raw_json"),
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)
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rows: list[AccountOut] = []
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if "wechat" in selected_channels:
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result = (await session.execute(sa.select(WechatAccount))).scalars().all()
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for r in result:
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rows.append(
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AccountOut(
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channel="wechat",
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account_id=r.wx_id,
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nickname=r.nick_name,
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user_id=r.user_id,
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user_name=r.user_name,
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phone=r.phone,
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contacts_num=r.contacts_num,
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group_num=r.group_num,
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is_on_job=r.is_on_job,
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raw_json=r.raw_json,
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)
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)
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if "whatsapp" in selected_channels:
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result = (await session.execute(sa.select(WhatsappAccount))).scalars().all()
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for r in result:
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rows.append(
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AccountOut(
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channel="whatsapp",
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account_id=r.uid,
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nickname=r.nick_name,
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user_id=r.user_id,
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user_name=r.user_name,
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phone=r.phone,
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contacts_num=r.contacts_num,
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group_num=r.group_num,
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is_on_job=r.is_on_job,
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raw_json=r.raw_json,
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)
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)
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if channel == "wechat":
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parts: list[sa.Select] = [wechat_q]
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elif channel == "whatsapp":
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parts = [whatsapp_q]
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else:
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parts = [wechat_q, whatsapp_q]
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rows.sort(key=lambda a: (a.channel, a.account_id))
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total = len(rows)
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start = (page - 1) * page_size
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items = rows[start : start + page_size]
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base_q: sa.Select = parts[0] if len(parts) == 1 else sa.union_all(*parts)
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# Wrap in a subquery so COUNT and paginated SELECT both have a stable
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# column set (the labelled columns become ``sub.c.<label>``).
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sub = base_q.subquery()
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total = (
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await session.execute(sa.select(sa.func.count()).select_from(sub))
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).scalar_one()
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page_q = (
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sa.select(sub)
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.order_by(sub.c.channel.asc(), sub.c.account_id.asc())
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.offset((page - 1) * page_size)
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.limit(page_size)
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)
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rows = (await session.execute(page_q)).all()
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items = [
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AccountOut(
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channel=row.channel,
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account_id=row.account_id,
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nickname=row.nickname,
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user_id=row.user_id,
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user_name=row.user_name,
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phone=row.phone,
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contacts_num=row.contacts_num,
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group_num=row.group_num,
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is_on_job=row.is_on_job,
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raw_json=row.raw_json,
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)
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for row in rows
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]
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return Page(items=items, total=total, page=page, page_size=page_size)
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