The Execution Security Primitive

A Kubernetes sidecar that learns your workload's normal behavior and detects when something changes.
No rules to write.
No policies to configure.

The Problem

Rules can't cover everything.

Rule-based runtime tools require you to anticipate every attack. If you don't write the rule, you miss the threat.

Runtime threats evolve.

Attackers adapt faster than static policies. You need monitoring that adapts to your workload automatically.

Alert fatigue kills response.

Generic detection generates false positives. Real threats get buried. You need detection tuned to your specific workload behavior.

A Different Approach

PandoCore takes a fundamentally different approach to runtime security. Instead of requiring you to write detection rules for every possible threat, PandoCore learns what normal looks like for each of your workloads and flags when behavior deviates. Deploy it with one label, and it starts working immediately.

Zero configuration required
No application code changes
Kubernetes-native sidecar deployment
Works on existing infrastructure
Validated: 693 pod-hours, 0 false positives

Who Needs This

For Platform Teams

"One label. Every service monitored."

Add runtime anomaly detection across all your services with a single Kubernetes label. No per-service configuration needed. PandoCore learns each workload's behavior independently and works out of the box.

For Security Teams

"Catch what rules-based tools miss."

PandoCore detects runtime anomalies that policy-based tools can't catch without custom rules: unexpected process changes, behavioral shifts, and subtle deviations. Complements your existing Falco, OPA, or network policy stack.

For Compliance-Sensitive Workloads

"Continuous monitoring with a full audit trail."

Every detection generates structured evidence with forensic context. Monitor mode gives you visibility. Alert mode notifies your team. Enforce mode responds automatically. All with complete, auditable records.

See It In Action

Whether you're securing critical workloads or exploring runtime monitoring for your Kubernetes clusters, we want to hear from you.