Runtime Detection

Containers operate at a speed and scale that overwhelm traditional security approaches, creating new opportunities for attackers to leverage highly dynamic, ephemeral applications to their advantage. Vulnerabilities and misconfigurations can be exploited to carry out attacks on containerized applications with greater speed and scale, and within shorter time spans, than ever before.

StackRox automatically detects container attacks in seconds with machine learning that generates a full behavioral context of each application.

When a Fortune 500 financial services firm deployed StackRox to secure its containers, it detected threat vectors that gave malicious actors the opportunity to escalate privileges, establish persistence, and spread to other systems. StackRox enabled its security team to detect, investigate, and fully understand these attack vectors.

Fingerprinting

Expose Attacks in Real Time

StackRox pinpoints container threats by identifying attacker activity as it occurs. Detect anomalous process execution, container breaches, lateral movement, secrets exfiltration, data leaks, crypto mining, and more.

Build a complete picture

Adapt Detection

StackRox’s machine learning detects anomalous activity based on the behavioral context of each application. Detection models auto-tune as activity changes, without the need for manual training.

Generate summary reports

Determine Root Causes Faster

Use StackRox to unmask indicators of compromise, investigate attacker techniques, and analyze event context over any time horizon. Accelerate root cause analysis with a deeper understanding of attack patterns.

See StackRox in action

Watch Now: Machine learning demo

In this video, hear how StackRox automatically analyzes indicators of compromise and detects attacks across distributed applications.

Detection rules