Ensure your cloud environments remain secure in the AI era by detecting and validating AI-driven activity with runtime visibility, attack path context, and real-time detection across modern cloud environments.

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AI Cloud Security That Delivers Results

15x faster MTTR

with real-time runtime context

Up to 90%

reduction in false positives by validating real risk

45–50%

lower TCO through agentless deployment

One unified platform

with real-time runtime context

AI Security Gaps

As organizations rapidly deploy AI agents and automation systems, a new category of security risk is emerging. AI systems increasingly interact directly with cloud infrastructure, APIs, and sensitive data, often with privileged access.

Traditional security tools were not designed to monitor or validate this behavior.

01.

AI Privileged
Access

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.

AI Privileged Access

Visibility Lost at the Prompt

Runtime Blind Spots in the Cloud

Most AI Security vs. RoonCyber

Most AI security platforms analyze the prompt layer.
But the real risk occurs when AI interacts with real infrastructure.

Focus areas typically
include

Prompt injection detection
Model safety
LLM guardrails
Suspicious text analysis

What most AI Security tools see

RoonCyber Sees the Full Execution Path

By observing runtime activity across cloud environments, RoonCyber provides visibility into:

AI-driven process execution
Tool invocation and API activity
Network connections and service interactions
Data access and file activity
Infrastructure systems impacted by AI activity

Instead of analyzing hypothetical threats, security teams can detect the real consequences of AI-driven behavior.

Built for the Risks Security Teams Care About

AI agents are no longer simple assistants. They now operate as autonomous systems capable of invoking tools, calling APIs, accessing services, and interacting with sensitive data across cloud environments.

If attackers manipulate those systems, AI can become an indirect pathway into critical infrastructure.

RoonCyber helps organizations detect when AI-driven behavior deviates from expected patterns, including:

Unusual API activity

Unexpected tool invocation

Abnormal network destinations

Access to sensitive data sources

Large or abnormal data transfers

Three Pillars of AI Workload Protection

Secure cloud environments from AI-driven threats with runtime detection, attack path intelligence, and business-level risk context.

Runtime Detection
and Validation

See and validate what AI workloads
actually execute.

RoonCyber observes runtime activity across processes, APIs, network connections, and data access to reveal how AI-driven activity interacts with production cloud environments. This provides the visibility needed to detect abnormal behavior and validate what AI systems are actually doing in real time.

Attack Path
Context

Understand where AI-driven activity
can move.

By correlating runtime telemetry with cloud infrastructure inventory, RoonCyber reveals how AI-driven activity flows across services, APIs, and data stores. Security teams gain visibility into reachable assets, exploit paths, and the potential blast radius of compromised AI activity.

Business
Impact

Translate runtime threats into dollars and confidently score risk.

RoonCyber connects runtime activity with infrastructure, data exposure, and asset context to quantify potential business impact. This allows organizations to understand how threats affect critical systems and prioritize response based on real operational and financial risk.

Secure What AI Actually Does

The greatest risk in AI security is not the model itself.
The real risk is AI interacting with production systems.

AI agents now have access to APIs, automation tools, internal services, and sensitive data across cloud environments. If those systems are manipulated, attackers may gain indirect access to infrastructure and critical business systems.

RoonCyber helps organizations detect, validate, and investigate AI-driven activity by securing the runtime layer where AI actions become real.

Joseph Feiman

Board Advisor

Sydney Gangi

Director, Product Marketing

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Runtime security should be exactly how it sounds - always active and everywhere within your organization.