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wechatauto-replica — WeChat 4.x Windows Automation (wxauto-compatible)

Automate the WeChat 4.x Windows desktop client (not the web version): read messages, listen in real time, download media, export full history, read Moments (朋友圈), and send messages — by driving the local client directly.

Current version: 1.1.1 · Windows 10/11 · Python 3.9+ (verified on 3.12) · WeChat 4.1.12+

Why this project exists: the classic wxauto relies on the UI Automation tree, which WeChat 4.x broke with self-drawn rendering (no accessibility nodes). wechatauto-replica is a drop-in-style replacement: messages are read through local database decryption (SQLCipher 4), and sending uses a UIA + OCR hybrid driver that auto-falls back between engines.

Reading the encrypted contact.db / message_*.db / sns.db files directly from xwechat_files/.../db_storage/ — no web API, all local.

✨ Features

🚀 Quick Start

pip install -e .
# extra deps for the OCR sending path:
pip install winsdk pypinyin

Read messages

from wechatauto import WeChatDB

db = WeChatDB()  # auto-detects account & data dir (WeChat must be logged in)

info = db.get_self_info()                    # current account
for s in db.get_sessions(limit=10):          # session list
    print(db.get_nickname(s["username"]), s["unread"])

hits = db.search_contact("Ayi")              # search contacts
for m in db.get_messages("filehelper", limit=10):   # recent messages
    print(m["create_time"], m["sender_id"], m["type"], m["content"])

Send a message

from wechatauto.guia import quick_send, quick_send_file

quick_send("Hello", "filehelper", verify=True)   # verify=True reads back from DB
quick_send_file(r"D:\report.pdf", "filehelper")

Real-time listening

from wechatauto import WeChatDB
from wechatauto.db import Listener

db = WeChatDB()
lst = Listener(db, interval=1.0)
lst.add_listener("filehelper", lambda msg, lst: print("new:", msg["content"]))
lst.start()
# ... your code ...
lst.stop()

Callbacks run on dedicated per-chat worker threads: messages in one chat are processed in order, different chats in parallel; slow callbacks (AI calls, image recognition) never block the poller.

Media & Moments

from wechatauto import WeChatDB, MediaDownloader, MomentDB

db = WeChatDB()
md = MediaDownloader(db)
md.detect_image_key()          # scan process memory for the image AES key (persisted after first hit)
for m in db.get_messages("filehelper", limit=50):
    out = md.download_media("filehelper", m["local_id"])
    if out:
        print("downloaded:", out)

moments = MomentDB(db)
for feed in moments.get_moments(limit=10):
    print(feed["nickname"], feed["text"])
    print("  images:", [i["md5"] for i in feed["images"]])
    print("  likes:", [l["nickname"] for l in feed["likes"]])
    print("  comments:", [(c["nickname"], c["content"]) for c in feed["comments"]])

🧠 How It Works

• Reading — WeChat 4.x stores everything in SQLCipher 4 encrypted SQLite databases under xwechat_files/<wxid>/db_storage/ (contact.db, message_*.db, media_0.db, sns.db, …). Each DB has its own 32-byte key living in the Weixin.exe process memory (com.Tencent.WCDB.Config.Cipher config objects). The library locates them with a read-only memory scan, validates candidates with SQLCipher HMAC rules, decrypts pages to a temp dir and caches the result (first decrypt ~6s, then instant). WAL incremental merging with frame-salt filtering prevents database disk image is malformed corruption.
• Sending — WeChat 4.x chat UI is self-drawn (no accessibility nodes), so sending uses a hybrid driver: hot-activate the Qt accessibility gate inside Weixin.dll (RVA scan, writes the screen-reader flag) to materialize the mmui::* UIA tree — search box, chat_input_field, etc. Sending is UIA-first, coordinate + OCR fallback: auto-calibrating layout (~/.wechatauto/layout-<machine>.json), zoomed OCR (3x) with multi-round voting for rare Chinese characters, clipboard + Ctrl+V input to dodge IME interception.
• Media — image .dat files are [6B sig][4B aes_size][4B xor_size] + AES-ECB + plaintext + xor chunks. The account-level AES key is transient (only resident in memory while viewing an image); MediaDownloader scans for it, validates via JPEG/PNG magic, and persists it to image_keys.json so later runs need no scanning (or pass image_key= explicitly). Voice is plain SILK read from media_0.db; files are read from msg/file/ with original names resolved from message_resource.db.

⚖️ vs wxauto

⚠️ Known Limitations

1. WeChat must be logged in — DB keys live in process memory; cached after first extraction, re-extracted automatically after re-login.
2. Image AES key is transient — only resident while viewing an image; persisted to image_keys.json once found, or inject via image_key=.
3. Sending is a GUI operation — fails cleanly when the desktop is locked (desktop_available() returns False).
4. Videos are downloadable only when the mp4 already exists on disk (msg/video/).
5. Moments posting is dropped (4.x self-drawn UI, unreliable); reading/likes/comments are supported.

🗺️ Roadmap

• Calibrate and verify file/image/reply/@ sending on unlocked desktops
• Video message download (4.x storage location TBD)
• Performance: parallel export / first-scan, incremental memory-scan cache

📝 Changelog

v1.1.1 (2026-08-16)

• Recall last message (Chat.RecallLastMessage / uia_driver.recall_last_message): right-click the latest own message → UIA-first menu-item click (mmui::XMenuView found inside the main-window subtree), OCR fallback; fails cleanly when the 2-minute recall window has passed (menu only shows "Delete").
• UIA robustness: menu-item lookup scoped to the main-window subtree (avoids the Windows UIA root-traversal hang), removed the fragile WindowControl(ClassName=...) fallback.
• Media fix: video id bytes→str decoding in MediaDownloader.
• demo_media.py --photos default 3 → 10.

v1.1.0 (2026-08-15)

• Image AES key auto-capture (media.py): the V2 image key is only resident in memory while viewing an image (~5 min). _scan_aes_key() gained a monitor mode — polls continuously and persists the key to image_keys.json once found; users just open one image to finish setup.
• Fixed the process-ordering scan bug (removed the memory-usage sort that pushed the main process last).
• Forward voice messages: SILK extraction from media_0.db + file-message send (demo_forward_voice.py).
• New demos: demo_group_messages.py (group + red-packet ZSTD parsing), demo_robust.py.

🤝 Acknowledgments

Thanks to vesio for sharing the WeChat 4.1.12 UIA control-tree approach and debugging ideas in issue #1 — it made the UIA hybrid driver (v1.0.8) possible.

📄 License & Disclaimer

Apache-2.0. This project is for personal learning and automation research only — please respect the WeChat software license agreement and applicable laws.

Contact: fanyuantaier@163.com