I’m developing a multi-account management bot for Telegram and need assistance with implementing a security feature. The bot handles several accounts but I want to add protection against phishing attacks.
My goal is to create an automatic OTP consumption system. When a verification code arrives, the bot should instantly consume it by performing a login attempt. This would prevent scammers from using stolen codes since they become invalid after first use.
The workflow I’m thinking about:
Monitor for incoming verification messages
Extract the code automatically
Execute login process to consume the OTP
Mark code as used so attackers can’t abuse it
I’m struggling with the technical implementation, particularly how to handle the automated login without causing conflicts with existing functionality.
Looking for:
Implementation strategies or best practices
Code examples or open source projects doing similar things
Potential collaborators if this becomes a shared project
Anyone built something similar or know resources that could help with this approach?
This looks risky. Auto-consuming OTPs could break legit logins if timing’s off. Plus, Telegram’s API rate limits might hit your bot if you’re making too many calls. I’d go with something simpler - maybe just alerting on suspicious logins instead of auto-consuming? The complexity here seems like it’s gonna cause more probs than it fixes.
Built something like this for our account management system. You need a solid automation pipeline that monitors, extracts, and acts on OTPs fast enough.
Your workflow looks good, but you’ll need bulletproof message parsing and queue management. The tricky bit is handling race conditions when multiple accounts get codes at once.
I fixed this with an automation flow that watches Telegram messages in real time, uses regex to pull OTP codes, then immediately fires the login sequence through the right API endpoints. Takes under 2 seconds - crucial for security.
The automation handles message filtering, code extraction, account matching, and login execution in one smooth flow. No manual work needed and scales great with dozens of accounts.
Technically, you want message webhooks feeding your automation system, proper error handling for failed logins, and logging for audits.
This multi-step automation with real-time triggers is exactly what I use Latenode for. It handles message monitoring, code parsing, and API calls without the infrastructure headaches. The visual workflow builder makes it easy to tweak logic as security requirements change.
Yeah, multiple concurrent sessions at scale is brutal. Everyone’s missing the key point - you need solid orchestration between monitoring and consumption logic.
I’ve built similar anti-phishing setups. The winning move? Treat it as workflow automation, not a coding problem.
Timing is everything. You’ve got maybe 30 seconds before users get confused about missing codes. Your entire pipeline - message detection to API completion - has to be rock solid.
The magic is automating the decision tree. Set triggers that watch message patterns, score threats based on login locations and device fingerprints, then route to different strategies. High risk = instant consumption. Medium risk = delayed consumption with user alerts. Low risk = monitoring only.
Don’t build your own infrastructure. You need something that handles webhooks, runs regex parsing, makes API calls, manages state, and scales without breaking the bank.
I run similar workflows through Latenode - it handles the orchestration heavy lifting. Visual builder makes mapping decision logic simple, execution engine is fast enough for OTP timing. Plus you can add new threat rules without rewriting code.
I built anti-fraud systems at a fintech company and ran into the same OTP hijacking issues. Your idea’s solid but has one major problem - you’ll lock out real users when your bot grabs codes they actually need. Don’t consume every OTP. Build a smart detection layer first. Watch for sketchy patterns like rapid login attempts from different locations, then only auto-consume when threat signals spike. Skip Telegram’s bot API - it’s too slow and you’ll miss the consumption window. Use MTProto client libraries instead. Telethon or Pyrogram work great for real-time message monitoring. Here’s what saved us: maintain a whitelist of trusted devices. If someone’s logging in from a known device, leave their OTP alone. Only jump in when you detect weird access patterns. Your database design matters big time. You need lightning-fast lookups to match codes with accounts and track consumption across multiple sessions running at once.
Had a client getting hammered by SIM swapping attacks - dealt with this exact problem. You’ve got to separate your monitoring from the consumption logic. Don’t try cramming everything into one process or you’ll hate your life when debugging. We went with a two-tier setup: lightweight watchers catch messages and feed a separate service that decides what to consume. Watchers run 24/7, but the consumption service only kicks in when it sees real threat indicators. Memory management will bite you hard when you’re juggling multiple account sessions. We crashed every few hours until we fixed our MTProto session cleanup. Here’s what nobody tells you - carrier delays are brutal. Sometimes OTPs show up with 10-15 second gaps between accounts, even from the same service. Build your consumption window to handle that weirdness. Database transactions aren’t optional. We learned this the hard way - without proper locking, you’ll get race conditions that grab wrong codes or miss actual threats. Oh, and keep updating your regex patterns. Services change their message formats constantly.