|By Lori MacVittie||
|May 1, 2014 09:00 AM EDT||
This week's "bad news" with respect to information security centers on Facebook and the exploitation of HTTP caches to affect a DDoS attack. Reported as a 'vulnerability', this exploit takes advantage of the way the application protocol is designed to work. In fact, the same author who reports the Facebook 'vulnerability' has also shown you can use Google to do the same thing. Just about any site that enables you to submit content containing links and then retrieves those links for you (for caching purposes) could be used in this way. It's not unique to Facebook or Google, for that matter, they just have the perfect environment to make such an exploit highly effective.
The exploit works by using a site (in this case Facebook) to load content and takes advantage of the general principle of amplification to effectively DDoS a third-party site. This is a flood-based like attack, meaning it's attempting to overwhelm a server by flooding it with requests that voraciously consume server-side resources and slow everyone down - to the point of forcing it to appear "down" to legitimate users.
The requests brokered by Facebook are themselves 110% legitimate requests. The requests for an image (or PDF or large video file) are well-formed, and nothing about the requests on an individual basis could be detected as being an attack. This is, in part, why the exploit works: because the individual requests are wholly legitimate requests.
How it Works
The trigger for the "attack" is the caching service. Caches are generally excellent at, well, caching static objects with well-defined URIs. A cache doesn't have a problem finding /myimage.png. It's either there, or it's not and the cache has to go to origin to retrieve it. Where things get more difficult is when requests for content are dynamic; that is, they send parameters that the origin server interprets to determine which image to send, e.g. /myimage?id=30. This is much like an old developer trick to force the reload of dynamic content when browser or server caches indicate a match on the URL. By tacking on a random query parameter, you can "trick" the browser and the server into believing it's a brand new object, and it will go to origin to retrieve it - even though the query parameter is never used. That's where the exploit comes in.
HTTP servers accept as part of the definition of a URI any number of variable query parameters. Those parameters can be ignored or used at the discretion of the application. But when the HTTP server is looking to see if that content has been served already, it does look at those parameters. The reference for a given object is its URL, and thus tacking on a query parameter forces (or tricks if you prefer) the HTTP server to believe the object has never been served before and thus can't be retrieved from a cache.
Caches act on the same principles as an HTTP server because when you get down to brass tacks, a cache is a very specialized HTTP server, focused on mirroring content so it's closer to the user.
<img src=http://target.com/file?r=1> <img src=http://target.com/file?r=2> <img src=http://target.com/file?r=3> ... <img src=http://target.com/file?r=1000>
Many, many, many, many (repeat as necessary) web applications are built using such models. Whether to retrieve text-based content or images is irrelevant to the cache. The cache looks at the request and, if it can't match it somehow, it's going to go to origin.
Which is what's possible with Facebook Notes and Google. By taking advantage of (exploiting) this design principle, if a note crafted with multiple image objects retrieved via a dynamic query is viewed by enough users at the same time, the origin can become overwhelmed or its network oversubscribed.
This is what makes it an exploit, not a vulnerability. There's nothing wrong with the behavior of these caches - they are working exactly as they were designed to act with respect to HTTP. The problem is that when the protocol and caching behavior was defined, such abusive behavior was not considered.
In other words, this is a protocol exploit not specific to Facebook (or Google). In fact, similar exploits have been used to launch attacks in the past. For example, consider some noise raised around WordPress in March 2014 that indicated it was being used to attack other sites by bypassing the cache and forcing a full reload from the origin server:
If you notice, all queries had a random value (like “?4137049=643182″) that bypassed their cache and force a full page reload every single time. It was killing their server pretty quickly.
But the most interesting part is that all the requests were coming from valid and legitimate WordPress sites. Yes, other WordPress sites were sending that random requests at a very large scale and bringing the site down.
The WordPress exploit was taking advantage of the way "pingbacks" work. Attackers were using sites to add pingbacks to amplify an attack on a third party site (also, ironically, a WordPress site).
It's not just Facebook, or Google - it's inherent in the way caching is designed to work.
