What If Your Security Teams Could See Into The Future?

• Modern attacks don’t stay in one place anymore, making cross-domain visibility crucial for today’s defenders.
• An attacker’s last move can reveal a lot about their next one.  
• Predictive AI turns those behavioral patterns into intelligence, helping security teams anticipate an attacker’s next move and stop them in their tracks. 

For years, detection has served as the foundation of every cybersecurity strategy. And that’s not changing. But as AI continues to accelerate attacks, the gap between seeing an attacker’s latest move and understanding what they’re likely to do next is getting tougher to close. 

Agentic AI is a primary perp behind this shift. In the last year alone, AI has shown us that attackers can use it to execute workflows, adapt to changing conditions, and even spawn other agents to handle subtasks. All this at speeds that make human response times look, well, undeniably human. Exploits that recently took them days or weeks to execute will take just a minute by 2027. 

Now, add in bad actors' second-favorite advantage, highly interconnected environments, and you’ve got one worrisome landscape. As attackers chain tactics across endpoints, networks, cloud environments, and data repositories, they move from one control point to the next. And persistent attackers take plenty of opportunities to keep trying, adapting until something works. Block one path, and AI helps them find another. Disrupt one technique, they pivot—all within minutes. By the time analysts sort through telemetry from multiple domains to understand what’s happened, the attacker may already be two moves ahead.

But what if your teams could see four steps ahead of their attacker? Here’s how that works.

First, see the multi-vector attack for what it is  

Before you can predict an attacker’s next move, you need to understand the moves they’ve already made. While that may sound like a line out of The Art of War, the key to an attacker’s next move is often hidden within their previous move. 

That’s because modern, sophisticated attacks rarely stay in one place. In a single chain of events, an attacker can establish access through an endpoint, move laterally across the network, abuse credentials, and access sensitive data. Most security controls only see a piece of that, which leaves analysts to pick up the pieces and manually stitch together answers. And this comes at a high cost of defender’s time and energy—two resources at critically low levels in most SOCs. 

To go from behavioral datapoints to behavioral intelligence, security teams need to start connecting the dots. When you correlate activity across multiple vectors, the attack starts to look less like a collection of isolated events and more like what it actually is: a coordinated sequence of moves. Scattered behavioral data turns into invaluable intelligence that can help defenders understand what’s happening in their environment, and what might come next. 

Then, level the playing field with cross-domain correlation 

Native telemetry correlation brings signals across every domain to help security teams get a clear view of how individual events connect across an attack chain. Instead of investigating isolated alerts, analysts can start with the bigger picture: What is this activity telling us about the attack?

Consider a phishing email that delivers a beaconing agent. The attacker then begins listing network shares and creates a remote scheduled task. With cross-domain correlation, all these signals are brought together to unveil the attacker’s strategy. Now your team knows exactly what’s going on and why. That’s step one and two, complete. 

Here’s where AI makes it interesting 

Everything has a pattern. By analyzing thousands of real-world attack chains, AI can learn the playbook attackers repeatedly use to move from one stage to another. Instead of manually correlating fragments across disconnected tools, defenders can let AI solve the next move problem and focus on what’s most likely to happen next. 

But prediction is only useful when defenders can understand what’s happening. AI-generated incident summaries can turn complex security activity into clear, plain-language explanations. Analysts get a clearer picture of what happened, why it matters, and where to go next without having to stitch together every alert and event themselves. 

With a clearer view of where an attacker is headed, teams can raise the proper defenses, cut the right paths, and potentially save their organization billions. Because when analysts are able to see the patterns behind the noise, they can finally get ahead of the attack. 

That’s the unique, exclusive power behind Incident Prediction, a predictive AI capability engineered to uncover patterns and transform them into foresight. 

Anticipate an attacker’s next three to four moves

Trained on over 500,000 real-world attack chains analyzed by Symantec and Carbon Black Threat Hunters, Incident Prediction leverages AI-powered behavioral analysis and probability scoring to identify the likely next steps in an active attack. 

Instead of waiting for the next stage of an attack to happen, defenders can anticipate and automatically disrupt the chain before attackers reach the point of impact—and before data can be encrypted, stolen, or exfiltrated. For attacks that deliberately hide behind legitimate tools, like living off the land (LOTL) attacks, seeing the sequence can be the difference between suspecting an LOTL attack and stopping one.  

With Incident Prediction, defenders can identify high confidence attack sequences in 80% of real-world incidents, giving analysts the context and confidence to determine exactly where attention—and intervention—would make the biggest impact. And when the threat calls for it, protective policies can be enforced before damage occurs, then automatically reverted to baseline once the threat is neutralized. If you’re thinking that’s cool, Incident Prediction is merely one example of what becomes possible when AI actually delivers what the assistance and protection defenders want.

Stop leaving AI to the bad guys  

Seeing four moves ahead is a pretty wicked advantage. 

But predictive AI is only one piece of a much bigger shift happening in cybersecurity. As much as AI is giving attackers new ways to scale their operations and change the rules, it’s also giving defenders new ways to fight back. But attackers aren’t going to wait around for us to catch up. 

They’re putting AI to work at every turn. Defenders should do the same. 

That means looking beyond the hype and finding the areas where AI can actually help security teams grow faster, sharper, and frankly, a little less overwhelmed. From predicting an attacker’s next move to cutting through alert fatigue to correlating signals across domains and reducing hours of investigation to minutes, AI is changing what’s possible in the SOC. 

A new eBook, 8 Ways AI is Easing Stress on the SOC, takes a closer look at the ways AI is already transforming cybersecurity. No baseless promises. No sci-fi scenarios. Just eight practical ways AI is delivering real defensive value today.  

Ready to see predictive AI at work? Watch How to Predict Bad Actor Moves With AI for an exclusive look at Incident Prediction, part of Symantec CBX, and how security teams can use AI to disrupt attacks earlier in the sequence. Or reach out to your in-region partner to schedule a 1:1 demo.