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Great article, but the actual technical details of their current “browser fingerprinting” approach are linked at the bottom: https://stytch.com/docs/fraud/guides/device-fingerprinting/o...

This seems semi-effective for professional actors working at scale, and pretty much useless for more careful, individual actors — especially those running an actual browser window!

I agree that the paywalls around LinkedIn and Twitter are in serious trouble, but a more financially pressing concern IMO is bad faith Display Ads publishers and middlemen. Idk exactly how the detectors work, but it seems pretty impossible to spot an unusually-successful blog that’s faking its own clicks…

IMHO, this is great news! I believe society could do without both paywalls or the entire display ads industry.



Ah, this is great feedback -- I don't think we do enough to articulate how much we're doing beyond that simplified explanation of device fingerprinting on those docs. I'll get that page updated, but 2 main things worth mentioning:

1. We have a few proprietary fingerprint methods that we don't publicly list (but do share with our customers under NDA), which feed into our ML-based browser detection that assesses those fingerprint data points against the entire historical archives of every browser version that has been released, which allows us to discern subtle deception indicators. Even sophisticated attackers find it difficult to figure out what we're fingerprinting on here, which is one reason we don't publicly document it.

2. For a manual attacker running attacks within a legitimate browser, our Intelligent Rate Limiting (IntRL) tracks and rate-limits at the device level, making it effective against attackers using a real browser on their own machine. Unlike traditional rate limiting that relies on brute traits like IP, IntRL uses the combo of browser, hardware, and network fingerprints to detect repeat offenders—even if they clear cookies or switch networks. This ensures that even human-operated, low-frequency attacks get flagged over time, without blocking legitimate users on shared networks.


Thanks for the clarification, the second point is really smart and something that didn't occur to me! You can slow down a scraper and add real mouse movements, but at the end of the day, if you don't have it collecting data for more extended periods than a human would be able to do, what's the point?

And of course the swiss cheese model applies here, as always. Thanks for fighting the good fight! I'm a big hater of IP laws, but this cultural move towards "scraping is never immoral" seems like a big step too far in the other direction.


I'm in a business tangential to the one the author is in and I've mostly encountered annoyances automating websites which perform browser fingerprinting including TLS fingerprinting, but outright blocks not really, not unless you also block real users like cloudflare and datadome frequently do (in their cases, automations have a marginally lower bypass rate than real users do).

In my experience, the level of sophistication to automate bypassing WAFs which do fingerprinting is much too high for those skills to be used to click ads. Seriously, it's not just about the compute cost of running real browsers and residential proxies, it's also the dev time invested, nobody clicks google ads when they can do much, much more with that knowledge.




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