My naive take on a Cloudflare perspective wants to combine "three times is enemy action" with toddler-speed block dropping and manual clearance. What's the money reason this problem isn't handled at the ISP level?
That has only partially mitigated much smaller attacks (residential proxy scraping etc) on my employer's site.
We're currently on the "Business" plan, but I'm coming to the conclusion that we need to upgrade to the "Enterprise Advantage" plan for the JA3/4 fingerprinting and detection ID features.
I'm the author of the blog. I don't know. Internally, we were half joking that we were going to get ransom notice, but we never did.
The only thing that sort of correlates with this attack is that before it started, we began rolling out some slightly more aggressive rate limits one by one. This was mostly because anytime any new "company" thinks they're going to catchup with Claude/OpenAI, they scrape us very aggressively (and they're not respectful about it). My guess is that the attackers behind this attack were already probing us (they were) and they thought the window of opportunity might be closing.
Just curious, if you're tolerant of scraping, do you make an archive of all your content available so that scraping is unnecessary, and if so do the scrapers prefer that?
It's terabytes of content and other than we're the host not really related to each other. However, for most projects, it's possible to download a zip file of all the HTML docs for that project. We have a lower rate limit to pull these, but a scraper can pull thousands of docs at once. We only host a few hundred thousand projects so pulling a zip of the latest docs for all of them could be done in a day or two at a very reasonable rate.
It's also possible to request the docs already processed into markdown[1]. Lastly, basically all of the docs come from Git. A smart scraper could just clone a project's repo.
I run a similar service, and we get almost daily attacks like this. Sometimes it's a specific high-profile customer, other times it's broader.
I can't speak for RTD, but I think it's less "documentation site" and more just that we sit on the domains of high-profile products and the tools are just looking for any hole they can find?
Often it's even the company themselves, for whatever reason (security research, etc).
Interesting that the Under Attack Mode wasn’t used at all here. I understand not wanting to break APIs but I feel temporarily challenging non-API usage could have at least helped without impacting users too much?
I talked about that directly in the post. We didn't want to just challenge everyone. We use JS challenges but we try to use them sparingly. The rest of the ops team and I were fighting to stay up but it never got so bad that it was a choice between complete outage and using the Under Attack mode.
A more interesting question is, what exactly do the attackers gain from hitting read the docs? Most of their docs hosting is static/easily CDN cached. Unlike database bound sites, you would need a lot more traffic to overload pure/mostly static hosting. Maybe it's a malicious AI lab looking to deny their competitors training data? As far as infosec profiling goes, this is probably the oddest case I have heard of.
I am thinking it's probably an AI lab that misconfigured their data scraper (made it too agentic) and it ended up looking like a DDoS.
The new generation of scrapers are all agentic and self healing. (As an example see YC's https://parse.bot)
Author here. This was not a misconfigured data scraper. We see those every week[1]. This attack wasn't scraping useful content. It was almost entirely 404s and 302s and pulled virtually zero real docs. It specifically looked for URLs not served by the CDN and when it found a pattern, did millions of variations of it. Whether built by an AI or not, it was designed to cause outages and financial damage from autoscaling. However, as others have suggested, we may have been a test run for a real target.
> Most of their docs hosting is static/easily CDN cached
The article says
> and it purposefully attacked areas that bypassed caching
So that doesn't work. Also, it seems that they were trying to cause financial harm, not to take down the infrastructure but to make it costly for the org itself. That's smart.
Given how adaptive the rest of the attack was, I would be very curious to find out how it would approach that obstacle.
We're currently on the "Business" plan, but I'm coming to the conclusion that we need to upgrade to the "Enterprise Advantage" plan for the JA3/4 fingerprinting and detection ID features.
I get put off by "Contact Sales" pricing.
The only thing that sort of correlates with this attack is that before it started, we began rolling out some slightly more aggressive rate limits one by one. This was mostly because anytime any new "company" thinks they're going to catchup with Claude/OpenAI, they scrape us very aggressively (and they're not respectful about it). My guess is that the attackers behind this attack were already probing us (they were) and they thought the window of opportunity might be closing.
It's also possible to request the docs already processed into markdown[1]. Lastly, basically all of the docs come from Git. A smart scraper could just clone a project's repo.
[1] https://docs.readthedocs.com/platform/stable/reference/markd...
I can't speak for RTD, but I think it's less "documentation site" and more just that we sit on the domains of high-profile products and the tools are just looking for any hole they can find?
Often it's even the company themselves, for whatever reason (security research, etc).
I am thinking it's probably an AI lab that misconfigured their data scraper (made it too agentic) and it ended up looking like a DDoS.
The new generation of scrapers are all agentic and self healing. (As an example see YC's https://parse.bot)
[1] https://about.readthedocs.com/blog/2024/07/ai-crawlers-abuse...
The article says
> and it purposefully attacked areas that bypassed caching
So that doesn't work. Also, it seems that they were trying to cause financial harm, not to take down the infrastructure but to make it costly for the org itself. That's smart.