Kubernetes runtime threat correlation
TL;DR
Falco event correlation tool for DevSecOps engineers managing 5+ Kubernetes clusters that automatically links container runtime anomalies (e.g., unexpected processes) to network flows, service mesh context, and privilege escalation paths in a single timeline dashboard so they can reduce mean time to detect (MTTD) runtime threats by 70% and cut manual investigation time by 80%.
Target Audience
DevSecOps engineers and security-focused Kubernetes admins at mid-market to enterprise companies running 5+ production clusters, who use Falco or similar tools but struggle with operational overhead.
The Problem
Problem Context
Kubernetes teams use tools like Falco and network policies to detect runtime threats, but they struggle to connect container-level events (e.g., unexpected processes) to network traffic or service context. This creates blind spots where attacks go unnoticed or require manual investigation.
Pain Points
Teams waste hours manually correlating Falco alerts with network flows or service mesh data. They lack visibility into privilege escalation chains across services and can't tie suspicious outbound connections to specific container processes. Existing tools generate noise without actionable insights.
Impact
Undetected runtime threats lead to breaches, compliance violations, and downtime—costing teams thousands per incident. Manual correlation also slows incident response, increasing exposure time. Teams end up treating Falco as a checkbox rather than a real security layer.
Urgency
Runtime threats like container process hijacking or lateral movement can compromise entire clusters in minutes. Without correlation, teams miss critical attack chains until it's too late. Compliance requirements (e.g., PCI, SOC2) demand visibility into these gaps.
Target Audience
DevSecOps engineers, SREs, and security-focused Kubernetes admins at mid-market to enterprise companies running production workloads. Teams using Falco, Aqua, or Prisma but frustrated with their operational overhead will also face this problem.
Proposed AI Solution
Solution Approach
A lightweight agent that ingests Falco (or other runtime detectors) events and automatically correlates them with network flows, service mesh context, and image provenance. It surfaces actionable threat timelines in a dashboard, reducing manual investigation time by 80%.
Key Features
- Threat correlation engine: Builds timelines linking container events to network traffic and privilege escalation paths.
- Dashboard: Shows correlated threats (e.g., 'Container X spawned
curl→ connected to IP Y → blocked by policy Z'). - Alerts: Slack/email notifications for critical correlations (e.g., lateral movement attempts).
User Experience
Users deploy the agent as a DaemonSet, then see a unified view of runtime threats in their dashboard. Instead of sifting through Falco alerts and network logs separately, they get a single timeline per workload. Alerts highlight only the most suspicious correlations, cutting investigation time.
Differentiation
Unlike Falco (which requires manual rule management) or Prisma (which lacks deep container-network correlation), this tool automatically ties container events to network context. It’s also lighter than Aqua, focusing only on correlation rather than full runtime protection.
Scalability
The agent scales with the number of clusters (per-cluster pricing) or users (per-seat pricing for large teams). Teams can add more clusters over time without reconfiguring rules—correlation logic adapts automatically.
Expected Impact
Teams reduce mean time to detect (MTTD) runtime threats by 70% and cut manual investigation time by 80%. They also gain compliance visibility (e.g., proving no lateral movement occurred) and avoid breaches from undetected attack chains.