Deconstructing eBPF for Cloud Threat Detection: Real-Time Visibility Without Performance Hit

eBPF (extended Berkeley Packet Filter) is changing the way we monitor cloud workloads. It offers deep, low-overhead visibility into system behaviour, without intrusive agents or kernel changes.

This briefing unpacks how eBPF works, what makes it useful for cloud threat detection, and how to deploy it securely.

What Is eBPF and Why It Matters in the Cloud

eBPF lets you run sandboxed programs in the Linux kernel to inspect or modify system events. It's fast, secure, and doesn’t require patching the kernel or installing custom modules.

For cloud workloads, eBPF can:

• Trace syscalls, process activity, and network events
• Enrich logs with runtime context
• Power real-time alerting without degrading performance

Key Benefits of eBPF for Threat Detection

1. Real-Time, Kernel-Level Observability

• Capture events before they hit user space
• Trace activity across containers and namespaces
• Detect file access, process spawning, and network connections

2. Minimal Performance Overhead

• eBPF is event-driven and JIT-compiled
• Far less overhead than traditional syscall tracing or audit logging, but still requires monitoring

3. No Kernel Mods or Inline Agents Required

• Load and unload eBPF programs safely at runtime
• Use portable programs across distributions
• Ideal for cloud-native environments like EKS, GKE, and AKS

Threat Detection Use Cases

1. Lateral Movement Detection

• Monitor for suspicious socket activity across pods or VMs
• Trace unexpected access to internal services

2. Privilege Escalation Alerts

• Capture setuid, capset, or other syscalls tied to permission changes
• Alert on new binaries being executed with elevated rights

3. File Access and Tampering

• Detect access to sensitive files in containers (e.g., /etc/shadow, /var/run/secrets)
• Catch attempts to overwrite binaries or config files

Example: If a container accesses /etc/shadow, Tracee logs the openat syscall along with the process name, arguments, container ID, and timestamp. This context is crucial for validating whether the access was expected or malicious.

4. Command and Control Beacons

• Monitor outbound traffic to rare destinations
• Flag suspicious DNS lookups or TLS connections from non-user processes

Tools That Use eBPF for Detection

• Falco: Behavioural runtime detection engine with eBPF backend
• Cilium Tetragon: Kernel-level observability and security policy enforcement
• Tracee: Open-source eBPF-based runtime security and forensics tool from Aqua Security
• Pixie: Observability platform built on eBPF (focused on telemetry and application visibility, does not include threat detection or alerting out of the box)

Deploying eBPF Securely in the Cloud

1. Choosing Tools That Fit

• Start with managed agents (e.g., EKS add-ons or DaemonSets) that abstract eBPF setup
• Test with open-source tools like Tracee to validate visibility and signal quality

2. Safely Controlling What Loads into the Kernel

• Only allow signed or verified programs to be loaded
• Use Linux Security Modules (LSM) to restrict program loading paths and actions

3. Being Careful with Syscall Access

• Ensure only privileged nodes or containers can access raw telemetry
• Keep detection paths separate from enforcement to reduce impact of false positives

4. Keeping an Eye on Performance

• Use BPF maps and metrics to track CPU or memory pressure
• Avoid attaching probes to high-frequency syscalls unless filters are applied

We’ve seen teams underestimate the performance impact when attaching probes to noisy syscalls like read or recvfrom. Always benchmark before scaling out.

Considerations and Limitations

• eBPF is Linux-only (no native support for Windows nodes)
• Requires kernel version 4.14+, though some features like LSM hooks or specific trace points need 5.4 or higher
• Complexity increases when tracing across multi-node or multi-tenant environments
• Requires tuning to reduce noise in high-volume systems

Final Thoughts

eBPF unlocks high-fidelity, low-overhead threat detection at the kernel level. For cloud workloads, it’s one of the few ways to gain real-time visibility without introducing fragility.

If you’re running Kubernetes in production, using eBPF isn’t optional, it’s foundational.

Start small. Monitor key syscalls. Validate alerts. Build trust in the telemetry. Then scale it across your cloud estate.

Next Steps:

• Test Tracee or Tetragon in a non-prod cluster
• Map your top detection use cases to syscall events
• Partner with your platform team to integrate eBPF into observability stack

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