Shadow AI refers to any AI model, agent, pipeline, or tool operating in your environment without the knowledge, approval, or oversight of your security team. It is the AI equivalent of shadow IT but faster moving, harder to detect, and significantly more dangerous. Unlike a rogue SaaS tool, a shadow AI agent can actively query databases, call external APIs, access sensitive data, and take actions across your systems the moment it starts running.

Why do traditional tools miss Shadow AI?

Guardrails and gateways only monitor traffic that passes through them - a shadow AI agent that bypasses your approved gateway is completely invisible. Asset scanners and CSPM only find what is registered - an unauthorized agent running inside an approved container looks like normal activity. Log review finds shadow AI after the fact, if someone is looking for it. By the time a log review surfaces an unauthorized agent, it may have been running and accessing data for weeks. Runtime is the only approach that catches Shadow AI the moment it starts executing.

Real Runtime

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Analyzing an event that occurred at runtime is not the same as having visibility into runtime itself.

The hybrid problem

"Runtime" is getting stretched.

Security spent years moving past point-in-time scanning toward continuous protection. Hybrid tools quietly move it backward: they borrow the runtime label while listening intermittently, scanning, or analyzing activity generated somewhere else.

Using an LLM to "listen" to activity

Useful analysis, but interpreting activity doesn't make the underlying technology runtime. The question is whether it observes execution directly, or reads what another mechanism collected.

MISSES

Anything the collection layer never captured.

Sending events to AI for analysis

An event can happen at runtime without the tool analyzing it being runtime technology. Correlating telemetry is valuable, and it is still a step removed from what the workload is doing as it executes.

MISSES

The moment of execution, and the chance to stop it.

Inferring behavior after the fact

Reconstructing behavior from downstream signals can help, but it can't match continuous visibility into what actually happened inside the running workload.

MISSES

The ground truth. You get a best guess.

The AI execution path

Hybrid "runtime"

Real runtime

Prompt & model I/O

Inputs and outputs at the model boundary

Seen

Gateway & API logs

Traffic that passes through a gateway

After the fact

Hybrid visibility ends here

Agent runtime & tool calls

What the agent actually invoked

Seen

Process spawns

Child processes, shells, scripts

Blind

Syscalls, files & network

File ops, connections, privilege changes

Blind

Kernel

Where execution actually happens

Blind

Hybrid tools see the edges: prompts, gateways, logs. Below the line they are guessing, or blind.

Prompt & model I/O

Inputs and outputs at the model boundary

Observed live

Gateway & API logs

Traffic that passes through a gateway

Observed live

Agent runtime & tool calls

What the agent actually invoked

Observed live

Process spawns

Child processes, shells, scripts

Observed live

Syscalls, files & network

File ops, connections, privilege changes

Observed live

Kernel

Where execution actually happens

eBPF · Live

Real runtime observes every layer continuously from the kernel up. Ground truth, not inference.

The execution layer

Where breaches are won or lost.

Most AI security tools stop at the prompt. An agent that skips the gateway is invisible to them. These are the signals that only exist at the kernel, and that a hybrid never sees.

Process spawns

An agent launching a child process or shell it was never meant to run

System calls

The lowest-level record of what code actually asked the operating system to do.

File operations

Unexpected reads of credentials, configs, and sensitive data stores.

Network connections

Lateral movement, and data leaving authorized boundaries before anyone notices.

API & tool calls, end to end

Every container, database, and cloud API an agent touches, including the ones that never pass through a gateway.

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Real vs. hybrid

Same label. Different technology.

THe Question

Real Runtime

Hybrid “Runtime”

How does it observe execution?

eBPF at the kernel level, directly observing processes, API calls, and syscalls as software executes.

Reads logs, gateway traffic, or model inputs and outputs collected by another mechanism.

Is visibility continuous?

Always on, with minimal performance impact.

Intermittent: periodic checks, scans, or listening windows.

Where does the telemetry come from?

The running workload itself.

Activity generated elsewhere, then forwarded to an LLM or AI engine for analysis.

What does it inventory?

What is actually running right now: agents, services, APIs, and processes, including shadow AI.

What was configured, documented, registered, or previously scanned.

What evidence do you get?

A record of actual execution: ground truth, not inference.

Behavior reconstructed or inferred after the fact.

What actions can be taken?

Block the process, contain the workload, and remediate access, from the same platform.

An alert, a severity score, and a dashboard.

How does it observe execution?

Real Runtime

eBPF at the kernel level, directly observing processes, API calls, and syscalls as software executes.

Hybrid “Runtime”

Reads logs, gateway traffic, or model inputs and outputs collected by another mechanism.

Is visibility continuous?

Real Runtime

Always on, with minimal performance impact.

Hybrid “Runtime”

Intermittent: periodic checks, scans, or listening windows.

Where does the telemetry come from?

Real Runtime

The running workload itself.

Hybrid “Runtime”

Activity generated elsewhere, then forwarded to an LLM or AI engine for analysis.

What does it inventory?

Real Runtime

What is actually running right now: agents, services, APIs, and processes, including shadow AI.

Hybrid “Runtime”

What was configured, documented, registered, or previously scanned.

What evidence do you get?

Real Runtime

A record of actual execution: ground truth, not inference.

Hybrid “Runtime”

Behavior reconstructed or inferred after the fact.

What actions can be taken?

Real Runtime

Block the process, contain the workload, and remediate access, from the same platform.

Hybrid “Runtime”

An alert, a severity score, and a dashboard.

How RoonCyber works

Built around continuous runtime observability.

Using eBPF, RoonCyber monitors processes, API calls, syscalls, and other kernel-level activity in real time with minimal performance impact. That visibility is the evidence to understand what happened, and the control to act when a threat is confirmed.

API calls

syscalls

real time

processes

API calls

syscalls

real time

processes

API calls

syscalls

real time

processes

API calls

syscalls

real time

processes

API calls

syscalls

real time

processes

API calls

syscalls

real time

processes

01 · Discover

A real-time inventory

Every process, API, agent, and service that is actually running, not just what was configured or previously scanned. Shadow AI included.

02 · Visualize

The full execution path

Trace an agent from prompt to every tool call, container, database query, and cloud API it touches, process by process.

03 · Protect

Block. Contain. Remediate.

Kill the process, quarantine the workload, and revoke access at the moment of execution, with evidence behind every action.

What to ask any vendor

Four questions that expose a hybrid.

Take these into your next evaluation. Real runtime answers every one without hedging.

How does it observe execution?

Listen for: kernel-level instrumentation such as eBPF. Not log ingestion or model I/O.

Is that visibility continuous?

Listen for: always on. Not polling, periodic scans, or sampling.

Where does the telemetry come from?

Listen for: the executing workload itself. Not events generated elsewhere and forwarded to AI.

What actions can be taken from it?

Listen for: kill, quarantine, and revoke, from the same platform. Not just an alert.

Protect your AI security with real runtime.

Analyzing an event that occurred at runtime is not the same as having visibility into runtime itself.

"Runtime" is getting stretched.

The AI execution path

Where breaches are won or lost.

Same label. Different technology.

Built around continuous runtime observability.

A real-time inventory

The full execution path

Block. Contain. Remediate.

Four questions that expose a hybrid.

Ask how their runtime actually works.