Q: Sanjay, how exactly is unsupervised machine learning and AI helping make security systems smarter and more effective?
Today's cyber attackers are faster and more unpredictable than ever. Machine-speed ransomware, insider threat, and novel, silent attacks that lurk in networks pose new challenges for defenders as they try to protect their data, operations and corporate reputation. In addition, digital environments are becoming increasingly complex with distributed infrastructures and non-traditional IT, such as printers and smart coffee machines, exposing organizations to unforeseen risks.
Given this new normal, organizations can no longer handle the threat on their own – AI technology will be essential in fighting back against the new era of threat. Darktrace's technology uses machine learning and AI algorithms that autonomously learn the 'pattern of life' for every user and device to build a sense of what constitutes 'self' for the network and what represents 'other' or anomalous. Modelled on the principles of the human immune system, this technology can not only detect the earliest signs of emerging threats and fend off attacks in real time, but it can also understand if a foreign presence is already in operation on your network.
Traditional security tools are inherently retrospective and can only offer a basic level of protection. Based on rules and signatures of past attacks, legacy systems are designed to define what 'bad' looks like and prevent it from entering the network. However, new, previously unclassified threats are able to bypass these controls and slip into the network unnoticed. The battle at the border is over and organizations need to identify the threats within if they are to get smart about their security.
Unsupervised machine learning is automating cyber-threat detection and response on an unprecedented scale. Our machine learning algorithms require no human training. It deploys in less than an hour and immediately starts learning. The technology grows with the network, constantly updating its understanding of 'self' for the organization and learning the most effective actions to take in response to emerging threats.
Q: Max, what has your experience in pen testing and red teaming taught you about threat hunting? What are some of the emerging best practices and trends around threat hunting?
My background in offensive security has formed the foundation for my threat uunting skills with Darktrace. My experience has taught me that attackers will always find smart new ways to bypass security controls - chasing after yesterday's attacks in an attempt to stop those of tomorrow is futile. This was an important realization, as it made me approach my hunts objectively and dismiss prior assumptions about historical attacks. Instead of hunting for 'known-bad', I shifted my focus to unusual activity in general. Knowing how a hacker thinks is an advantage when investigating potential breaches, i.e. why is this device beaconing to an unusual domain on the Internet? What would an attacker gain from this? Might this be a covert Command and Control channel?
A key success factor for every hunt is the ability to quickly and flexibly pivot around and drill into data. An unusual file download was observed on a laptop - what other rare websites did the user visit around the same time? Gaining situational awareness by pivoting around data is critical in order to judge whether behavior is merely interesting, or actually malicious.
Filtering through line after line of log data is time-consuming and often unreliable in the hunt for genuine threats. Instead, comprehensive, real-time visualizations of the network offer huge benefits for security officers. For example, graphs and color-coding can help a hunter rapidly visualize unusual behavior otherwise hidden among the day-to-day network noise.
The most successful hunts are aided by AI technology which autonomously spots abnormal behavior. With the machines doing the heavy lifting and prioritizing the most suspicious activities, the hunters can spend their time more strategically and efficiently than ever before.
Q: Sanjay, you have previously talked about 'trust attacks' as an emergent threat. What exactly are, trust attacks? What challenges do such attacks present from a detection and mitigation standpoint?
In today's world, cyber-threats are no longer restricted to stealing monetizable data and defacing websites. Cyber-crime has evolved to now also include savvy attackers subtly changing data to erode our confidence in organizations. Imagine an attacker moving one decimal point across millions of bank statements, or changing patients' blood types in a laboratory results database. Once our trust in the integrity of data is gone, our trust in these institutions is completely undermined.
The alteration of sensitive information, such as financial or government records, may well have harmful reputational consequences, but these turn potentially life threatening when medical records are implicated. Such attacks can also cause host organizations to doubt the veracity of their own data.
Unlike noisy attacks such as ransomware, trust attacks are often silent and can lurk in networks undetected for months, or sometimes years. For example, polymorphic malware is able to rapidly change its code at the network border, enabling it to penetrate the network under a cloak of invisibility. Once inside, 'low and slow' attacks can make calculated lateral movements under the radar, in pursuit of the 'crown jewels'. Without the ability to detect such threats in their nascent stages, the window for mitigation is extremely small and security teams often do not realize they have been compromised until it is too late.
Q: Max, if there is one thing you would like people at Black Hat Asia 2018 to know about Darktrace, what would it be and why?
The cyber security landscape is intensifying as networks explode in digital complexity and span not just the physical, on-premise network, but also cloud and virtualized environments, non-traditional IT (IoT), and the supply chain. Security teams cannot keep up with a threat landscape that is evolving 24/7, and which includes automated attacks, that can cause an organization to virtually grind to a halt within minutes.
The future of cyber defense belongs to autonomous response technology that can fight back against threats before humans have even had a chance to notice. Darktrace is at the forefront of this revolution – its autonomous response technology, Darktrace Antigena, is already used by organizations around the globe to defend their networks against advanced and fast-moving threats. The technology works by creating 'digital antibodies'; it intelligently takes defensive action when a threatening anomaly arises without disruption to organizations' day-to-day business activity.
Darktrace Antigena's innate understanding of what represents 'self' for the organization, enables it to generate very precise and targeted actions in response to emerging threats. For example, it can stop anomalous connections to foreign IPs, prevent devices from communicating with unauthorized users, slow down unusual data transfers, and isolate infected devices and suspicious users. At its core, Antigena's AI technology creates a dynamic boundary for users and devices. When they deviate from normal activity, Antigena is automatically triggered to re-enforce the organization's 'pattern of life'.