Not Just HTTP
This isn't just an issue with HTTP. We can see similar behavior in a DNS exploit that renders DNS caching ineffective as protection against certain attack types. In the DNS case, querying a cache with a random host name results in a query to the authoritative (origin) DNS service. If you send enough random host names at the cache, eventually the DNS service is going to feel the impact and possibly choke.
In general, these types of exploits are based on protocol and well-defined system behavior. A cache is, by design, required to either return a matching object if found or go to the origin server if it is not. In both the HTTP and DNS case, the caching services are acting properly and as one would expect.
The problem is that this proper behavior can be exploited to affect a DDoS attack - against third-parties in the case of Facebook/Google and against the domain owner in the case of DNS.
These are not vulnerabilities, they are protocol exploits. This same "vulnerability" is probably present in most architectures that include caching. The difference is that Facebook's ginormous base of users allows for what is expected behavior to quickly turn into what looks like an attack.
The general consensus right now is the best way to mitigate this potential "attack" is to identify and either rate limit or disallow requests coming from Facebook's crawlers by IP address. In essence, the suggestion is to blacklist Facebook (and perhaps Google) to keep it from potentially overwhelming your site.
The author noted in his post regarding this exploit that:
Facebook crawler shows itself as facebookexternalhit. Right now it seems there is no other choice than to block it in order to avoid this nuisance.
The post was later updated to note that blocking by agent may not be enough, hence the consensus on IP-based blacklisting.
The problem is that attackers could simply find another site with a large user base (there are quite a few of them out there with the users to support a successful attack) and find the right mix of queries to bypass the cache (cause caches are a pretty standard part of a web-scale infrastructure) and voila! Instant attack.
Blocking Facebook isn't going to stop other potential attacks and it might seriously impede revenue generating strategies that rely on Facebook as a channel. Rate limiting based on inbound query volume for specific content will help mitigate the impact (and ensure legitimate requests continue to be served) but this requires some service to intermediate and monitor inbound requests and, upon seeing behavior indicative of a potential attack, the ability to intercede or apply the appropriate rate limiting policy. Such a policy could go further and blacklist IP addresses showing sudden increases in requests or simply blocking requests for the specified URI in question - returning instead some other content.
Another option would be to use a caching solution capable of managing dynamic content. For example, F5 Dynamic Caching includes the ability to designate parameters as either indicative of new content or not. That is, the caching service can be configured to ignore some (or all) parameters and serve content out of cache instead of hammering on the origin server.
Let's say the URI for an image was: /directory/images/dog.gif?ver=1;sz=728X90 where valid query parameters are "ver" (version) and "sz" (size). A policy can be configured to recognize "ver" as indicative of different content while all other query parameters indicate the same content and can be served out of cache. With this kind of policy an attacker could send any combination of the following and the same image would be served from cache, even though "sz" is different and there are random additional query parameters.
/directory/images/dog.gif?ver=1;sz=728X90; id=1234 /directory/images/dog.gif?ver=1;sz=728X900; id=123456 /directory/images/dog.gif?ver=1;sz=728X90; cid=1234
By placing an application fluent cache service in front of your origin servers, when Facebook (or Google) comes knocking, you're able to handle the load.
There have been no reports of an attack stemming from this exploitable condition in Facebook Notes or Google, so blacklisting crawlers from either Facebook or Google seems premature. Given that this condition is based on protocol behavior and system design and not a vulnerability unique to Facebook (or Google), though, it would be a good idea to have a plan in place to address, should such an attack actually occur - from there or some other site.
You should review your own architecture and evaluate its ability to withstand a sudden influx of dynamic requests for content like this, and put into place an operational plan for dealing with it should such an event occur.
For more information on protecting against all types of DDoS attacks, check out a new infographic we’ve put together here.
Scott Jenson leads a project called The Physical Web within the Chrome team at Google. Project members are working to take the scalability and openness of the web and use it to talk to the exponentially exploding range of smart devices. Nearly every company today working on the IoT comes up with the same basic solution: use my server and you'll be fine. But if we really believe there will be trillions of these devices, that just can't scale. We need a system that is open a scalable and by using the URL as a basic building block, we open this up and get the same resilience that the web enjoys.
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