We at Capsule8 have put a lot of thought into our product by thinking about what would make us most mad as hackers if we encountered it while attacking an organization.
One difference between Capsule8 and other Linux detection solutions is that our detection happens locally. It’s far less expensive for everyone to do computations locally vs. sending off the machine via the network, and we like avoiding unnecessary pain. We also make Capsule8’s resource cost tunable, so you can set how much CPU time goes towards Capsule8 doing its thing.
How you configure Capsule8 depends on your risk tolerance and your preference. This is how we’ve gotten the thumbs up from Ops, even at large enterprises. But what’s extra cool about Capsule8 is that we use kprobes + perf in an intelligent way, driven by our extensive experience breaking into systems.
Think of it like this: if you want to know whether someone broke into your apartment, there are a few strategies you could create. The most obvious ones would be catching the window breaking, the doors being bashed in, or the safe with the jewels opening. This is where our exploitation expertise comes in handy (more on that below) because we look at what attackers must do to complete an attack.
We maintain multiple vantage points, with an eye to the attacker’s “kill chain” — like looking at the front door, window, stairs, and closet door to the safe. You could also create a policy like: normally you hear the front door open before the window opens, so if you hear the window open before the front door, that’s weird. Think of this as the “check the context around the window opening” strategy.
Most ML, AI, and other mathematically-magical solutions are more like: “Let’s spend some time counting all the times the doors opened, and then send alerts on anything that deviates from this baseline we established.” Some go to an extreme and perform analysis that sounds cool, akin to asking, “Are the bricks moving? We should analyze the atomic states of the bricks in the building, maybe we should look at the chemical composition of the glass, too.”
For too many of these ML and AI-based solutions, they not only ignore how attackers actually behave, but also end up wasting a lot of network traffic and compute time. No one wants their time wasted, and the organization certainly doesn’t want its resources wasted.
At Capsule8, we also want to make attackers sad — hopefully crushing their souls. Ideally, you want to pinpoint exactly which points are interesting to attackers in the kernel and watch those closely. This is where a deep bench of exploitation experience (like our Capsule8 Labs team) comes in handy. That way, you know which places in the kernel are most loved by attackers, and can collect data that matters rather than collecting all the things.
For example, attackers love popping shells. But developers and programs love using bash or bin shells, too — it’s just a handy tool that everything uses. Most solutions will create a rule like, “show me anytime a shell runs,” which is going to be all the time.
This sort of rule becomes functionally useless unless you absolutely love sifting through the same alert over and over. Capsule8 instead can determine the difference between a user or a program using it, and answer questions like, “Is this shell executing to routinely process a script, or is it interacting with a live user?”
Capsule8’s approach means we can detect the entire spectrum of unwanted behavior on Linux, from devs risking production stability to sexy kernel exploitation by motivated attackers. This includes real zero-days — not zero-days as in “a slightly modified malware strain,” but the top-shelf expensive stuff that is exploiting the system in a way you can’t patch.
If you want a cool recent example, check out our recent case study in detecting a compromise (specifically, a cryptominer) in our demo Kibana infrastructure. We also recommend checking out our Part 1 and Part 2 of how we exploited systemd (the first public exploit, I might add). The best part is, our stack pivot detection catches it — and that’s just one of the many detections we have in place. So it’s not about finding CVEs or anomalous behavior, it’s about finding the exact techniques attackers must use to compromise the system.
If you’re interested in learning more about how Capsule8 can protect your enterprise Linux infrastructure, request a demo.
Kelly Shortridge is currently VP of Product Management and Product Strategy at Capsule8. In her spare time, she researches applications of behavioral economics to information security, on which she’s spoken at conferences internationally, including Black Hat, AusCERT, Hacktivity, Troopers, and ZeroNights.
Most recently, Kelly was the Product Manager for Analytics at SecurityScorecard. Previously, Kelly was the Product Manager for cross-platform detection capabilities at BAE Systems Applied Intelligence as well as co-founder and COO of IperLane, which was acquired. Prior to IperLane, Kelly was an investment banking analyst at Teneo Capital covering the data security and analytics sectors.