Detect and Contain Lateral Movement in the Cloud with Illumio Insights

Cloud adoption is skyrocketing, and with it comes a new wave of threats.  

Attackers don’t just “break in.” They move across your network as fast as possible and hunt for high-value assets across sprawling cloud infrastructure. This tactic is called lateral movement, and it’s one of the hardest security breaches to detect and contain.

Traditional threat detection and response isn’t cutting it. Alert fatigue, siloed tools, and blind spots leave security teams scrambling while malicious actors creep quietly through east-west traffic.  

The good news is that a new generation of detection and response tools powered by artificial intelligence (AI) is reshaping the game.

In this post, we’ll break down what lateral movement is, why it’s such a critical risk in today’s threat landscapes, how AI is helping detect anomalies and contain attackers, and why Illumio Insights is the smarter way forward.

What is lateral movement?

If attackers gain access to your environment, their first step usually isn’t to exfiltrate data or run ransomware.  

Instead, they poke around. They scan for connections, attempt privilege escalation, and exploit gaps in security controls to move deeper into your environment.

This is lateral movement, navigating sideways across workloads once an initial foothold is established.

Think of it like a burglar who enters through an unlocked window. They don’t grab the first thing they see. They explore, test doors, and eventually find the safe with your most valuable items in the back bedroom.

In cloud environments, that “safe” could be:

• A database with customer PII
• A DevOps pipeline with secrets and tokens
• SaaS integrations critical to business operations

Attackers’ goals are persistence and privilege. Lateral movement is their path to both.

Why detecting lateral movement in the cloud is so hard

Security teams are confident in catching north-south traffic (the in-and-out flow between users and the internet). But east-west traffic — the workload-to-workload chatter inside hybrid environments — is another story.

Here’s why detecting lateral movement in the cloud is so challenging:

• Blind spots multiply. Ever-changing cloud workloads appear and disappear constantly. Without consistent security that changes with it, attackers can exploit the gaps. ‍
• Alerts pile up. Tools that generate thousands of signals often can’t separate noise from true emerging threats. This leads to alert fatigue in your security operations center (SOC) team and the potential to miss alerts that matter. ‍
• Anomalies hide in plain sight. Without smart behavior analysis, suspicious user activity looks just like normal traffic. Attackers can hide in your cloud environment’s shadows for a long time to avoid detection.  ‍
• Identity gets abused. Stolen credentials let threat actors act like insiders, bypassing traditional defenses. Logins can look legitimate and let attackers get past your security. ‍
• Legacy tools can’t keep up. Legacy detection and response tools weren’t designed to detect lateral movement across modern cloud infrastructure. This leaves security gaps and inconsistencies that attackers find and abuse.

Despite more security spending than ever, organizations are struggling to secure the hybrid cloud. It’s no wonder bad actors can dwell undetected for weeks while preparing for devastating attacks.

Today’s most popular detection and response tools

Organizations rely on multiple categories of tools for threat detection and response.

SIEMs  

SIEMs (security information and event management) collect logs and telemetry from across your environment.  

They’re great at archiving vast amounts of data, correlating alerts, and supporting compliance. But in practice, SIEMs often struggle with speed.  

By the time analysts dig into logs, malicious actors may already have escalated privileges and moved laterally.  

SIEMs are reactive. They tell you what happened after the fact, not what’s happening in real time monitoring.

EDR and XDR  

EDR (endpoint detection and response) tools focus on endpoint activity, such as tracking processes, file changes, and user activity on servers and devices.

They’re highly effective against ransomware or a phishing attack that lands malware on a laptop. But when lateral movement occurs across cloud infrastructure, EDR can’t always follow the attacker beyond the endpoint.  

XDR (extended detection and response) platforms extend visibility across email, identity, and endpoints, but they still have blind spots in detecting east-west traffic in the cloud.

NDR  

NDR (network detection and response) solutions monitor network flows, applying behavior analysis and machine learning to detect anomalies in traffic. They’re particularly strong at spotting unusual lateral communications or hidden command-and-control channels.  

However, in elastic and ephemeral cloud environments where workloads spin up and down constantly, NDR can be challenged by scale and complexity. Attackers can blend into normal patterns of network traffic, slipping past even the smartest filters.

