Found a Pocket Option Bot on GitHub? A Checklist Before You Run It

This page assumes you have already found one specific repository you are tempted to run, and walks through judging that repo before it touches your account. For the broader choice between running scripts and using an extension, see GitHub Python bots vs a Chrome extension.

Signs a repo is maintained

A bot that drives a trading page breaks silently when the page changes, so maintenance matters more than for most hobby code.

• Last commit date. If the last commit is old, the bot may be clicking buttons that no longer exist. Treat a stale repo as untested against the live site.
• Open issues. Count them and look at their age. A repo whose recent reports have gone unanswered for months is effectively abandoned, even if the commit date looks recent.
• Are interface-change issues answered? Search the tracker for reports that the trading page changed: buttons moved, login flow altered, trades not registering. If those get fixes, the maintainer is tracking the live site. If they sit open, do not run it on a real account.

How it signs in

This is the most important section. Read the README and the source before installing anything.

• Does it want your password? If the script asks for your Pocket Option email and password, it holds your full credentials in whatever form it stores them: a plain config file, an environment variable, or a log. Ask where that password lives after the run, and whether anything else on your machine could read it.
• Does it store a session token in a file? Some bots capture a session token or cookie after one login and save it for reuse. That is narrower than your password, but it still opens your account to anything that can read the file. Check where the file lives and who can read it.
• Why it matters. Whatever credential the bot holds, anything holding it can act in your account. Give it the smallest credential it genuinely needs, store it where only you can read it, and delete it when you stop using the bot.

What it installs and runs

• Dependencies. Read the dependency list (requirements file or package manifest) before installing. A bot that pulls in a headless browser engine or packages you cannot name deserves extra caution. Install it in an isolated environment (a virtual environment or container).
• Background processes. Check what keeps running after you start it: a headless browser, a daemon, a scheduled task. Compare what is running before and after; anything you did not ask for should be stopped and understood before you continue.
• How to remove it. Know the removal path before you install: the uninstall command, the files it wrote (config, logs, stored credentials) and any background process to stop. If the README does not say how to remove it, that tells you something. For a bot inside your browser, see how to stop or remove the bot safely.

Test it on demo with a long sample and a written stop rule

1. Demo account only. Run it on a Pocket Option demo account until you have watched it through wins and losses, long enough to see how it behaves after a losing streak, not just its first five wins.
2. Write your stop rule before you start. Decide in writing how many losing trades in a row, or what drop in demo balance, ends the test. Then stop when you hit it.
3. Judge results honestly. At a 92% payout, break-even is 1/(1+p) = 1/1.92 ≈ 52.1%, so a bot winning 55% at that payout is only slightly above break-even. If it uses Martingale recovery, judge the cycle cost: with Steps N a losing cycle runs N+1 trades, so at 2x, Steps 2 risks up to 7x your base stake per cycle and Steps 3 up to 15x.
4. Only then consider a real account, and even then start small, keep the trading tab visible and re-check your stop rule each session. More in test a trading bot on demo.

Frequently asked questions

The repo has thousands of stars. Can I skip the checklist?

No. Stars measure popularity, not whether the bot still works against the current trading page or how it handles your credentials. Run the checklist anyway.

It is free on GitHub. What am I actually paying for?

Your time: installing dependencies, debugging a stale interface and, in the worst case, an account you did not protect. If you would rather use a maintained tool, Avalisa's Basic is $69 one-time and Pro is $119 one-time or $29/month (a recurring subscription); the two routes are compared in GitHub Python bots vs a Chrome extension.

It won every trade in my short demo test. Can I go straight to real money?

A short sample proves almost nothing, especially before any losing streak. Extend the sample until your written stop rule has actually been tested, and judge results against break-even (52.1% at a 92% payout), not against the demo balance going up.