Living off the Land Attacks and Emerging Cyber Threats - Cybersecurity Today

Podcast Summary: Cybersecurity Today

Host: Jim Love
Episode: Living off the Land Attacks and Emerging Cyber Threats
Date: December 3, 2025

Episode Overview

In this episode, Jim Love delves into the evolution and current trends of "Living off the Land" (LotL) cyberattacks—where attackers exploit legitimate software and tools to evade detection. The episode also highlights recent sophisticated phishing campaigns, real-world breach investigations, and eye-opening research into vulnerabilities in AI language models. Jim encourages defenders to rethink their approach to cybersecurity in response to these stealthy and persistent threats.

Key Discussion Points

1. Living off the Land Attacks: Definition and Evolution

[00:24–05:30]

Concept Origin: The term "Living off the Land" describes attackers leveraging trusted, built-in utilities (especially on Microsoft Windows) to hide their presence and persist on compromised systems.
Real-world Example:
- Jim references recent cyber operations in the Ukraine war, where intruders solely used Microsoft utilities to remain undetected.
- Binaries such as PowerShell, WMI, and the Windows Task Scheduler are commonly exploited.
Detection Challenges:
- Standard endpoint detection tools excel at finding malware or suspicious binaries but struggle with legitimate tools being misused.
- "Investigators in the Ukraine example... said the intrusion blended into regular administrative traffic. For weeks, what was dangerous looked almost identical to routine system work." — Jim Love [03:20]
Defense Recommendations:
- Behavioral logging and analysis are becoming vital: knowing what 'normal' looks like is crucial to spotting anomalies.
- “Zero trust and least privilege models can limit how much damage a built-in tool can do if it's misused, but it's not one control. We’re looking at an orchestrated defense.” — Jim Love [04:50]
- Emphasizes the need for layered, proactive defense and organizational learning.

2. Sophisticated Phishing Attacks Using Trusted Platforms

[05:31–08:40]

Emerging Phishing Technique:
- Attackers are sending fake calendar invites, resembling legitimate tools like Calendly, to hijack Google Ads and Meta ad accounts.
- The campaign targets business admins managing advertising budgets, not random users.
- “Instead of opening a scheduling page, the link may open a phishing site designed to steal either Google Ads or Meta business login credentials. And it’s a clever twist on this living off the land approach.” — Jim Love [06:10]
Attack Complexity:
- Uses familiar branding and authentic-looking login pages.
- No malware is delivered; the attack relies entirely on social engineering and trust in everyday tools.

3. Case Study: University of Pennsylvania Oracle Breach

[08:41–11:14]

Incident Summary:
- University of Pennsylvania (Penn) suffered a breach connected to vulnerabilities in Oracle’s E-Business Suite.
- Attackers accessed the university’s systems in August, prior to Oracle’s patch release in October.
- "Even when an organization patches quickly, the damage from an earlier compromise can continue to unfold months later." — Jim Love [10:35]
Implications:
- Illustrates how attackers can maintain persistence and leverage earlier access even after vulnerabilities are patched.
- Highlights the scale of risk for institutions holding vast data and financial assets.

4. AI Jailbreaks: Exploiting Sentence Structure

[11:15–15:00]

Problem:
- Large language models (LLMs) are susceptible to "jailbreaks," where users prompt them to bypass safety protocols.
Types of Jailbreaks:
- Traditional (social engineering): Rewording harmful requests as innocuous scenarios.
  - “The trick works on the framing, not the intent.” — Jim Love [12:17]
- Syntactic: Nonsense words or structures can also trigger unintended behavior.
New Research:
- A study from MIT, Northeastern University, and Meta found that some nonsensical phrases exploit hidden syntactic cues in LLMs’ training data.
  - “Some combinations of meaningless terms accidentally form structures that these large language models interpret as commands.” — Jim Love [13:35]
- Demonstrates that LLMs are sensitive to sentence shape and pattern, not just meaning.
Difficulty in Mitigation:
- These exploits are unpredictable and difficult to patch as they exploit generalized patterns, not specific vulnerabilities.
  - “Understanding why they work can bring us one step closer to higher levels of protection and defense.” — Jim Love [14:45]

Notable Quotes & Memorable Moments

On Defensive Limitations:
- “Nothing they do involves a suspicious binary, and nothing looks foreign to the system. These are the same tools administrators use every day, and they’re also tools Windows relies on, so you can’t simply block them.” — Jim Love [02:30]
On the Changing Nature of Attacks:
- “Attackers are now using the everyday cloud tools we depend on as their delivery mechanism. And when the threat arrives through something as ordinary as a meeting invite, the line between safe and suspicious becomes a lot thinner.” — Jim Love [07:55]
On Persistence after Breach:
- “The breach doesn’t end when the vulnerability is fixed. The challenge becomes understanding how far the original intrusion went and whether access that was gained early on could still be used quietly in the background.” — Jim Love [10:45]
On AI Vulnerabilities:
- “The researchers argue that this happens because models are more sensitive to shape and structure than pure meaning.” — Jim Love [14:00]

