I first built FPScanner during my PhD around 2017–2018, when I was doing research on browser fingerprinting and bot detection. After that I did not really maintain it for years.
I recently decided to revive it because things changed a lot. Automation is much easier now. With free automation libraries like Puppeteer/Playwright/Selenium + headless Chrome and cheap proxies, you can build decent bots very quickly. At the same time, open source defensive tooling is still quite limited, or very basic.
To be clear, FPScanner is not trying to be a silver bullet.
It is a small, self-hosted library that focuses on deterministic client-side signals:
- webdriver and automation flags
- CDP-related artifacts
- automation framework markers (Selenium, Playwright, etc.)
- JS cross-context inconsistencies: main JS context, iframes and workers
It also generates a JA4-inspired fingerprint ID for clustering sessions, and includes encrypted payload + simple anti-replay protections.
There is no ML here, no "AI detection", and no claim to block 100% of bots. The idea is just to expose strong, explainable signals and make automation a bit more expensive. I assume attackers can read the source code.
I tested it on different devices and browsers to avoid JS errors and obvious false positives, but I’m sure there are edge cases. If you try it on less common browsers or hardened setups and it breaks, please let me know or open an issue.
Happy to answer questions or discuss design choices / limitations.
avastel•1h ago
I first built FPScanner during my PhD around 2017–2018, when I was doing research on browser fingerprinting and bot detection. After that I did not really maintain it for years.
I recently decided to revive it because things changed a lot. Automation is much easier now. With free automation libraries like Puppeteer/Playwright/Selenium + headless Chrome and cheap proxies, you can build decent bots very quickly. At the same time, open source defensive tooling is still quite limited, or very basic.
To be clear, FPScanner is not trying to be a silver bullet.
It is a small, self-hosted library that focuses on deterministic client-side signals: - webdriver and automation flags - CDP-related artifacts - automation framework markers (Selenium, Playwright, etc.) - JS cross-context inconsistencies: main JS context, iframes and workers
It also generates a JA4-inspired fingerprint ID for clustering sessions, and includes encrypted payload + simple anti-replay protections.
There is no ML here, no "AI detection", and no claim to block 100% of bots. The idea is just to expose strong, explainable signals and make automation a bit more expensive. I assume attackers can read the source code.
I tested it on different devices and browsers to avoid JS errors and obvious false positives, but I’m sure there are edge cases. If you try it on less common browsers or hardened setups and it breaks, please let me know or open an issue.
Happy to answer questions or discuss design choices / limitations.