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A free scan shows the junk files, broken settings and background clutter dragging Windows down - then fixes them in one click.Free scan · Windows 10 & 11eBPF lets Linux run verified programs at kernel hook points, where they can observe events and, depending on the program and tool, filter them, make decisions, or trigger actions. That makes it useful for runtime security and observability: tools can act close to process, file, system-call, and network activity instead of first sending every event to a user-space collector. eBPF does not replace every security agent, guarantee low overhead, or protect a host from an attacker who can disable its security components.
What eBPF is—and what it does in a security tool
eBPF is a Linux kernel facility for running verified programs at defined hook points. Programs can collect or modify information, make decisions, and cause side effects, subject to the program type, attachment point, permissions, and kernel support. The Linux kernel’s BPF documentation and the eBPF documentation describe program types, maps for sharing data, pinning, and capabilities; Cilium also describes eBPF as a flexible, efficient virtual-machine-like construct used for networking, tracing, and security, including sandboxing.
In security, a hook can expose an event such as a process execution, system call, file operation, or network operation to an eBPF program. A tool can then observe or filter that event and, where its implementation supports it, respond in or from the kernel. eBPF is the mechanism, not a complete security product: coverage and available actions depend on the tool’s probes, policies, and deployment.
Why observe events in the kernel?
Kernel-side filtering can reduce the need to forward every event to a user-space agent, and an in-kernel program can react close to the event it observes. Tetragon, for example, documents filtering, blocking, and reactions in eBPF for process execution, system-call activity, and I/O such as network and file access. This offers a useful placement advantage, but it is not a published guarantee of a particular latency, CPU cost, or resistance to tampering.
#1 Best Overall
What the tool sees also depends on where it attaches and what context it collects. A host-level event is not automatically enriched with Kubernetes pod, namespace, or service identity. Network observability tools built around Cilium can provide identity-aware workload and service visibility; runtime tools may emphasize process and system-call details instead. Check the identity fields and event types of the specific deployment before treating its feed as a complete account of activity.
How the main eBPF tools differ
These projects address overlapping but distinct jobs. Their documented capabilities are not evidence of equal coverage, performance, or enforcement behavior; evaluate them against the events and actions your environment needs.
Rank #2
| Tool | Signal coverage | Action depth | Identity context | Placement and overhead | Kernel and privilege notes |
|---|---|---|---|---|---|
| Tetragon | Process execution, system-call activity, file I/O, and network I/O (Cilium Tetragon documentation). | Security observability and runtime enforcement; documents in-kernel filtering and reactions (Cilium Tetragon documentation). | Kubernetes-specific identity fields: not stated in the cited Tetragon pages. | Can filter and react in eBPF rather than ship every event to user space; no comparable benchmark stated (Cilium Tetragon documentation). | Policy behavior depends on kernel and container knowledge; requirements vary by configuration (Tetragon tracing-policy documentation). |
| Cilium and Hubble | Network and service observability, including visibility into services and workloads (Cilium and Hubble documentation). | Network security visibility and control logic in Linux; specific enforcement actions depend on Cilium configuration (Cilium documentation). | Identity-aware visibility for services and workloads (Hubble documentation). | Built on Cilium and eBPF; a directly comparable overhead benchmark is not stated (Hubble documentation). | Requirements vary by Cilium features and environment; a single kernel or capability requirement is not stated on the cited overview pages. |
| Falco | Runtime event collection; exact coverage depends on the rules and driver configuration (Falco documentation). | Event-driven detection and alerting; in-kernel blocking is not established by the cited driver documentation. | Kubernetes-specific identity fields: not stated in the cited eBPF-driver page. | Its modern eBPF probe is an alternative driver; no comparable overhead benchmark is stated (Falco documentation). | Falco documentation identifies Linux 5.8 as the first kernel version with official support for its modern eBPF probe and notes that distributions may backport support. |
| OpenTelemetry OBI | Application and network observability (OBI documentation). | Instrumentation and collection; runtime security enforcement is not established by the cited documentation. | Depends on collected application and network telemetry; security-specific identity enrichment is not stated in the cited documentation. | Uses eBPF for observability and is designed to use only the capabilities needed for the selected configuration (OBI documentation); no comparable overhead benchmark is stated. | Needs interfaces for reading /proc, loading eBPF programs, and managing network-interface filters; the exact capabilities depend on configuration (OBI documentation). |
For runtime security observability and enforcement, Tetragon is the most direct fit among these examples: Cilium describes it as providing real-time, eBPF-based security observability and runtime enforcement. For network and service flows, Cilium with Hubble is the more focused choice. Falco is a runtime event-detection option, while OBI is aimed at application and network instrumentation rather than security enforcement.
Linux versions, capabilities, and compatibility
Linux 5.8 is a useful compatibility checkpoint, not a universal minimum for every eBPF program or tool. Falco’s documentation identifies it as the first kernel version with official support for the modern eBPF probe, while noting that distributions can backport support. Starting with Linux 5.8, eBPF permissions became more granular; the relevant capability depends on the operation and configuration.
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These capability classes do not mean that every eBPF deployment can run with the same minimal set. Program types, attach points, kernel version, distribution backports, and the tool’s configuration affect what is permitted. Check the documentation for the exact version and feature set you plan to deploy, and verify kernel support on the actual distribution rather than relying only on its version number.
Least privilege and safe policy rollout
Running as root is the simplest setup for some deployments, but it is not the only model. OBI documents narrower, configuration-dependent capability requirements. Grant only the permissions required for the selected features, and test the resulting deployment: a capability set that works for one observability configuration may not cover a different program type or network operation.
Enforcement policies need particular care. Tetragon’s tracing-policy documentation warns that low-level policies require Linux-kernel and container expertise and can cause unexpected behavior, including time-of-check-to-time-of-use (TOCTOU) issues, when configured incorrectly. A policy intended to observe or block a narrow event can have wider consequences if its selectors or conditions are wrong.
- Start with observation. Confirm that the policy matches the intended processes and events before enabling a blocking or reactive action.
- Validate scope. Test selectors against the host, containers, and workloads that should—and should not—match, including relevant namespace and identity boundaries.
- Roll out in stages. Apply changes to a limited workload first, watch for unexpected matches or interruptions, then expand deliberately.
- Plan recovery. Keep a way to disable or revert a policy if it disrupts legitimate work, and ensure the policy itself cannot be casually confused with complete host protection.
Runtime security also has a trust boundary. Cilium’s threat model recommends runtime security such as Tetragon for detecting container compromise, but identifies limits when an attacker has direct host namespace access or can disable the security components. eBPF monitoring should therefore complement, not replace, host hardening, access controls, and a response plan.
Choose by the problem you need to solve
- Choose Tetragon when the priority is observing process and system-call behavior and applying runtime responses close to those events.
- Choose Cilium with Hubble when the priority is identity-aware network and service visibility across workloads.
- Consider Falco when event-driven runtime detection is the goal and its driver and rules fit the target Linux environment.
- Consider OBI when application and network instrumentation is the goal and its configuration-specific privilege model suits the deployment.
No one of these choices establishes a universal replacement for agents. Decide based on required signals, whether you need alerts or enforcement, the identity context operators need, supported kernels and privileges, and the operational risk of policy mistakes. The projects’ cited documentation does not provide a shared performance benchmark for a like-for-like comparison.
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