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
Automatic discovery
Identifies services and APIs the instant they appear, change, or disappear. No tagging, no agents to chase.
Step 2
Runtime validation
Confirms what's real by what's executing — not what a config file claims. Misconfigs and orphans surface fast.
Step 3
Relationship mapping
Connects every service to its infrastructure, data stores, identities, and network paths. Live, not last quarter.
Context
Inventory with context, not just counts.
A list of services tells you nothing. RoonCyber enriches every entry with the signals that decide how — and whether — to respond.
RISK ENRICHMENT
Each service comes with the risk signal attached.
Reachability and exposure indicators
Associated vulnerabilities and misconfigurations
Business impact and financial risk
Active incidents and runtime activity
BLAST RADIUS
See how one compromise could spread.
Which services depend on each other
How a compromised service can reach others
Downstream systems and data at risk
The true scope of service-level exposure
“An unused service and a customer-facing production service are not equal. Service Inventory makes the difference visible.”
What changes
A single source of truth — and what it lets your team do.
15x
Faster MTTR
Real-time runtime context means investigators stop guessing and start acting.
90%
Fewer false positives
Validating real risk against live service behavior — not config assumptions.
50%
Lower TCO
Agentless deployment, zero manual tagging, no inventory upkeep tax.
Built for AI in production
Discover undocumented or forgotten APIs
Track services across multi-cloud and Kubernetes
Support audits with an always-current inventory
Accelerate investigations by knowing what's running
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