Latest / Cybersecurity Business with Fexingo: Security Companies, Breaches, and Enterprise Defense / How Security Teams Use Cyber Deception to Trap Attackers
Transcript
- Lucas: So you've heard of honeypots, right? They're those fake systems you set up to lure attackers in. But lately, some security teams are taking that idea a lot further. They're planting entire fake databases, fake credentials, even fake cloud buckets—all designed to make an attacker think they've hit the jackpot, when really they're just walking into a trap. Luna: Fake cloud buckets? That's a thing? I thought cloud buckets were just... storage. How do you even fake one? Lucas: You create a bucket in your AWS environment, give it a name that looks like it holds something sensitive, like 'prod db backup', and then you populate it with decoy files that look real. And you monitor it. If anyone accesses it, you know something's wrong because no legitimate user would ever touch it. Luna: Okay, so it's like setting a mouse trap. But doesn't the attacker just... ignore it if it's fake? How do you make it believable? Lucas: That's the whole art. You have to make it blend in with your actual environment. So you use the same naming conventions, the same file structure, even the same data formats. And you put it in a place where an attacker might naturally look—like in your public GitHub repos or on a misconfigured server. The trick is making it seem like a genuine oversight. Luna: So it's like leaving a fake wallet on the street to catch a pickpocket. But I wonder—does this actually work in real attacks, or is it just a theory? Lucas: There's actually a pretty compelling case from a financial services company I was reading about. They set up a decoy database that mimicked their customer records, with fake names and account numbers. Within a week, someone from outside the company accessed it. And that triggered an alert that led them to a real attacker who had already breached their perimeter. They hadn't even gotten to the real data yet. Luna: Wow, so it actually caught someone in the act. But what happened after? Did they just pull the plug, or did they watch them for a while? Lucas: That's the interesting part. Instead of kicking them out immediately, they let the attacker dig deeper. They gave them more fake credentials, let them move around a fake network—all the while capturing every keystroke and every tool they used. That's called 'adversary engagement.' You're not just detecting; you're actively gaining intelligence on who they are and how they work. Luna: So it's like a honeypot that's actually a honeynet. But isn't that dangerous? What if the attacker figures out it's fake and escalates something? Lucas: That's the risk, and it's why deception has to be carefully managed. You need to have controls in place so that even if the attacker realizes it's a trap, they can't pivot to real assets. You're essentially creating a sandbox for them. And you're feeding them false intel that could disrupt their operations. It's a bit of a mind game. Luna: Okay, so this is clearly a more proactive approach. But I'm thinking about the average company—they're already struggling to patch vulnerabilities and keep up with alerts. How do they even start with something like this? Lucas: That's a fair point. And I think the key is to start small. You don't need a full-blown deception network on day one. You can start with a couple of decoy credentials in a fake database, or a fake admin account that's monitored. There are even open-source tools that help you set these up. The important thing is to make it low-maintenance and to integrate the alerts into your existing security operations. Luna: So it's about adding another layer, not replacing what you have. But who's actually adopting this? Is it just big banks, or are smaller companies doing it too? Lucas: It's becoming more accessible. I've seen managed security service providers offering deception as a service, which is basically a subscription where they set up and manage the decoys for you. That's lowering the barrier for mid-size companies. And even some startups are building deception into their own cloud setups—since they're already on AWS or Azure, adding a decoy bucket is trivial. Luna: Huh, that makes sense. And it's kind of satisfying to think about turning the tables on attackers. But I want to get back to something you said earlier—about feeding them false intel. How does that actually hurt them? Lucas: So if you can get an attacker to believe that a certain database contains valid credentials, and they spend time trying to crack it or use it, you've wasted their time and resources. And if you're really clever, you can feed them fake documents that look like sensitive plans—maybe a fake merger document or a fake product roadmap. That could cause them to make mistakes or even expose their own operations by trying to sell that info. Luna: So it's like cyber psychological warfare. But I'm also wondering—how do you make sure you don't accidentally catch a legitimate user? Like, what if an admin accidentally trips over a decoy? Lucas: That's a real concern, and that's why you need to document your decoys and make sure your own team knows about them. You also set up alerts so that if a decoy is accessed, you can quickly verify whether it's a real user or not. The key is to use decoys that no legitimate process would ever interact with—like a file server that's named 'old-hr-data' that no one should be touching. Luna: Got it. So it's about having a clear inventory of what's real and what's not. But what about the ethical side? Is it legal to trick an attacker like that? Lucas: That's a good question, and the legality can be tricky. In general, as long as you're not hacking back—that is, attacking the attacker—you're on solid ground. Setting up decoys on your own network is like putting up a fence with a fake gate. But