Hostile nation states and hacker groups are estimated to have stolen information on over 126.3M Americans in the recent OPM, Anthem, Premera, UCLA and Excellus breaches. This equates to almost 40% of the US population. In all cases security measures including Anti-Virus Software, NextGen Firewalls, Intrusion Prevention Systems (IPS), and Secure Gateways were unable to detect and prevent the theft.
The “bad guys” have gotten much smarter. They are well funded and have considerable technical resources. Using encrypted payloads and well documented weaknesses in existing products, hackers easily evade outdated detection techniques including Signatures, Sandboxes and DNS reputation services. State-of-the-art protection requires a new approach that actively takes the battle to the hacker’s front door.
Today's cyber threats easily evade existing detection technologies but they are not able to evade a researcher’s trained mind. Human researchers routinely find malware that technologies miss. Humans use their intuition and senses along with analytical reasoning to classify the good from the bad, and the malicious from the non-malicious. At SlashNext we have codified this process and automated the thinking of some of the world’s best researchers to build a better system.
The SlashNext Active Cyber Defense System uses an advanced form of Artificial Intelligence specifically, a Dynamic Knowledge Based System (KBS) to emulate human cognitive thinking. Clues gathered throughout an attack sequence and active threat intelligence feed the system’s machine learning engine, allowing it to rapidly identify threats with pin point accuracy – much like a human researcher.
Traditional detection systems only protect against some types of object based exploits. Engaged at all stages of the attack lifecycle the SlashNext Active Cyber Defense System protects against credential phishing attacks, both object and on-object based exploits, malicious EXEs, post-infection callbacks and data exfiltration.