eBPF for network monitoring and host-based IDS: use cases, risks and operational knowledge

eBPF for network monitoring has become a practical tool for many operators of Linux systems: it enables performant monitoring directly in the kernel without compiling fixed kernel modules. eBPF (extended Berkeley Packet Filter) is a kernel‑running, verified sandbox technique that allows small programs to be attached to hooks such as network paths, system calls or tracepoints. In combination with XDP (eXpress Data Path, a very early hook in the receive path) and userspace tools like bpftool or bpftrace, host‑based IDS functions and traffic analyses with low overhead can be realized. This guide shows when eBPF makes sense, which prerequisites are required, which typical risks arise, how to structure tests and rollout, and how to achieve secure integration into SIEM pipelines.

Why eBPF for network monitoring and host‑based IDS?

eBPF enables observation and limited intervention in deep system layers with low context switching overhead. For network monitoring this matters because packet‑related data is available very early in the receive path (with XDP even before the kernel stack). A host‑based IDS is a solution that detects suspicious activity on the host — for example unusual socket connections, suspicious process spawns or signs of lateral movement. With eBPF these signals can be collected cost‑effectively and with process context, without necessarily relying on physical network taps.

Concrete operational benefits

• Visibility in container and microservice environments where traditional taps are difficult.
• Lower CPU and memory usage compared to full userland packet inspection, since filters run in the kernel.
• Real‑time detection of anomalous connection attempts, DNS queries or system calls.

Prerequisites, architecture and compatibility

Kernel, distribution and CO‑RE

eBPF features evolve with the kernel. Newer features like CO‑RE (Compile Once, Run Everywhere — a mechanism that makes eBPF objects more portable) benefit from recent kernels and LLVM/Clang toolchains. In practice basic functions work from kernel 4.14; for stable CO‑RE support and verifier improvements 5.x kernels are preferable. Check the distribution documentation, as many distros provide backports.

# Kernel-Version prüfen
uname -r
# Prüfen, ob Kernel eBPF-Features kompiliert hat
zcat /proc/config.gz | grep -i bpf || grep -i bpf /boot/config-$(uname -r)

Tools, permissions and deployment variants

Standard tools are bpftool (inspection and management), bpftrace (ad-hoc tracing) and bcc tools (libbpf/bcc-Collection). Many eBPF operations require elevated privileges (e.g. CAP_BPF, CAP_PERFMON, CAP_NET_ADMIN). In Kubernetes environments DaemonSets with an appropriate securityContext are the usual approach:

apiVersion: v1
kind: Pod
metadata:
  name: ebpf-agent
spec:
  containers:
  - name: agent
    image: your/ebpf-agent:latest
    securityContext:
      capabilities:
        add: ["CAP_BPF","CAP_PERFMON","CAP_NET_ADMIN"]
  hostNetwork: true
  hostPID: true

eBPF for network monitoring: practical operational tips

This section summarizes concrete operational measures, checks and automation recommendations so that a rollout remains controllable.

CI/CD build and artifact management

Build and test eBPF programs in CI, not directly on production hosts. Use clang/llvm, libbpf and CO-RE options, and version the .o artifacts. Sign artifacts within your pipeline or verify hashes during deployment.

# Example: compile eBPF program (CO-RE) with clang
clang -O2 -target bpf -c trace_program.c -o trace_program.o
# Optional: generate hash
sha256sum trace_program.o > trace_program.o.sha256

Store artifacts in an internal artifact repository (e.g., Artifactory, Nexus) and use CI pipelines for signature checks before deployment.

Normalize events: Example JSON schema

Standardize fields so ingest workers and SIEMs process alerts consistently. A lightweight, efficient schema helps with enrichment and search.

{
  "timestamp": "2026-07-01T12:34:56.789Z",
  "host": "host01.example.local",
  "event_type": "connect_attempt",
  "pid": 1234,
  "uid": 1000,
  "process_path": "/usr/bin/zammad",
  "src_ip": "10.0.0.5",
  "src_port": 55872,
  "dst_ip": "198.51.100.10",
  "dst_port": 443,
  "raw_meta": { "map_id": 7 }
}

Serialize map contents asynchronously in the agent and send them via a message broker (e.g., Kafka) to enrichment jobs, instead of pushing every perf event synchronously.

