CAPTCHAs are great. Exploiters get around them with proprietary anti-detect browsers and unethical residential proxies, while privacy browsers and affordable privacy VPNs get blocked and shadowbanned to death.
Fingerprint.com, while not a CAPTCHA, gives you +3 suspicious score just for using privacy settings like adblock on your browser. This makes it harder to sign up for any sites that use fingerprint.com.
Adversaries do not have to wait for LLM models to evolve to mimic human process, they can simply evade the detection JavaScript that evaluates similarity. JavaScript is visible, can easily be reverse-engineered.
Apparently CloudFlare’s turnstile can’t, as evidenced by several public-facing CRUD and mail routines we maintain that no longer are warding off the spam.
Yeah, we benchmarked against a few bot detection provides end of last year (https://research.roundtable.ai/bot-benchmarking/), and Turnstile didn't do great when it came to AI agent detection. We hypothesized that Turnstile primarily focuses on device/network characteristics, which AI agents can bypass
Meanwhile the moment I (a human, of which I'm reasonably confident) see a Cloudflare captcha I nope immediately out of the site and block it forevermore in Kagi. It's not worth the waiting game. "Verifying..." lasts ages.
The anime girl captcha works fine and provides no such annoyance.
I think it's just a game of cat and mouse. It might be easier to catch naive AI agents that are not fine-tuned for specific CAPTCHA tasks with human behavior, can't recognize new challenges, don't know when to stop and ask a human, and just want to brute force their way with limited or no specialized harness and tools available.
This is relatively close to our conclusion from the paper: unless agents are specifically trained for the task and know all the information ahead of time, they're not able to generalize from one cognitive CAPTCHA to another
I’ve been using Claude Opus 4.7 with Chrome MCP, and it has worked successfully about 95% of the time. However, I’ve failed various hCaptcha challenges.
The thing many people miss is that the challenge itself isn't the primary signal. The challenge creates an opportunity to observe user activity. You're browser is also fingerprinted.
I mean, their CAPTCHAs presumably have tons of data collected over the years, and they can't detect a pretty clear AI agent here: https://www.youtube.com/watch?v=UeTpCdUc4Ls
Well no, the idea is a tradeoff between interfaces and telemetry.
OK, the agents don't click in the same way as humans. You learn that, what about mouse hovering telemetry, time spent, etc. And one of the most extreme is to force biometrics - a lot of telemetry, breaks the interface a lot - but hey, you have assurance.
And none of these tradeoffs require understanding the deep processes of the human mind. Just, map is not the territory, how you do game the map harder and harder and how do the mapmakers respond to that?
LLMs can solve original math problems at the IMO level and beyond, and you might be talking to one now. I don't think they are going to have problems with any CAPTCHA short of separate device attestation.
Whatever mechanism the paper proposes, rest assured it can be trained on.
CAPTCHAs are great. Exploiters get around them with proprietary anti-detect browsers and unethical residential proxies, while privacy browsers and affordable privacy VPNs get blocked and shadowbanned to death.
Fingerprint.com, while not a CAPTCHA, gives you +3 suspicious score just for using privacy settings like adblock on your browser. This makes it harder to sign up for any sites that use fingerprint.com.
https://github.com/CloakHQ/CloakBrowser is a good anti-detect browser as well as CAPTCHA bypass.
Adversaries do not have to wait for LLM models to evolve to mimic human process, they can simply evade the detection JavaScript that evaluates similarity. JavaScript is visible, can easily be reverse-engineered.
Apparently CloudFlare’s turnstile can’t, as evidenced by several public-facing CRUD and mail routines we maintain that no longer are warding off the spam.
Yeah, we benchmarked against a few bot detection provides end of last year (https://research.roundtable.ai/bot-benchmarking/), and Turnstile didn't do great when it came to AI agent detection. We hypothesized that Turnstile primarily focuses on device/network characteristics, which AI agents can bypass
Meanwhile the moment I (a human, of which I'm reasonably confident) see a Cloudflare captcha I nope immediately out of the site and block it forevermore in Kagi. It's not worth the waiting game. "Verifying..." lasts ages.
The anime girl captcha works fine and provides no such annoyance.
I think it's just a game of cat and mouse. It might be easier to catch naive AI agents that are not fine-tuned for specific CAPTCHA tasks with human behavior, can't recognize new challenges, don't know when to stop and ask a human, and just want to brute force their way with limited or no specialized harness and tools available.
This is relatively close to our conclusion from the paper: unless agents are specifically trained for the task and know all the information ahead of time, they're not able to generalize from one cognitive CAPTCHA to another
I’ve been using Claude Opus 4.7 with Chrome MCP, and it has worked successfully about 95% of the time. However, I’ve failed various hCaptcha challenges.
The thing many people miss is that the challenge itself isn't the primary signal. The challenge creates an opportunity to observe user activity. You're browser is also fingerprinted.
Until they learn to do that. So cat and mouse. So nothing new.
think the point is that they can't just "learn to do that", because to do so would mean solving human mind (that famously hasn't been going well)
until Google trains an AI model off that data, too
I mean, their CAPTCHAs presumably have tons of data collected over the years, and they can't detect a pretty clear AI agent here: https://www.youtube.com/watch?v=UeTpCdUc4Ls
Well no, the idea is a tradeoff between interfaces and telemetry.
OK, the agents don't click in the same way as humans. You learn that, what about mouse hovering telemetry, time spent, etc. And one of the most extreme is to force biometrics - a lot of telemetry, breaks the interface a lot - but hey, you have assurance.
And none of these tradeoffs require understanding the deep processes of the human mind. Just, map is not the territory, how you do game the map harder and harder and how do the mapmakers respond to that?
did you look at the paper? they specifically look at mini tasks with cognitive processes (Eg what dictates the strategy of how people solve tasks)
LLMs can solve original math problems at the IMO level and beyond, and you might be talking to one now. I don't think they are going to have problems with any CAPTCHA short of separate device attestation.
Whatever mechanism the paper proposes, rest assured it can be trained on.