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Defending at Machine Speed: Predict, Adapt, Stop Agentic Attacks

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Defending at Machine Speed: Predict, Adapt, Stop Agentic Attacks

Transcript

AI powered attacks don’t follow a script.

They continuously adapt, testing new techniques, pivoting around defenses, and exploiting the unique weaknesses of every environment. Multiple benign alerts can indicate a broader, more complex attack. Traditional defenses, though, were never designed to keep pace with attackers that learn and evolve at machine speed. But what if your security platform could defend using a defending agent that’s customized to your environment, continuously predicting multistage attack chains, and creating customized protections before attackers strike? That is the power of Cato Agentic Threat Prevention. Cato Agentic Threat Prevention begins with knowing what’s on each customer’s network. Cato shared context notes hundreds of fields from all network assets and traffic.

All of this information is used not only to make more informed security decisions, but security predictions. Attackers used to move at human speed, but now attacks are agent enabled, which means they’re adaptive and automated, so defenses must be as well. The Agentic Threat Prevention screen shows AI findings and reasonings in real time and points to the resulting behaviors, controls, and events. Here, Agentic Threat Prevention has noticed a host for the first time attempting to download PS tools, which are used in remote process execution.

Agentic Threat Prevention predicts the use of these tools as lateral movement and automatically restricts both the lateral movement and the execution of the tools. But agentic attackers are adaptive, and this attacker quickly pivots to install OpenClaw on the host. With the context of the environment in mind and having seen previous suspicious tool downloads earlier, Agentic Threat Prevention predicts additional tool usage by this attacker and instantly blocks the ability to download further OpenClaw installations, GitHub skill installations, and access to other malicious tools via NPM.

Traditional defenses would normally take hours or days to correlate, identify, and react to this attack.

By then, this attack would have been completely successful. But in the timeline of events, we see that Agentic Threat Prevention was able to analyze, predict, and block this agentic attacker autonomously within one second to prevent the attack from completing.

That is the kind of machine speed defense required to defeat agentic attacks. The new protections are enforced throughout the entire organization because the Cato global platform works from a single policy. Users don’t have to worry about ensuring protection reaching the right places because it’s applied globally. Frontier AI gives attackers new levels of speed, adaptation, and scale. To defeat an agentic opponent, organizations need agentic defenses. Cato agentic threat prevention helps stop AI driven attacks by using customer specific context to predict attacker behavior, adapt protections automatically, and enforce prevention globally automatically platform. The result is prevention at machine speed built for the pace of modern attacks.

To learn more about how Agentic Threat Prevention could help secure your network, visit us at catonetworks.com.

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Secure Enterprise AI Apps and Agents

Product video

Secure Enterprise AI Apps and Agents

Transcript

What happens when a user finds a way to extract data from your internal application?

What if a prompt manipulation causes your customer facing chatbot to respond in ways you never intended?

When something does go wrong, does your security team have any record of what happened?

For most organizations deploying AI applications today, those aren’t hypothetical questions, they are gaps. Cato AI Security closes them.

This is guard logging in Cato AI Security. Security teams can see every interaction with the AI application, who used it, what was sent, and whether policy was violated. Every session tracked with invocation count, detection count, and timestamps.

This is also your audit trail. If a compliance or legal question ever comes up about your AI application and what it was doing on a specific date, this is where you go.

Opening a session, here is what enforcement looks like at the individual call level. The user’s prompt contains sensitive data anonymized before it reached the model. The model’s response contains sensitive data anonymized before it reached the user.

Pulling back to the guard overview, you can see the full picture across all activity. The hit rate shows the split between violating and safe prompts and the detection breakdown shows which policy rules are doing the work.

The usage over time graph shows exactly when activity spiked and where enforcement kicked in. This is what runtime protection looks like across a deployed AI application.

The detection logic behind all of that comes from engine profiles. Configurable sets of detectors scoped to your application specific risk surface. Address, name, phone number, more. You define what sensitive means for your context and that profile applies consistently across every interaction the application handles.

AI applications are moving into production faster than security controls have been able to keep up. Cato AI Security changes that. Runtime visibility into every interaction, policy enforcement on what goes in and what comes back out, and a complete audit trail from day one.

