Certificate Transparency Log Compromised via Salt Vulnerability
groups.google.com
groups.google.com
However some of the unfinished work on CT means that we're more vulnerable here than would be ideal.
For example: An adversary who does have the SCT private key can make any SCT. So they can make one which says this log saw a certificate last month, before their compromise, because that's just a date change and they get to pick what is signed. This claim would be untrue, but nobody would automatically notice that.
In theory the complete CT system could detect this SCT - at least probabilistically - because clients which are shown the SCT could periodically check whether a log consistent with that SCT actually exists and report mysterious SCTs that don't match. But that isn't yet built, a Chrome which is shown an SCT from a trusted log promising the certificate was logged last month just takes that as gospel truth.
Now for Google this is pretty satisfactory because their CT policy requires that you use their (Google's) logs. But for a third party like Apple it's a bit less comfortable. If the Google logs suffered a security breach, Apple has no reassurance that they would find there was a problem short of Google voluntarily letting them know.
https://sourcehut.org/blog/2020-04-20-prioritizing-simplitit...
Dozens of people wrote to me, aghast at the idea that I provision servers manually, wondering how I could refuse to use the rube goldberg machines that define the modern "cloud-scale" computing trends. It looks like it didn't take long for my approach to be validated.
Salt is complicated as hell. k8s, Docker, Ansible, they're all the same. Complicated systems break more often and more severely than simple systems. It's a simple fact, and I hope that our industry gets over its collective devops fetish sooner rather than later.
https://cve.mitre.org/cgi-bin/cvekey.cgi?keyword=ansible
Your servers ought to be simple, too. Once you're simple enough, the problems shrink and shrink until they're barely there. Or, you can go as complex as possible and just hide them in mountains of garbage. "There are two ways of constructing a software design: One way is to make it so simple that there are obviously no deficiencies, and the other way is to make it so complicated that there are no obvious deficiencies."
Seriously though, payment infrastructure actually is known for its reliability and fault tolerance. Banking systems don’t go offline terribly often.
Nowhere did I say you should be on one incredibly large server, nor that you should have a single point of failure. That wouldn't be simple, either, because it would fail to support the prime directive, or would require a great deal of gymnastics to. It's about balance. You don't need thousands of servers to make a reliable system.
I don’t know if they have a specific reputation for it. But their services were very reliable and resilient.
> The main reason banks don't go offline is because the core critical infrastructure is running on 50 year old mainframes that no one is allowed to touch because all of the greybeards with actual talent who made them are pushing up daisies.
This isn’t really true at all. The banks central ledger will likely be running on DB2, and that will almost never fail. But most of their infrastructure runs on more “modern” systems (DB2 is still modern if we’re being honest, it’s just more specialized). When you swipe your card somewhere, nearly all of the systems the transaction passes through are ordinary web services, running on ordinary architecture. That’s where the greatest risk of service disruption is. It’s just the final side effect is updating a record in a DB2 database somewhere.
Most banks also outsource a lot of the core system maintenance directly to IBM. A typical software or infrastructure engineer in a bank will have absolutely no contact with those systems.
> Nowhere did I say you should be on one incredibly large server
No, you just seem to think that reducing the number of components in your infrastructure is the key to reliability. If you want fault tolerance, then you generally want redundancy, and you want your services to fail gracefully (ie, not take down other non-dependant services when they do). Both of those things require deploying more servers.
If points of failure are a concern, then you also need to account for the fact that every single time you make a manual change you are creating a new point of human failure (with humans generally being the least reliable part of any well designed system). If you automate a change, you can spend more time scrutinizing it for mistakes, and be reasonably sure it’s deployed exactly the same everywhere. Combine that with blue/green, rolling or canary deployments, and automated testing, and you end up with something much more reliable than shelling your way across the entire infrastructure to deploy a single change. To suggest that deploying less infrastructure is a superior alternative really just comes across as ludditism.
What makes banking systems reliable is that there's so much built in latency in every operation that nobody really notices if something is down for six hours.
This is true for settlement, but not authorization. When you spend your money it could be hours or days until the transaction is correctly reflected in your balance. But in order to spend it in the first place the transaction has to be authorized, and this happens in real time. Depending on where you live, who you bank with, what kind of card you’re using, how you’re using it... this authorization may rely heavily on your bank being available for online transaction processing, or not very much. But unless you’re doing a transaction with one of those imprint devices, your transaction must be authorized in real time by somebody.
I carry some cash too. But the times I’ve needed it were for things like an outage of the internet connection at a restaurant, or an issue with a payment terminal provider (or for the very uncommon cash-only merchant).
> Nowhere did I say you should be on one incredibly large server, nor that you should have a single point of failure. That wouldn't be simple, either, because it would fail to support the prime directive, or would require a great deal of gymnastics to. It's about balance. You don't need thousands of servers to make a reliable system.
