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Comment by bsamuels | Hacker News Reader

Modern cred stuffing is done by botnets. When I see a cred stuffing attack, it's maybe 1-3 attempts per IP address spread over 100-500k IP addresses. Often you'll have a family of legitimate users behind an IP address that's cred stuffing you at the same time.

Throttling by IP address may have worked 10 years ago, unfortunately it's not an effective measure anymore.

Modern cred stuffing countermeasures include a wide variety of exotic fingerprinting, behavioral analysis, and other de-anonymization tech - not because anyone wants to destroy user privacy, but because the threat is that significant and has evolved so much in the past few years.

To be entirely honest, I'm kinda surprised Google didn't require javascript enabled to log in already.

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Any advice on where to read more about these modern cred stuffing countermeasures? I'd love to learn more.

A relatively successful company in the area is Shape Security. Their marketing is a bit painful, but they invented the concept of cred stuffing. Disclaimer: I worked there for four years.

Unfortunately I don't have much reading material to provide. It's a bit of an arms war, so the latest and greatest countermeasures are typically kept secret/protected by NDA. The rabbit hole can go very deep and can differ from company to company.

The most drastic example I can think of was an unverified rumor that a certain company would "fake" log users in when presented with valid credentials from a client they considered suspicious. They would then monitor what the client did - from the client's point of view it successfully logged in and would begin normal operation. If server observed the device was acting "correctly" with the fake login token, they would fully log it in. If the client deviated from expected behavior, it would present false data to the client & ban the client based on a bunch of fancy fingerprinting.

Every once in awhile, someone will publish their methods/software; Salesforce and their SSL fingerprinting software comes to mind: https://github.com/salesforce/ja3

This is a rare paper published on the topic.

https://link.springer.com/chapter/10.1007%2F978-3-319-07536-...

Fundamentally it's a question of fingerprinting the behaviours of humans versus bots. The problem is that it's becoming increasingly difficult to distinguish them, particularly when bots are running headless chrome or similar, and real users are automating their sign-ins with password managers.

I don't do much of this sort of thing, but numerous things come to mind. Aim to identify and whitelist obviously human browsers, blacklist obviously robot browsers, and mildly inconvenience/challenge the rest.

For example, an obvious property of a real human browser is that it had been used to log in successfully in the past. Proving that is left as an exercise for the reader, though it inevitably requires some state/memory on the server side.

A company I am considering investing into: https://fingerprints.digital/

Are they looking for funding? They appear to be privately funded.

They have been at https://www.wolvessummit.com/ - they are preparing for a funding round. You can find them at other events listed on their page: https://fingerprints.digital/event/

But you don't have thousands of families logging in from thousand of different servers: in your case a max of 10 login attempts would prevent it.

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