Important Timestamps

00:24 – Introduction to Living off the Land attacks
03:20 – Blending of attacker and admin activity
04:50 – Advocacy for orchestrated defense
06:10 – Fake calendar invite phishing campaign
07:55 – Shift to cloud tool-based attacks
08:41 – Penn Oracle breach timeline and lessons
11:15 – AI jailbreak problem introduction
13:35 – Research findings on syntax-based jailbreaks
14:45 – Path forward for AI security

Tone & Style

Jim Love’s delivery is informative, conversational, and laced with urgency, highlighting real-world implications for defenders and organizations. He balances technical explanation with actionable advice, making complex topics accessible for listeners.

Conclusion

This episode underscores the increasing sophistication of threat actors, who now exploit trusted tools, cloud services, and even quirks in AI models to evade detection and maintain access. Jim Love calls on defenders to adopt behavioral analytics, embrace zero trust, and stay informed about both classical and novel attack vectors. The takeaways are clear: vigilance, layered defenses, and continuous adaptation are essential in today's cybersecurity landscape.

Transcript

A (0:00)

Cybersecurity Today would like to thank Meter for their support in bringing you this podcast. Meter delivers a complete networking stack, wired, wireless and cellular in one integrated solution that's built for performance and scale. You can find them@meter.com CST living off the Land Attacks on Microsoft Attackers use fake calendly invites to hijack Google and meta ad accounts, Oracle breach claims yet another vict, and researchers trace AI jailbreaks to hidden patterns in sentence structure. This is Cybersecurity Today. I'm your host Jim Love. Living off the Land attacks is a phrase that was first coined about a dozen years ago by Christopher Campbell and Matt Graeber at DerbyCon3. It describes a technique where attackers can hide using existing software and utilities. I was reading about this and how it had been used in the Ukraine war, where intruders were relying entirely on Microsoft utilities to stay hidden. And then I looked around and I found more and more examples of where intruders were relying entirely on trusted Microsoft utilities. But now in North America, the stories are the same. Attackers start with a foothold, and they pivot using PowerShell WMI Task Scheduler, all legitimate Windows components. PowerShell might quietly download a script, WMI might execute commands remotely, a scheduled task or a Registry run key might be altered to keep the attackers hidden inside. And nothing they do involves a suspicious binary, and nothing looks foreign to the system. These are the same tools administrators use every day, and they're also tools Windows relies on, so you can't simply block them. And of course, that's why these attacks evade so many defenses. Endpoint detection and response systems are excellent at spotting malware, lateral movement, or even odd binaries. But when an attacker sticks to Microsoft signed utilities, there's often nothing to flag. Investigators in the Ukraine example that I was using said the intrusion blended into regular administrative traffic. For weeks, what was dangerous looked almost identical to routine system work. And the real risk isn't just the intrusion, it's the quiet persistence that follows. Living off the land techniques let attackers stay inside networks for long stretches of time, often without writing a single malicious file to disk. And I guess that's why defenders are being pushed to rethink how these tools are monitored. When the threat hides inside some normal system activity, the only way to spot it going offside is when you have an idea of what normal really is and a way to spot the difference. And that means logging that captures what these utilities are doing. But that logging is going more to a behavioral analysis that can surface these anomalies. Of course, zero trust and least Privilege models can limit how much damage a built in tool can do if it's misused, but it's not one control. We're looking at an orchestrated defense. And living off the land attacks are showing why that shift is becoming perhaps even more important. And you know how it is when you see something and it makes you think and then you keep seeing examples of the same thing over and over again. While I was working on that last story, David, our Monday host, sent me a story. And this time they were spoofing a different trusted utility. A new campaign is sending fake meeting invitations that look like the real thing, complete with branding, but from well known companies. But instead of opening a scheduling page, the link may open a phishing site designed to steal either Google Ads or Meta business login credentials. And it's a clever twist on this living off the land approach. Calendly is a tool that is used by a lot of people. And of course people click meeting links without thinking about it. And the attackers aren't dropping malware or trying to compromise devices. They're going after the people who control Google AdWords or meta advertising budgets. And the phishing pages are tuned specifically for them. Once an attacker gets access to an ad manager account, they can spend thousands of dollars in minutes running fraudulent campaigns or crypto scams, all billed to the victim, and all coming from what might be a trusted source. What makes this campaign stand out is the precision. The phishing isn't being blasted out to random users. It's aimed at people who manage business pages and have payment methods attached. The entire attack relies on trust, a familiar scheduling tool, a familiar business brand, and a login page that looks exactly like like Meta or Google's own interface. It's another reminder of how this living off the land idea is shifting beyond system utilities. Attackers are now using the everyday cloud tools we depend on as their delivery mechanism. And when the threat arrives through something as ordinary as a meeting invite, the line