State-Backed Hackers Are Using Gemini AI for Reconnaissance — And That's Just the Beginning
State-Backed Hackers Are Using Gemini AI for Reconnaissance — And That’s Just the Beginning
I’ve been watching the AI security space closely, and Google just dropped some news that confirms what many of us have been quietly worrying about. They’ve caught North Korean hackers using Gemini AI to conduct reconnaissance on their targets. This isn’t theoretical anymore — it’s happening right now.
When AI Becomes the Attacker’s Research Assistant
The threat actor Google identified is UNC2970, linked to North Korea, and they’re essentially using Gemini as a sophisticated research tool. Think about it from their perspective: instead of manually gathering intelligence on targets, they can now ask an AI system to help them understand infrastructure, identify potential vulnerabilities, and even craft more convincing social engineering attacks.
What makes this particularly concerning is how it scales the threat. Previously, thorough reconnaissance required significant time and expertise. Now, even less skilled attackers can leverage AI to conduct detailed target analysis. Google Reports State-Backed Hackers Using Gemini AI for Recon and Attack Support notes that various hacking groups are using these tools across “various phases of the cyber attack life cycle.”
We’re not just talking about reconnaissance either. The report mentions threat actors using AI for information operations and even model extraction attacks. That last part is especially interesting — they’re essentially trying to steal the AI models themselves.
The Ivanti Problem Keeps Getting Worse
Speaking of scaling threats, Ivanti is back in the headlines with more zero-day vulnerabilities in their Endpoint Manager Mobile (EPMM) platform. I know, I know — at this point, “Ivanti vulnerability” feels like a weekly occurrence, but this one highlights a bigger issue we need to address as a community.
The Ivanti EPMM Zero-Day Bugs Spark Exploit Frenzy article makes a crucial point: we need to move beyond the “patch and pray” approach. One expert quoted suggests eliminating needless public interfaces and enforcing proper authentication controls from the ground up.
This resonates with me because we keep seeing the same pattern. A vendor releases a product with extensive external interfaces, vulnerabilities are discovered, patches are released, and the cycle continues. Meanwhile, attackers are getting faster at weaponizing these flaws.
PyMuPDF’s Path Traversal Problem
Here’s one that might fly under the radar but could bite you if your organization processes PDFs programmatically. PyMuPDF version 1.26.5 has a path traversal vulnerability that allows arbitrary file writes through the ’embedded_get’ function.
The CERT advisory explains that the vulnerability stems from improper handling of embedded file metadata. Essentially, if you’re using PyMuPDF to process untrusted PDFs — which many organizations do for document analysis or content extraction — an attacker could potentially write files anywhere on your system.
This is exactly the kind of vulnerability that gets overlooked because it’s in a library rather than a headline-grabbing enterprise product. But if you’re running any automated PDF processing, you need to check your PyMuPDF version immediately.
Russia’s Communication Crackdown Continues
On the geopolitical front, Russia is escalating its attempts to block WhatsApp and Telegram as part of what BleepingComputer describes as an intensifying crackdown on communication platforms outside government control.
This matters for our field because it demonstrates how nation-states are increasingly viewing encrypted communication platforms as security threats to their own operations. We’re likely to see more countries following similar approaches, which could impact how organizations with global operations handle secure communications.
What This Means for Our Security Programs
The common thread through all these stories is the increasing sophistication and scale of threats we’re facing. AI is giving attackers new capabilities, traditional patch management isn’t keeping up with the vulnerability disclosure cycle, and even basic tools like PDF processors are becoming attack vectors.
Here’s what I think we need to focus on:
First, we need to start thinking about AI security more seriously. This isn’t just about protecting our own AI implementations — it’s about understanding how attackers are using AI against us. We should be experimenting with these tools ourselves to better understand their capabilities and limitations.
Second, the Ivanti situation reinforces why attack surface reduction matters more than ever. Every public interface is a potential attack vector, and we can’t rely solely on patching to protect us.
Finally, supply chain security extends to every library and dependency we use. That PyMuPDF vulnerability is a perfect example of how threats can hide in seemingly innocuous components.
The threat environment is definitely evolving, but I think we can adapt if we stay focused on fundamentals while keeping an eye on emerging risks like AI-assisted attacks.