eBPF kernel telemetry, per-workload behavioral baselines, and MITRE ATT&CK-classified alerts — deployed to your EKS, GKE, or AKS cluster in a single afternoon, no dedicated security analyst required.
eBPF sensor adds less than 1.2% CPU overhead per node in production workloads
Runtime threat events are detected and classified within 50 milliseconds
From helm install to live threat visibility in under four hours
Workload behavioral baselines mature within one to two weeks of deployment
From kernel-level syscall collection to Wiz and CrowdStrike context enrichment, Kubesentry covers every stage of a Kubernetes runtime attack chain without sidecars, image changes, or weeks of rule tuning.
Kubesentry deploys a single eBPF DaemonSet probe per node that hooks into the kernel system-call interface using CO-RE probes compatible with Linux kernel 5.8+. Every exec, connect, open, and mount event from every container streams to the detection pipeline within 50 milliseconds. No container image modifications, no per-pod sidecar injection, no application restarts. Node overhead benchmarks under 1.2% CPU on c5.xlarge-equivalent instances.
Over a 7–14 day learning window, Kubesentry builds a behavioral fingerprint for each Deployment, DaemonSet, and StatefulSet in your cluster: which binaries it execs, which network destinations it reaches, which file paths it touches, and how it uses its ServiceAccount. Deviations from that profile trigger scored anomaly alerts. When you ship a new container image version, the profile automatically updates to reflect the new baseline without generating false positives for the intentional change.
Every Kubesentry alert arrives pre-tagged with the applicable MITRE ATT&CK for Containers tactic and technique — Execution, Persistence, Privilege Escalation, Credential Access, Lateral Movement, and more. The classification runs inline during detection, not as a post-processing step, so your on-call engineer sees the attack chain stage at the same moment the alert fires. No separate enrichment pipeline, no pivoting between tools to figure out what you’re looking at.
No professional services engagement. No multi-week proof-of-concept. No changes to your application images or CI pipeline. Four steps and you have runtime visibility across every namespace in your cluster.
Run helm install kubesentry kubesentry/kubesentry -n kubesentry-system --create-namespace to deploy the DaemonSet probe and the detection engine to your cluster. The chart automatically selects the right eBPF probe for your node kernel version — no manual kernel module configuration required.
Point alerts at your existing tools: Slack, PagerDuty, Datadog Log Management, Splunk HEC, or a custom webhook. You can filter by severity, namespace, or MITRE tactic before the baselining window completes, so high-severity detections route immediately even on day one.
Over the next 7–14 days, Kubesentry learns the normal syscall and network profile for every Deployment and DaemonSet in your cluster. Baseline coverage per namespace is visible in the dashboard. No manual rule writing required during this period — the engine handles it.
Once baselining completes, every behavioral deviation produces a structured alert with the MITRE tactic, the specific syscall sequence that triggered it, the affected pod and namespace, and the Wiz and CrowdStrike enrichment data for that workload. Your on-call engineer has everything needed for triage without opening a second console.
The average time a cryptomining deployment runs undetected in a misconfigured Kubernetes namespace when cloud billing anomalies are the primary detection signal — by which point lateral movement to adjacent secrets is well underway.
Mid-size SaaS teams report that the majority of Kubernetes runtime security events are first discovered during post-incident forensics, not during the attack itself — because no real-time behavioral detection layer was running.
Average time for a container-escape to reach cluster-admin privilege level in an unmonitored Kubernetes environment. CSPM tools and audit logs do not capture the syscall sequence that makes this escalation visible in real time.
