Deep Instinct introduces new analytical capabilities for cyberattack insights and visibility

With the rise in malware and new attack vectors, Deep Instinct has introduced new threat analysis services to provide visibility and analysis of new and emerging threats.

Deep Instinct’s approach to security predicts and prevents the threats before any damage can occur. Its new threat analysis services leverage learning capabilities to provide visibility and understanding of threats as they are discovered.

This offering features Deep Classification to provide automated, real-time malware classification without human involvement, and an Advanced Threat Analysis to provide a level of detail around threat incidents.

In addition, the Deep Threat Analysis Report, delivers in-depth findings, insights, statistics, highlights and assessment on the threats found in the organization network and adds malware analysis for malicious campaign found.

“Cybersecurity threats are evolving so quickly that most IT departments and SOC teams can’t keep up – so they become concerned for the state of their organizational security,” said Guy Caspi, CEO, Deep Instinct.

“Our predictive threat prevention approach to security equips organizations with peace of mind because they have the best possible protection against emerging attack vectors like fileless malware and coin miners, preventing them in real-time and before any damage can occur. With the addition of sophisticated threat analysis solutions, we can now also give those organizations a better understanding of these threats, as part of our offering.”

Not only can deep learning be used to prevent malicious files from running, it can also provide threat analysis by classifying in real-time what type of malware is targeting the organization.

Deep Instinct’s Deep Classification capability based on Deep Neural Network (DNN) ensures that any malware, known and unknown, is classified.

Once malware is detected, it is scanned again by the classification brain providing results for the file malware family, without any human involvement. The Deep Neural Network brain is able to classify between 7 malware family types: Ransomware, Backdoor, Dropper, Spyware, Virus, Worm and Potential Unwanted Applications (PUAs).

“The true value of quickly and efficiently classifying zero-day malware files comes from the immediate knowledge and understanding of the threat, and the ability to then respond quickly and accurately, saving time and money,” said Guy.

The addition of the Advanced Threat Analysis provides a tool set that performs analysis on top of threats found in the organization, as part of the D-Appliance management console. It includes static analysis, sandboxing analysis, screenshots and network dump of the potential threats.

The introduction of Deep Instincts’ Deep Threat Analysis Report, also part of its new threat analysis services, gives organizations a line of defense by helping them better understand more about thwarted attacks on their environment.

The executive report enables visibility of prevented threats, enabling a clearer view of the threat environment and saving time and money analysing future dangers.

Deep Instinct has disrupted the cybersecurity market with new levels of accuracy that enable it to predict and prevent new threats others cannot find.

It uses a proprietary artificial neural network inspired by the brain’s natural ability to learn and is to be applied to cybersecurity.

It scans 100% of the raw data sets to protect against zero-day threats and Advanced Persistent Threat (APT) attacks, while ensuring lowest false positives and an overall safer organization.

“There is an increasing need to respond to cyberattacks in real-time with minimal human interaction using AI, and this is the value of deep learning. It brings a completely new approach to cybersecurity where the artificial neural network can learn to identify any type of cyber threat, then detect and prevent attacks in real-time with unmatched accuracy,” concluded Guy.