Detect & Respond To Threats Autonomously

Gain complete visibility over your endpoints. Detect threats in seconds & remediate malware with one click. Secure business continuity with ReaQta-Hive.


360° Visibility

ReaQta’s proprietary ​NanoOS™ provides deep visibility into the processes and applications running on endpoints. It sits at the hypervisor layer and protects the endpoint from outside the operating system, making it invisible & tamper-free to malware and attackers.


Respond in Real-Time

An easy to understand graphical storyline for every threat is automatically created as an attack unfolds, including mapping to MITRE ATT&CK giving analysts full visibility of the threat which can be automatically mitigated or manually with a click.


Simplify & Automate

Simple, yet powerful. ReaQta-Hive is developed for analysts, by analysts. Our user-friendly interface brings novice and expert staff up to speed quickly. Let our dual-AI engines do the heavy lifting, returning precious time back to you.

ReaQta-Hive offers full visibility over the infrastructure, allowing real-time queries to the endpoints, extended searches for both IOCs and behavioral indicators, together with advanced data-mining for discovery of dormant threats.

A unique NanoOS offers an unprecedented level of detail to the analysts and, at the same time, a barrier extremely difficult to overcome for the attackers. Two different sets of engines apply state-of-the-art machine learning to applications’ behaviors, automatically alerting about active or emerging threats without need for prior knowledge of the attacks. This signature-less approach, combined with an A.I. driven behavioral analysis, ensures that threats are detected independently of their delivery techniques and payload types.

Powered by A.I.
Rapid Incident Response
Threat Hunting
End-To-End Security
Artificial Intelligence detection engines are used both on the endpoints and at the infrastructural level to identify new patterns of attack, anomalous activities and lateral movements. The flexibility provided by continuous learning A.I. allows for the detection of new techniques and previously unknown threats, that would otherwise escape detection from legacy solutions. A comprehensive early-warning system automatically identifies potential emerging threats, allowing the security teams to perform a full security assessment ahead of time.

Detection & Protection

ReaQta-Hive A.I. engines work by analyzing the dynamic behavior, thus they’re agnostic to the delivery techniques and are equally effective on malware (ransomware, RAT, trojans etc) and non-malware (in-memory, file-less) attacks.

Attackers can leverage different types of technologies to breach the defenses of an organization, not all of them are malware based. So called “living off the land” attacks abuse components already present on the targeted operating system to avoid alerting legacy security solutions. These attacks, classified as non-malware, are highly effective and hard to detect due to the fact that most of the activity happens in memory, leaving a low (if any) forensic footprint.

Whether it’s a ransomware or a sophisticated in-memory attack, ReaQta-Hive helps the organization track the threat and respond with the appropriate measures in real-time. ReaQta-Hive can be configured in Detection, Protection and Hybrid mode, automating the way the platform responds to different types of threats.

Hunting & Data-Mining

ReaQta-Hive provides complete support to search for threat data inside the infrastructure in real-time and to perform more sophisticated data-mining tasks aimed at uncovering dormant threats.

In-memory and file-less threats are hard to track by their own very nature and they become even harder to follow when the attackers are using different variants as they move inside a large infrastructure. By leveraging on data-mining, ReaQta-Hive enables the security teams to automatically hunt for threats that share similarities – at the behavioral and functional level – with other incidents, automatizing the hunting job and bringing back results in just seconds.

The highly granular search support allows the analysts to look, in the present and in the past, for traces of attacks. IOCs (hashes, ip addresses, names) and behaviors can easily be searched to understand when and if a threat, or one of its components, came in contact with the infrastructure.

Lateral Movement Detection

ReaQta-Hive detects lateral movements natively, the analysts can instantly understand which devices are being abused during an ongoing attack, enabling a lightning fast response in case of successful breach.

Attackers got access to the infrastructure and now they’re moving laterally, waiting to pivot in order to get access to more valuable resources. Identifying lateral movements disguised as legitimate user’s activities is hard and speed is of the essence, an active attacker can cause all sort of damages in a very short period of time. Once identified, the affected resources can be isolated immediately, or kept under monitoring to gather intelligence on the attacker, understand the modus operandi and identify their toolkit chain.

Simplicity & Automation

We want your team to be up and running in no time, without requiring additional personnel or highly skilled resources, by letting the bulk of the work to the algorithms and reducing human interaction to a minimum.

ReaQta-Hive has been designed with simplicity in mind, we know that acquiring visibility over the whole infrastructure looks like a daunting task, as much as we know how damaging it can be to ignore the endpoints. All the data is pre-processed and filtered to remove the noise and to make it easy to read, incidents are reconstructed and assessed so as to be understandable in a matter of seconds and in most cases without digging into the data. Every response can be automated and security teams alerted only when the engines identify suspicious activities.

Want to know more about ReaQta-Hive?

Contact us if you are a business and our team will get back to you to schedule a free demonstration. You’ll be able to see how ReaQta-Hive behaves in a live environment, how it reacts to threats and how to swiftly respond to incidents when they happen.

This project has been partly financed by the European Union’s Horizon 2020 research and innovation programme under grant agreement No 726818.