Artificial intelligence has long been positioned as a defensive advantage, with faster detection. Better correlation. Smarter response.
This week, that narrative shifted.
New reporting confirms that state-backed threat actors are actively using Google’s Gemini AI to support real-world cyber operations, according to The Hacker News.
This is not about attackers generating spammy phishing emails or experimenting with AI out of curiosity. The activity described shows AI being used to accelerate reconnaissance, target analysis, malware development support, and operational planning. In other words, AI is now being embedded directly into the attack lifecycle.
Google’s Threat Intelligence Group observed multiple nation-state actors leveraging Gemini to assist with tasks that traditionally required time, research, and manual effort.
This included summarizing technical vulnerabilities, researching organizations and infrastructure, generating scripts and tooling concepts, and refining phishing and malware delivery techniques. The goal was not automation alone. It was speed and precision.
By reducing the time between target identification and execution, attackers gain a meaningful advantage. Campaigns become faster, more adaptive, and harder to disrupt once they are underway.
What makes this development important is not just that attackers are using AI. It is where they are using it.
Gemini is being applied before malware is deployed, before credentials are stolen, and before alarms typically trigger. That places AI squarely in the pre-intrusion phase, where most security tools have limited visibility.
Traditional defenses are designed to respond once something malicious happens. AI-assisted reconnaissance and planning leave far fewer artifacts, making early detection extremely difficult.
Once access is gained, everything that follows looks cleaner, quieter, and more intentional.
Many security programs assume that advanced attacks begin when malware executes or credentials are abused. This reporting shows that the real activity starts much earlier.
Research. Profiling. Simulation. Iteration.
All happening quietly, assisted by AI.
When identity, endpoint, cloud, and network signals are monitored in isolation, this buildup goes unnoticed. By the time alerts fire, attackers already understand the environment they are operating in.
AI-assisted attacks demand a different defensive approach. One that does not rely on single indicators or isolated detections.
A unified security platform like Seceon’s correlates identity activity, endpoint behavior, cloud telemetry, and network signals continuously. This makes it possible to surface subtle indicators that only become meaningful when viewed together.
This includes unusual reconnaissance patterns tied to privileged accounts, abnormal access sequencing across cloud services, early lateral movement behaviors, and activity that does not match historical operational baselines.
Instead of reacting to individual alerts, the platform evaluates intent and progression across the entire environment.
State-backed actors are signaling where cyber operations are headed next. AI is no longer just a defensive tool. It is becoming an offensive multiplier.
Organizations that continue to treat detection as a point-in-time event will struggle to keep up. The challenge is no longer just blocking attacks. It is recognizing when preparation itself becomes hostile.
In a world where attackers use AI before exploitation begins, visibility and correlation across systems become the only way to regain the advantage.