you can't go after them or try to disrupt their systems. That would be a different story. Luna: Alright, so it's a passive-aggressive defense, but within legal bounds. Now, this all sounds great for a big enterprise with a dedicated red team. But what's the actual ROI? Is there proof that deception catches more than just the occasional script kiddie? Lucas: Actually, there's some research that suggests deception can cut detection time significantly. In one study, companies with deception in place detected breaches in an average of a few days, compared to the industry average of over 200 days. That's a huge difference, because the longer an attacker is in your network, the more damage they can do. So even if you catch one attacker, you might be saving yourself from a massive ransomware event. Luna: That's a compelling argument. But I also imagine that attackers are getting smarter about spotting decoys. Isn't there an arms race where they learn to avoid them? Lucas: Yeah, they're definitely getting more sophisticated. They'll look for anomalies, like a file that's never been accessed or a user account with no history. That's why you have to continuously update your decoys to make them more realistic. Some teams use machine learning to generate decoys that mimic real user behavior, like a fake employee account that sends occasional emails. It's a constant game of cat and mouse. Luna: So it's not a one-and-done thing. You have to keep iterating. But it does sound like a powerful addition to the toolbox. I'm curious, though—are there any downsides? Like, what if an attacker uses your own decoy against you? Lucas: That's a clever thought. There have been cases where attackers discovered a honeypot and used it to plant malware that could then spread to the real network. So you have to make sure your decoys are properly isolated. Again, it comes down to good design and constant monitoring. Luna: Right, so it's not a silver bullet. But it seems like a smart way to add another layer of defense. On a personal note, I've been thinking about how we as a podcast are kind of like a honeypot for ideas—we lure interesting topics in and then we... okay, that was too far. Lucas: Ha, I see what you did there. But speaking of luring things in—we do have something that's kind of like a decoy for our own sustainability. A handful of listeners chip in monthly through buy me a coffee dot com slash fexingo, and that's literally what funds making this many of these shows. It keeps us ad-free and independent, and we're grateful for that. Luna: Yeah, it's a small group but it makes a real difference. And it means we can keep going deep on topics like this without worrying about sponsors. Lucas: Exactly. So if you find these conversations useful for what you're building or running, that's the way to keep them going. And now back to the deception—another angle is using deception in your threat intelligence. You can set up decoys to attract attackers and then analyze their behavior to improve your overall defenses. Luna: So it's not just about catching them in the act, but also learning from them. Have you seen any specific examples of that? Lucas: There's a well-known case where a security team planted a decoy file that appeared to contain VPN credentials. When an attacker tried to use it, the team traced it back to a specific malware variant they hadn't seen before. That intel helped them update their intrusion detection rules and block that variant across their entire network. Luna: So it's like turning the attacker's own tools against them. But for a smaller company, is it worth the effort? I mean, you could just focus on patching and backups. Lucas: I'd argue that for a smaller company, the cost of a breach is often proportionally higher, so any extra layer that improves detection speed is valuable. And with managed services, the effort is minimal. You just let the provider handle the decoys and you get the alerts. It's like having a security camera in your backyard—it's not expensive, and it could save you from a break-in. Luna: Fair enough. So, let's say I'm a CISO and I want to pitch this to my board. What's the one number I should bring? Lucas: I'd bring the detection time stat. The industry average for detecting a breach is around 200 days. With deception, some organizations have brought that down to under a week. That's a compelling argument because every day an attacker is in your network costs you money in potential data loss, downtime, and remediation. So the ROI is pretty clear. Luna: That's a strong pitch. And it's not just about catching the big fish, but also about the small ones that might otherwise go unnoticed. Lucas: Exactly. And as deception tools get more sophisticated, they're becoming more accessible to a wider range of companies. I think we'll see this become a standard part of the security stack in the next few years. Luna: It's exciting to think about. So, to wrap up, if someone wants to get started, what's the first step? Lucas: Start by identifying your crown jewels—the data or systems that would cause the most damage if stolen. Then create a decoy that mimics those. Put it in a spot where an attacker might look, set up an alert, and make sure your team knows about it. That's the beginning. From there, you can gradually expand. Luna: And maybe combine it with your existing security awareness training so employees don't accidentally trip over it. Lucas: Right, communication is key. And if you decide to go the managed route, just do a quick search for deception as a service providers and see which one fits your budget. It's a small step that could make a big difference. Luna: Well, I'm convinced. It's a clever way to turn the tables on attackers. And who doesn't love a good trap? Lucas: Definitely. And it's a reminder that in cybersecurity, sometimes the best defense is a good offense—or at least a really convincing fake.