IAM and PAM

Since most lateral movement depends on compromised credentials, IAM (identity and access management) and PAM (privileged access management) tools are critical. They help enforce security controls, manage least privilege, and prevent unchecked privilege escalation.

But they don’t provide visibility into what attackers do after they’ve hijacked valid accounts. In other words, they can block initial abuse but often miss the downstream activity of threat actors once access is gained.

SOAR  

SOAR (security orchestration, automation, and response) platforms are designed to speed up cloud breach response by automating workflows. They integrate with SIEM, EDR, and other tools to trigger playbooks (like disabling an account or isolating a host) when a threat is detected.  

The effectiveness of SOAR depends entirely on the quality of the detections feeding it, though. If upstream tools don’t see the anomalies detected in lateral movement, SOAR can’t respond to them.

CSPMs and CNAPPs

Cloud-native tools like CSPM (cloud security posture management) and CNAPP (cloud-native application protection platforms) focus on configuration and compliance in cloud environments. They reduce risk by ensuring security baselines are in place across services and workloads.  

While essential for preventing misconfigurations, most are not built to stop active threat actors moving laterally across your hybrid cloud.

How AI supercharges cloud detection and response

Each cloud detection and response tool provides a piece of the puzzle. What’s missing is correlation: the ability to analyze vast datasets, detect anomalies in context, and understand how malicious actors move inside hybrid environments.  

That’s where AI changes the picture.

The shift to AI in network security is essential. Attackers already automate. Defenders need to leverage AI to fight back.

AI offers your security team a fast, automated way to:

• Analyze vast amounts of data. AI can process logs, flows, and telemetry at a scale no human team could manage. ‍
• Monitor the network in real time. It enables detection of phishing attacks, lateral moves, and other behaviors as they happen. ‍
• Detect anomalies faster. AI-driven behavior analysis highlights risks traditional tools miss. ‍
• Prioritize alerts based on risk. Analysts see the riskiest attack paths first, not just a flood of alerts. ‍
• Quickly recognize behavior patterns. AI identifies repeatable behaviors of malicious actors and threat actors across environments.

AI security graphs: mapping the cloud’s hidden attack paths

A key AI innovation in cybersecurity is security graphs. An AI security graph builds a living, breathing map of your cloud infrastructure. It connects every workload, user, and communication, then uses AI to highlight unusual patterns.

With it, security teams can:

• Detect east-west traffic at scale
• See anomalies detected in context
• Simulate “what-if” scenarios to test security controls
• Spot privilege escalation attempts before they succeed
• Understand the potential blast radius of a breach

By leveraging AI, teams move beyond reactive alerting and into proactive cloud breach response.

Illumio Insights: AI-powered breach detection and containment

This is where Illumio Insights delivers. It’s the first platform to combine automated segmentation with AI-driven threat detection and response.  

With Insights, you unlock:

• AI breach detection: spot lateral moves attackers try to hide. ‍
• Unified visibility: map every workload and user activity across hybrid clouds. ‍
• Anomaly detection: identify anomalies in real time monitoring using AI-based behavior analysis. ‍
• Prioritized response: know which threat actors and attack paths matter most. ‍
• Automated containment: instantly block risky east-west connections with policy enforcement.

By leveraging the AI security graph, Insights allows you to see, understand, prioritize, and contain lateral movement attacks before they spread through your network.

Why Illumio Insights matters in today’s threat landscape

The stakes have never been higher. Threat actors are adapting fast, using AI-driven attacks to quickly and quietly burrow into cloud infrastructure.  

They’re exploiting gaps in security controls and masking their moves in user activity that looks normal.

Defenders can’t keep pace with manual methods alone. They need AI for internal threat detection, AI breach detection, and tools that can analyze vast amounts of data in real time.

That’s why Illumio Insights matters. It gives security teams the power to fight malicious actors on equal terms, using AI to surface anomalies detected at scale, contain breaches instantly, and restore confidence in their ability to stop attacks.

Contain the movement, control the outcome

The perimeter is gone. Breaches are inevitable. The real question is whether you can stop them from moving once they’re inside your network.

With Illumio Insights, you can. By combining AI for cloud security with segmentation, Insights empowers teams to detect anomalies, contain lateral movement, and shut down emerging threats before they cause lasting damage.

In today’s threat landscape, the organizations that survive aren’t the ones who stop every intrusion. They’re the ones who detect and contain lateral movement in real time.

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