Detect what doesn't fit the norm
orovar learns the normal behavior of an environment — login patterns, data flows, typical application execution, common network paths. Deviations are scored on trained models, not on static thresholds.
Cybersecurity Suite
orovar
Autonomous security agent, powered by NeoI (neonotu Intelligence).
Doesn't hide. Hunts.
orovar is the autonomous security agent of the Cybersecurity Suite. Unlike classic detection tools, orovar doesn't just report — it acts. Detected activity can be automatically isolated or redirected to honeypots, while the security team is informed and retains control.
What it changes
01
Response in seconds
Automatic first response within the time windows where human reaction is too slow.
02
Deception, productive
Honeypot redirection becomes part of daily defense, not a research project.
03
Low maintenance overhead
NeoI scoring replaces the extensive playbook maintenance of classic SOAR platforms.
04
Complete audit trail
Every action and override is documented in audit-grade form — ideal for regulated industries.
HOW IT WORKS
The orovar approach
orovar unifies detection, isolation, and active deception in one agent — and places that agent under a clear policy and audit regime.
Isolate before damage spreads
When orovar detects a confirmed anomaly, the affected system can be cut off from critical zones within seconds. Isolation is reversible, fully logged, and overridable.
Redirect to honeypots, learn from the attacker
Detected attacker activity can be routed to a controlled honeypot environment. There, attacker behavior, tooling, and objectives are observed — information that flows back into the detection models.
Human in the loop, always
orovar acts within a policy defined by the organization. Action classes can be configured from suggestion to confirmation-required to fully automatic — by severity, zone, and risk authorization. Every action is documented traceably.
POLICY
Policy model
The policy engine defines what actions orovar may carry out on its own. An organization can tailor the policy to its maturity, risk appetite, and regulatory pressure.
| Action class | Description | Typical setting |
|---|---|---|
| Suggest | orovar recommends an action without executing it. | Low severity |
| Confirm | Action requires sign-off by a SOC analyst. | Medium severity |
| Auto-execute | Action is executed immediately and logged. | High severity, clear indicators |
| Manual override | Every action is overridable at any time. | Always active |
In comparison
Market positioning
orovar addresses a gap that classic EDR tools and SOAR platforms each only partially close.
| Aspect | EDR alone | SOAR platform | orovar |
|---|---|---|---|
| Detection | Endpoint-centric | Source-agnostic | Behavioral, multi-source |
| Response | Limited | Script-based, high maintenance | Policy-based, NeoI-scored |
| Deception/Honeypot | Not in scope | Only via integration | Native |
| Maintenance effort | Medium | High | Low |
| Audit suitability | Variable | Variable | Design principle |
In practice
Three examples
How organizations across the European mid-market and the public sector use the module.
Lateral movement detected outside business hours
On a Saturday at 03:14, orovar observes login behavior on a server that deviates from the learned normal model. Correlated signals from Strider point to a preceding unusual identity sign-in. orovar isolates the affected server, redirects further connection attempts to a honeypot environment, and informs the on-call engineer through the defined escalation path. The situation is contained before the security team could have responded manually.
Honeypot observation of targeted attacks
A mid-sized mechanical engineering firm is repeatedly targeted by clearly intentional attacks on its R&D environment. orovar consistently routes detected attacker activity into honeypot systems modeled after the real R&D zone. Over several weeks, a detailed picture of the tooling and objectives is built up without touching production systems.
Reducing mean time to contain
A public administration under high regulatory pressure deploys orovar across its critical zones. Mean time to contain — the time between detection and complete containment — drops from a previous 4 hours to under 90 seconds for the defined action classes. Internal and supervisory reporting benefits measurably.
NEXT STEP
From detection to action
orovar shifts the boundary between detection and response to where, in today's threat landscape, it actually needs to sit: into the seconds, with clearly documented and overridable actions. Human and machine do not work against each other but on a jointly defined policy.
orovar is the part of the Cybersecurity Suite that closes the detect-and-response gap. For organizations under elevated response pressure — regulatory, operational, or insurance-related — it is the logical next step.
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