between safe and suspicious becomes a lot thinner. And again, as if to show how much damage can be done once somebody breaches your defenses and gets within your system, the University of Pennsylvania is reporting another data breach. This one appears to trace back to the Oracle E Business suite hack disclosed earlier this year. Penn says attackers stole documents from its Oracle EBS servers in August, months before Oracle issued patches for multiple vulnerabilities in in October. And even though those patches were applied, the university now believes the new breach may have stemmed from access the attackers gained during that earlier incident. And Penn is a major target. It's an Ivy League institution with more than 29,000 students, almost 6,000 faculty, and an operating budget of $4.7 billion. It also holds a $24.8 billion endowment as of mid and this isn't the first time it's been hit. Back in October, PEN disclosed a separate compromise involving its development and alumni systems, and in that case, a hacker claimed to have stolen personal information on roughly 1.2 million students, alumni and donors. What makes the new incident stand out is the timing. The attackers first accessed the Oracle EBS servers in August. Oracle then released patches in October. But Penn's latest investigation shows the intruders may have used the foothold from August to carry out newly reported data theft. It suggests that even when an organization patches quickly, the damage from an earlier compromise can continue to unfold months later. It's a reminder that once attackers get inside a system, especially one tied to business operations, the breach doesn't end when the vulnerability is fixed. The challenge becomes understanding how far the original intrusion went and whether access that was gained early on could still be used quietly in the background. And finally, a different story, but something that keeps coming up. One of the ways we could spot patterns in behavior and maybe work to defeat living off the land is in using AI. But AI has its own set of issues and problems, one of them being how easily it be jailbroken and turn what should be a trusted tool into a liability and an attack vector. We hear about a breach almost every couple of days. OpenAI reported one last week that was a major one. So most jailbreaks make sense in a human way. Someone reframes a harmful request so it sounds harmless, essentially socially engineering the model. The famous example is you can't ask it to build a bomb, but you can ask for help writing a scene in a community play where your character builds one. The trick works on the framing, not the intent. We've used this as little as last week to break one of the major models. It's a problem, and it's one they need to solve. But there's another problem that surfaced, and researchers have begun studying a stranger kind of jailbreak, the one built from strings of nonsense words or words appended to the end of sentences. These prompts don't look like trick questions or role playing setups. Many of them read like gibberish, yet they sometimes cause an AI system to ignore its own safety rules. And now a new study by researchers from MIT Northeastern University and Meta may explain why. In their paper with the mellifluous flowing title of syntactic domain Spurious correlations in Language models, which I'll translate for you into syntax How Sentence Structure Enables LLM Jailbreaks they show that many nonsense jailbreaks work not because of the words, but because of the syntactic patterns hiding underneath them. Some combinations of meaningless terms accidentally form structures that these large language models interpret as commands. In other words, they're using the correct grammar. But nonsense words syntax resembles that system level instruction learned during the training, the patterns that can slip past the safety layers added later. So just to recap, they're using a grammatic structure that's accurate but with nonsense words, although the system might recognize that grammatical structure, the words just slip past. The researchers argue that this happens because models are more sensitive to shape and structure than pure meaning. That doesn't mean they don't understand meaning they do, but they have this inherent flaw that calls them to look at the shape and structure of sentences as well. They generalize from these patterns in sentence construction, and those patterns can override the safeguards when they resemble the cues the model associates with higher level instructions. It also explains why gibberish jailbreaks are inconsistent and difficult to patch. They don't rely on a specific loophole, they rely on quirks in how the model processes language. And while both of these vulnerabilities breaking the frame and breaking the syntax have been known for some time, understanding why they work can bring us one step closer to higher levels of protection and defense. And that's our show for today. We'd like to thank Meter for their support in bringing you this podcast. Meter delivers full stack networking infrastructure, wired, wireless and cellular to leading enterprises and working with their partners, Meter designs, deploys and manages everything required to get performant, reliable and secure connectivity in a space. They design the hardware, the firmware, they build the software, they manage deployments and run support. It's a single integrated solution that scales from branch offices, warehouses and large campuses all the way to data centers. Book a demo@meter.com CST that's M E T E R.com/CST. And while the show is all news, there's some ideas that are important. I'd always love to hear from you on what you think. You can reach me with tips, comments, even constructive criticism. You can find me@technewsday.com or ca. Take your pick. Use the Contact Us page. If you're watching this on YouTube, you can just put a comment under the video or you can track me down on LinkedIn. As many of you have I'm your host Jim love. Thanks for listening.