Exploring Host Security with eBPF: Building a Deep Kernel‑Level Monitoring Loop

Background

In cloud‑native and hybrid infrastructure, host security is a foundational pillar. Traditional host security solutions face challenges from evolving attack techniques, while eBPF provides deep kernel‑level perception and a closed‑loop monitoring mechanism.

eBPF Core Advantages

Kernel‑level visibility : Real‑time, complete system events (processes, network, etc.) are captured directly in the kernel, eliminating user‑space blind spots and latency.

Extreme performance : JIT compilation and an event‑driven model keep overhead minimal.

Dynamic programmability and safety : Programs can be loaded, updated, and unloaded at runtime without reboot, and a strict verifier ensures safety.

Security Benefits

Real‑time monitoring : Accurate data collection, process‑to‑file relationship profiling, and support for forensic analysis.

Fast response : Immediate blocking of sensitive file exfiltration, ransomware encryption, webshell drops, etc.

Advanced evasion resistance : Bridges the gap between user‑space and kernel‑space defenses.

Risks

Running eBPF programs in the kernel introduces some performance overhead and stability risks, prompting deeper research into eBPF‑based host agents.

eBPF Mechanism Overview

Hook Points

eBPF programs must attach to specific kernel hook points to be triggered. Linux provides a rich set of hooks, including:

Tracepoints – predefined static probes (e.g., tracepoint/syscalls).

Kprobes/Uprobes – attach to kernel and user‑space functions.

Network hooks – XDP (driver layer), TC (traffic control), sockets, etc., for high‑performance network filtering.

Other – perf events, LSM security hooks, etc.

Loading Process

eBPF consists of a user‑space loader and a kernel program. The loader compiles source code to eBPF bytecode, passes it to the kernel via the bpf() syscall, where the verifier checks safety, the JIT compiler translates it to native machine code, and the program is attached to the chosen hook. Events are stored in eBPF maps, and user‑space communicates with the kernel through these maps.

Host Security eBPF Practice

Architecture

The design follows a closed‑loop: architecture design → scenario implementation → multi‑dimensional validation → continuous optimization . In the kernel, hooks load eBPF programs managed by a host eBPF Manager; maps store events; Netlink handles kernel‑to‑user communication. In user‑space, the host Agent manages eBPF lifecycle, configuration, and event processing, feeding data to security detection modules for deep analysis. The server side monitors configuration, stability, and emergency handling.

Process Collection Example

By attaching to key kernel functions such as tp/sched/sched_process_exec and kprobe/do_execveat, the eBPF program captures PID, PPID, command line, and executable path at process creation, storing them in maps. This avoids the data loss that occurs when user‑space agents read /proc after a short‑lived malicious process exits.

Network Collection Example

Hooks such as tcp_connect, inet_sock_set_state, and udp_sendmsg capture the association between a process’s task_struct and its socket, building a real‑time PID‑network‑tuple map without traversing /proc or parsing text.

BPF Compilation and Loading

Clang compiles BPF source to an object file, which the host Agent loads. The bpftool prog list and bpftool map list commands can query loaded programs and maps.

Result Comparison

In a command‑audit scenario, Netlink captures only PID, requiring user‑space to fetch additional fields, which fails for short‑lived processes. eBPF captures more fields directly, achieving a higher process capture success rate (92.04% vs 73.34%).

Performance Metrics

CPU Overhead

Tests on a 4‑core 16 GB machine using stress‑ng show eBPF adds roughly 0.5% more kernel CPU usage than Netlink.

Memory Overhead

Kernel slab memory growth is comparable between eBPF and Netlink under both process and network stress, indicating similar memory footprints.

Stability Mechanisms

Because eBPF runs in kernel space, stability monitoring is critical. The host Agent continuously collects eBPF program metadata (ID, name, load time) and runtime metrics (call count, CPU time). Threshold analysis on call frequency and CPU usage triggers alerts.

Alerting

When anomalies such as program initialization failure, configuration errors, or load/unload failures occur, the Agent pushes alerts to the server and a Feishu alert group.

Emergency Handling

To mitigate risks like kernel panics or resource contention, the system can automatically unload eBPF programs and fall back to user‑space solutions, or remotely switch, close, or unload specific eBPF functions. Additional emergency actions include stopping the Agent process or disabling modules, and providing remote debugging utilities (e.g., fetching vmlinux.h, exporting live configs, enabling debug logs).

Conclusion and Outlook

eBPF effectively addresses low process capture rates and weak process‑network correlation of Netlink, delivering real‑time security monitoring. Remaining challenges include optimizing resource usage under high concurrency, enhancing stability monitoring, and balancing low intrusion with high reliability. Future work may focus on:

Improving eBPF instruction efficiency and dynamic trigger rates.

Integrating eBPF data collection with AI models for behavior prediction.

Deepening kernel‑level threat detection to overcome user‑space evasion.

Overall, eBPF opens a new window of kernel visibility for host security; disciplined monitoring and emergency mechanisms are essential to translate its technical advantages into robust protection.

https://ebpf.io/what-is-ebpf/