To learn more or request a demo, visit catonetworks.com.

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Control How Your Enterprise Uses AI

Product video

Control How Your Enterprise Uses AI

Transcript

How many AI tools are your employees using right now?

Do you know which ones are sending data outside of your network? And if someone pasted customer records into ChatGPT this morning, would you know about it? For most security teams, the honest answer to all three of these is no.

Cato AI security gives you the visibility and control to change that. Let me show you what that looks like.

This is shadow AI in Cato AI security.

Every AI application active in the environment automatically discovered and risk rated.

Perplexity, Microsoft Copilot, Cloud, all high risk, all already being intercepted via AI Proxy. That means Cato isn’t just seeing the connection, it’s inspecting what’s inside the prompt and the response.

ChatGPT for business is low risk because it’s sanctioned. This is a living inventory that updates continuously, not a one time scan.

Now let’s look at what these tools are actually being used for. In session explorer, every session is logged with application, topic, user’s intent and any violations that were triggered.

There are some sessions on claud and perplexity that are flagged, blocked PII on major AI apps, Personal data in the prompt caught in transit.

The grok session right above it is clean, same environment, different behavior, both visible. This is the audit trail that compliance teams have been asking for. For most organizations, it’s the first time security has ever had this level of detail on AI usage. And here’s why governance actually happens.

One rule block PII on major AI apps run through the network proxy across any source covering every application in the environment.

The action drop down is worth a look. You’ve got block, monitor, anonymize, unblock, and anonymize and monitor. That last option is the one that changes the conversation. The session continues, the sensitive data gets masked before it reaches the model, and security gets the full log. You’re not telling employees they can’t use AI, you’re making sure the data stays where it’s supposed to.

Governing AI usage isn’t about blocking tools, it’s about having the visibility to understand what’s happening, the context to make informed policy decisions, and the controls to enforce them consistently across every user and every application.

That’s what Cato AI Security delivers. To learn more or request a demo, visit catonetworks.com.

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Shadow AI Is Everywhere. Cato Puts You Back in Control

Product video

Shadow AI Is Everywhere. Cato Puts You Back in Control.

Transcript

Hello and welcome to another video from Cato Networks. Generative AI boosts productivity, But how much sensitive data is being shared? Could the use of Gen AI lead to data leaks or compliance issues? And what if AI chatbots generate flawed outputs that mislead business decisions?

Lack of visibility into Gen AI usage creates serious risks. That’s why Cato introduced GenAI Security Controls as a native extension of Cato CASB. It gives organizations full control over GenAI activity with no extra deployments or consoles or licenses. Let’s dive in.

The Cato Gen AI dashboard gives IT and security teams instant visibility into Gen AI application usage across the organization. It spotlights which apps are sanctioned or unsanctioned, risky apps, alongside with data violations, and the amount of users leveraging AI apps.

With built in categorization by use case, from conversational to code generation, it helps teams quickly understand how GenAI is being used. The usage breakdown gives IT teams a real time pulse on how Gen AI tools are used. You can track blocked, monitored, or allowed actions, see which apps are most active, who’s using them, and the type of activity performed.

From top apps like ChatGPT and Copilot to individual user behaviors, Cato makes ShadowAI visible and manageable. Cato delivers explicit usage visibility by identifying the type of sensitive data being shared, where it’s going, and who is sharing it.

Whether it’s source code, financial records, API keys, or personal data, violations can be traced back to specific users. The dashboard reveals policy and helps I teams understand exactly which data was uploaded to which application and whether the action was allowed or blocked, enabling swift mitigation and reinforcing the organization’s overall security posture.

The Cato’s application control engine has been enriched with fine grained Gen AI enforcement options.

Security teams can create category based rules to block risky tools like code assistance, restrict specific actions such as file uploads, or enforce tenant level access for corporate environments only.

Policy based controls embedded into the dashboard make enforcement precise, scalable, and aligned with business risk. Gen AI adoption doesn’t have to come with risks.

With Cato’s Gen AI security controls, enterprises can embrace Gen AI to boost productivity without sacrificing security. Be sure to check out our website for more information. Thanks for watching.