Sampling, limits and map sizing

Avoid uncontrolled data throughput with sampling strategies and hard map sizes. Example: a counter in the map that forwards only every 100th event; or probabilistic sampling directly in the eBPF program. Define and test limits in a staging environment with production load profiles.

Monitoring and performance metrics

Measure CPU load, p99/latency and drop rates before and after activation. Create dashboards for eBPF agent health (program-loaded, map-usage, events/s) and alerts for unusual values.

# Basic checks during tests
# System CPU and load
top -b -n1 | head -n 12
# Processes with high CPU (kernel-mode visible)
ps -eo pid,cmd,%cpu | sort -k3 -nr | head -n 20
# eBPF-specific metrics (bpftool)
sudo bpftool prog show
sudo bpftool map show

Operational Runbook: Incident with eBPF alert

A structured approach reduces errors in analysis. Example steps for initial response:

1. Validate the alert: check timestamp, host ID, process path and whether canary hosts are affected.
2. Enrich context: correlate asset owner, job schedule and known maintenance windows.
3. Short-term containment: if critical, unload the eBPF program or stop the agent on affected hosts.
4. Preserve raw data: export map dumps and perf buffers for forensics.
5. Deep analysis: perform packet capture and process tracing only on dedicated analysis hosts.
6. Lessons learned: rule adjustments, whitelist, and if applicable permanent signature updates.

# Trigger packet capture briefly (only on affected host)
sudo tcpdump -i any host 198.51.100.10 and port 443 -w /tmp/incident.pcap
# Map dump (example with bpftool, adjust map ID)
sudo bpftool map dump id 7 format hex
# Stop agent
sudo systemctl stop ebpf-agent.service

Integration with Zammad: Practical notes

For Zammad operators it is important to deliver eBPF alerts with context: high outbound traffic from a scheduled maintenance job must not create unnecessary tickets. Use the following checklist:

• Correlate eBPF events with Zammad application logs and known job schedules (e.g. cron jobs).
• Create SIEM enrichment rules that recognize host tags or service roles (e.g. „zammad‑worker“).
• Define dedicated alert priorities: test/junk vs. security incidents.
• Automated ticketing: create a ticket in Zammad only for verified IOC matches; for suspected cases create a review task for Security/Sysops.

Example: a SIEM rule that correlates an eBPF event with a Zammad log showing HTTP status 500 can indicate possible exploits or faulty automation.

Typical troubleshooting sequence

When issues occur, work logically from surface to depth:

1. Check availability: is the agent running, are programs loaded (bpftool prog show)?
2. Check logs: dmesg for verifier errors, agent logs for serialization/transport errors.
3. Check permissions: capabilities, seccomp, Pod‑SecurityContext.
4. Check performance: event rate, CPU usage, map saturation.

Checks for verifier errors and syslog diagnostics

The kernel verifier rejects eBPF programs when security rules are violated or unsafe operations occur. Verifier messages are usually in dmesg. Search for terms like „BPF verifier“ or „bpf: program“. bpftool also helps enumerate programs and maps that are loaded or have failed.

# Verifier-Fehler schnell finden
sudo dmesg | grep -i 'bpf' -n | tail -n 50
# bpftool hilft beim Erkennen geladener Objekte
sudo bpftool prog show
sudo bpftool map show

Causes for verifier rejection often include pointer aliasing, too-deep loop structures, or missing constant bounding information. With CO‑RE, missing relocations or incompatible structures can lead to rejections — building against the target kernel headerset helps here.

Map strategies: types, sizes and pinning

Choose map types according to access profile: hash maps for sporadic lookups, perf event buffers for event streaming, LRU maps for automatic limiting. Pinning (persistent storage) of maps in the BPF filesystem (/sys/fs/bpf) simplifies debugging and map recovery.

