Protect VMs, containers, Kubernetes, and serverless workloads — without agents to deploy, snapshots that miss the moment, or noise that buries the real threats.
Agents are heavy. Snapshots are blind. You need both jobs done.
Heavy agents slow workloads and never reach 100% coverage.
Snapshot scanners miss anything ephemeral or in-flight.
CVE lists ignore whether the vulnerable code ever loads.
Runtime threats land before the next scan runs.
What it is
Protection for every workload, verified by runtime.
Continuous coverage for VMs, containers, Kubernetes, and serverless — with vulnerability, drift, and threat detection grounded in what the workload is actually doing.
AI agents increasingly operate as automation systems with access to APIs, cloud services, internal applications, and sensitive data. If manipulated or compromised, attackers may indirectly access infrastructure and critical systems through those agents — creating new pathways into cloud environments.
02.
Visibility Lost at the Prompt
Most AI security tools focus on prompt injection detection, model safety, and LLM guardrails. While these approaches analyze text interactions with models, they rarely reveal what actually happens when AI systems execute actions across production infrastructure.
03.
Runtime Blind Spots in the Cloud
To truly secure AI workloads, organizations must understand how AI interacts with cloud infrastructure. Without runtime visibility, security teams cannot see how AI-driven activity moves across services, APIs, and data stores or understand the potential impact on critical systems.
Step 1
Deploy without agents
Snapshot-based scanning gives you full workload coverage in minutes — no rollouts, no kernel modules, no production friction.
Step 2
Observe at runtime
Lightweight runtime sensing captures process, network, and file behavior on every workload — including ephemeral and serverless ones.
Step 3
Correlate and act
Findings are ranked by what's loaded, reachable, and active. Real threats trigger response; theoretical ones get suppressed.
Context
Protection that knows which workloads are real targets.
A workload CVE list with thousands of entries is a backlog, not a defense plan. RoonCyber enriches every finding with runtime context — so responders defend the workloads that actually carry risk.
RUNTIME-VALIDATED FINDINGS
Every workload risk, scored by what's running.
CVEs filtered by whether the vulnerable package is loaded
Reachability proven by live network paths
Behavioral anomalies detected against learned baselines
Drift flagged the moment a workload diverges from its image
AI & CONTAINERIZED WORKLOADS
Built for the workloads your platform team actually ships.
Inference containers, GPU workloads, and model-serving pods
Sidecars, init containers, and ephemeral build jobs
Kubernetes posture down to pod, namespace, and node
Serverless function behavior and supply-chain integrity
“A CVE in a library that never loads and a CVE in a library serving production traffic are not the same finding. CWPP should know the difference.”
What changes
Faster response. Quieter queues. Workloads you can actually defend.
15x
Faster MTTR
Runtime evidence cuts triage time — investigators see the live workload state, not a static CVE list.
90%
Fewer false positives
CVEs and misconfigs that aren't loaded, reachable, or active are suppressed by default.
50%
Lower TCO
Agentless deployment eliminates the rollout cost and ongoing maintenance tax of traditional CWPP agents.
Built for real workload ops
Protect VMs, containers, Kubernetes, and serverless
Prioritize CVEs by runtime exposure, not CVSS
Secure AI inference and GPU workloads
Detect crypto-miners, reverse shells, and privilege escalation
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