Heh those things go offline every night for 2 hour maintenance.
Also fun when those nice single points of failure crash (they do)
Source: work at a shop trying to _get out of_ greybeard mainframe to get more reliablity
How large is the company you work for (employees or revenue)? How many servers do you have to support that company?
“SourceHut [of which ddevault is the founder] has 10 dedicated servers and about 30 virtual machines, all of which were provisioned by hand... [It] made 4 thousand dollars in Q1 with two employees and an intern.” (from https://sourcehut.org/blog/2020-04-20-prioritizing-simplitit...)
> Oof... The smartest people I know generally assume the least of situations they are not intimately familiar.
Yeah, I generally think highly of Drew’s opinions on technical matters, but this thread is just painful to read.
Anyone whose properly managed more than a few servers realizes and understands this.
The correct way would be to just document the changes.
Maybe "don't have thousands of servers" is just a bad take :)
You haven't caught on that no one has said automation replaces testing or other processes but that seems to be the drum you're banging on. Ansible or whatever tool doesn't replace testing, monitoring, pentests, whatever else you want to do. Automation lets you fix the issues faster and replace servers faster and more reliably, once you have done the testing that you have to do either way.
Another part of the problem is that in the past they invested in every platform under the sun that ran the financial applications they required, so there was a lot of legacy platforms that they couldn't yet rationalize away (AIX, Solaris etc).
The other problem is that they are incredibly risk averse, and thus will build new platforms extremely slowly and only after immense testing will they cut over from the old platform to the new platform. They are typically averse to consolidation or rationalisation since the ongoing stability of the application is the most important factor to their business.
A virtualization umbrella project that I was working on 10 years ago for this bank that covered several "core" platforms (AIX, VMware, Solaris, etc) is still under way as we speak, with many applications still to be migrated from old platform to the new one, despite the original "replacement" hardware now being obsoleted by the manufacturer already, according to those I know that still work there. I wonder if they'll ever finish.
Now, at my current gig - we have 43 nodes - but each node can run 100+ k8s pods (and, they are beefy 768 GB nodes). Our administration overhead, in terms of people/effort/auditing is a fraction of what it was at the last gig. Also - Disaster and failover is just a matter of bringing up the clusters and persistent stores in another region. No need to keep compute on standby. This week, we're even doing a migration of a cluster from GKE to Azure. And it started out on AWS (though not in production) - I'm not in the sysadmin world anymore, but from what I've seen, things like k8s have made it a heckuva lot easier to do big things with fewer people.
My point is and has been much broader: these tools solve the same class of problems which are symptoms of a broken culture, and solve them poorly. It's no surprise to me that any and all of them have problems, have had problems, and will have more problems - because they're broken by design, and they "solve" problems that we shouldn't have.
Substantial experience says the simple way is the best to manage HPC systems, in particular, and it generalizes, like to managing teaching "clusters" with few resources[1]. There are minimal trades-off from just using things you already know -- package management, revision control, and initrd/pivot_root -- against using tools which are distinctly non-trivial, but make you look good for solving the extra problems and justify more manpower. I've used a cluster-building system from a maintainer and contributors with Ansible expertise and been unpleasantly surprised, if not as much as by several cluster vendors' products.
Of course you automate things like monitoring, alerts, and some problem mitigation, for which simple configuration management frees effort. Accidental and essential complexity, someone once talked about.
Goofing RSA is a more troubling sign, because it means there probably isn't anybody who understands how this stuff works in the room where plans to use it are made, and that means there will be security bugs forever.
Presumably other people don't agree with me or else there wouldn't be important stuff running on Salt?
The agent thing, though, would squick me out almost no matter which team implemented it.
Once your configuration management is tied into your CI/CD pipeline, I don't really see much of a difference between an agent running on each machine vs a master node that has a root ssh key into your whole fleet.
I was going to attempt to summarize both sides of the argument here, but instead I think it’s better if I just suggest that you take some time to attempt doing that yourself and try to understand the points that everyone else is trying to make. I don’t think it’s your point about excess complexity that’s garnering the downvotes (at least, I hope it isn’t), but rather (a) that you’ve tarred a very broad swathe of software with exactly the same brush, refusing to acknowledge the significant differences in design, implementation, and use between such diverse softwares as Kubernetes and Ansible; and (b) the dogmatism about there being no conceivable need for such any such tools under any circumstances whatsoever.
I’d be very interested in a blog post (if one hasn’t been published already) about how system management is done at Sourcehut. A lot of people (myself included) turn to the tools you’re disparaging to help them manage things like change tracking and testing server configurations before applying to production, and it would be interesting to read about how you manage these sorts of problems without introducing a tool to do it.