# Prüfen, ob BPFFS gemountet ist
mount | grep bpf || echo "/sys/fs/bpf not mounted"
# Beispiel: bpftool zum Pinnen
sudo mkdir -p /sys/fs/bpf/ebpf-demo
sudo bpftool map pin id 12 /sys/fs/bpf/ebpf-demo/map-conn
sudo bpftool map show pinned /sys/fs/bpf/ebpf-demo

When eBPF is not the right choice

eBPF does not always replace a classic NIDS or full deep packet inspection (DPI). Opt against eBPF when you:

• require full packet reconstruction for Layer‑7 analysis (e.g. complete HTTP payload scanning),
• have outdated kernel versions that do not provide necessary features,
• require deep packet manipulations that go beyond simple drop/redirect actions.

In these cases a combined architecture is recommended: taps / SPAN ports for full packet capture plus eBPF-based host telemetry for context-rich events.

Security and governance considerations, detailed

eBPF programs run in kernel context and may require high trust. Restrict the privilege to load eBPF programs via RBAC and change approval. Separate build and deploy pipelines, sign artifacts and centralize audit logs (who loaded what). Anonymize user-related data before exfiltration to central systems, and define retention policies for telemetry.

Checklist for a secure rollout

• Staging test cluster with identical kernel and workload profile
• CI artifacting: .o files signed and versioned
• Canary: 1–5% of hosts first, with alerting and performance monitors
• SLA KPIs: CPU budget, event drop rate, map saturation thresholds
• Rollback mechanism: automatic unload or systemd stop on threshold breach
• Audit: who is allowed to load, and automatic snapshot of map dumps on deploy

Conclusion

eBPF for network monitoring provides a precise, kernel-level view of process and network activity that is particularly useful in modern, containerized infrastructures. The added value comes from context-enriching data and low latency in capturing relevant signals. Critical for stable operations are solid testing pipelines, CO-RE-compatible builds, map-sizing strategies, canary rollouts and clear governance rules. For Zammad operators and other operators of process-near software solutions: contextualize alerts with application logs and maintenance schedules before initiating automatic ticketing. With disciplined procedures and measurable KPIs, eBPF can be safely integrated into existing SIEM and incident management landscapes without jeopardizing stability and compliance.

Further reading and resources: The documentation for bpftool, bpftrace, XDP and your distribution is the best starting point. Test in small steps, measure intensively and automate rollbacks instead of risky blanket rollouts.

eBPF for network monitoring: resilience, updates and tenant isolation

In addition to detection and aggregation, you should make architectural decisions that guarantee stability during kernel updates, load spikes and multi-tenant scenarios. Three areas are particularly relevant in practice: export resilience, ABI drift due to kernel upgrades, and secure isolation of load paths.

Export resilience and backpressure

Do not rely on direct, synchronous delivery of every event. Implement a local spool (append-only), bounded in-memory queues and a dead-letter procedure for faulty payloads. This prevents an overloaded broker from destabilizing entire hosts. Also define clear producer timeouts and retry policies.

Kernel updates, BTF and ABI drift

CO-RE reduces rebuild effort, however ABI drift (changed kernel structures or missing BTF data) can lead to runtime errors. Before a kernel rollout, automatically check whether BTF is present and whether the eBPF artifacts were built against the target kernel headerset. Example check:

# Prüfen: BPFFS und BTF
mount | grep -q /sys/fs/bpf || echo "/sys/fs/bpf nicht gemountet"
[ -e /sys/kernel/btf/vmLinux ] && echo "BTF vorhanden" || echo "BTF fehlt"

Tenant isolation and minimal privileges

Grant only the absolutely necessary Capabilities (CAP_BPF, CAP_PERFMON) and use user namespaces, seccomp profiles and PodSecurityPolicies to reduce multi-tenant risks. Separate build and deploy permissions: only a signed CI artifact store may publish.

Short operational checks before deploy: BTF presence, spool disk free space, broker lag and an automatic fallback path (systemd unit to unload on threshold breach). These measures make eBPF baselines robust against real operational scenarios and simplify integration into existing incident processes and compliance requirements.

Host-based IDS and the Kernel Verifier are also important for this topic. This article places these aspects into context in a clear way and shows what matters in daily operations.