Aviad Hasnis, CTO of Cynet Security, leads the company’s cybersecurity technology strategy, including the development of its extended detection and response (XDR) platform, threat research, and managed detection and response (MDR) services. Prior to Cynet, he held an advanced cybersecurity role in the IDF and held an advanced degree in engineering and physics in the technology.
Cynet Security provides an all-in-one automated cybersecurity platform designed to simplify protection for small and medium-sized organizations. Its solution integrates endpoint, network, user, email and cloud security into built-in automation, XDR functionality and 24/7 MDR support.
Cybersecurity is an ever-evolving field. How do you balance keeping threats ahead while making solutions user-friendly and available for SMEs?
Lean SMB security teams must face the same threats faced by the Fortune 500 properties, with a small percentage of people, resources or budgets. As the number and complexity of cyberattacks soar, SMB security leaders are driving the need for simplification, automation and consolidation of security solutions to reduce complexity and improve protection.
At Cynet, my team deliberately built an all-in-one cybersecurity platform to incorporate complete security features on a single, simple, AI-enabled solution.
- Cynet maximizes user-friendly simplicity by unifying environment-wide visibility and protection on one intuitive dashboard.
- By automating critical security processes, Cynet can help lean teams maximize efficiency.
Cynet’s platform is described as natively automated – can you explain how AI and automation play a role in detecting and mitigating cyber threats?
My team designed Cynet’s all-in-one cybersecurity platform to automate processes so people spend less time managing day-to-day operations and more time building their business.
At Cynet, my team is also proud of a “buy instead of buying” approach. Starting from scratch and integrating locally, every feature, functionality and automation of the all-in-one cybersecurity platform is developed internally, so everything runs seamlessly. This eliminates the integration gap and overlap that can compromise automatic protection measures.
The MITER ATT&CK evaluation will rank Cynet the highest. AI-driven strategies contribute to this success?
I am very proud of the team’s contribution to Cynet’s record performance in the recent Miter Att & CK assessment. There is good reason that Miter Att&CK is the most trusted independent assessment among cybersecurity decision makers. Miter uses real-world cyberattack scenarios to measure the performance of competitive security platforms. The Cynet is the only supplier to receive 100% protection, and the 100% detection visibility reflects our commitment to establishing reliable products for Cynet Partners and customers around the world.
AI-based cybersecurity has been criticized for potential false positives and adversarial attacks. How does Cynet ensure accuracy and robustness in its threat detection?
Cybersecurity solutions that support AI support are most effective when integrated with expert supervision. While AI can quickly process and analyze large amounts of data, it is crucial to provide ongoing oversight by experienced cybersecurity professionals. My team at Cynet ensures that the decisions of AI systems are constantly validated to prevent situations where AI may miss nuanced threats or draw false conclusions. In cybersecurity, risks are rapidly evolving, and human expertise is crucial to interpreting results and making context-sensitive decisions.
To provide additional layer of protection for partners and customers, Cynet can support an all-in-one cybersecurity platform supported by 24/7 SOCs. Cynet’s SoC is equipped 24/7 by world-class analysts to ensure active monitoring of the end user environment and complement automatic scanning. This unique combination of automatic protection and hands-on expertise maximizes the mindset of Cynet partners and customers.
With the rise of Deepfake attacks, AI-generated malware and complex social engineering, which emerging cybersecurity threats involve you the most?
We looked closely at how generative AI weapons are, not just for the deep effects, but for the automation of phishing, producing polymorphic malware and simulating legitimate user behavior. But all of these AI-driven strategies simply evolved to familiar purpose: to deceive people. Therefore, simply “phasing out” cybercriminals is not enough. Security teams must also be able to track user behavior and network activity of abnormal signals, which is the priority of AI.
To ensure our automated protections remain ahead of AI-enabled cyberattacks, Cynet’s product roadmap contains the latest security analyst insights, as well as direct input from Cynet Partners and customers.
Ransomware attacks continue to evolve – How does Cynet’s AI-driven protection prevent and mitigate these attacks?
To prevent ransomware attacks, early detection is key. By automatically detecting threats, identifying their root causes, eliminating all attack components throughout the environment, and providing reports to confirm repairs, the overall combined cybersecurity platform reduces manual events handling by 90% and delivers 50x results.
Do you see where autonomous cybersecurity will soon be real, and where AI independently detects and responds to threats?
Although AI can automatically detect and respond automatically, human analysts should always have a final say in strategic decisions. At Cynet, we adopt AI-driven automation while ensuring security professionals continue to solve problems with high value.
- Cynet’s all-in-one cybersecurity platform automates critical security processes, easing the burden of manual operations, so security teams can focus on strategic planning rather than regular tasks.
- In incident response, Cynet automatically detects threats, determines root causes, eliminates attack components and provides detailed reports. This automation reduces manual event processing by 90% and achieves 50 times the results.
- Despite the high automation, we always emphasize human supervision. Our 24/7 SOC team continuously monitors the environment, validates alerts, and ensures AI-driven actions are aligned with safety best practices.
This balanced approach ensures that automation systems work as expected while allowing human experts to provide critical insights and interventions when necessary.
What role does large language models (LLM) play in cybersecurity? Can they borrow offense and defense?
Cyber criminals put LLMS in a variety of situations. The guardrail can be bypassed relatively easily to prevent malicious activities from mainstream Genai platforms. Clicking a button can launch a social engineering scam on a large scale. Combining easy access to malware suites and RAAS in cybercrime forums, the standards for cybercriminals to cause damage are lower than ever. With Genai, aspiring script kids no longer need advanced hacking skills to do real harm.
Threat participants also use AI to automate cyberattacks. How do you view the AI arms race in cybersecurity?
An AI arms race in cybersecurity is underway, with attackers using AI to automate phishing activities, generate Deepfake content and create more advanced malware. These technologies allow cybercriminals to rapidly scale their attacks and make them harder to detect, thus increasing the overall threat landscape.
My Cynet teammates and I helped the security team fight with AI-Signable Fire. We automate detection, analysis, response and reporting to facilitate results much faster than human teams can. The key to maintaining an advantage is to enhance the latest models of automatic defense through the latest high-quality data, and integrate real-world threat intelligence to adapt to evolving strategies. As AI-driven threats become more complex, proactive defense strategies are crucial to keeping an attacker ahead.
How do you view quantum computing that affects cybersecurity over the next decade? Is Cynet preparing for potential quantum threats?
Quantum computing is an interesting but distant cybersecurity boundary. While it has the potential to undermine traditional encryption methods, I don’t see this as a direct risk in the coming years. Unlike generated AI, which has extensive access and has impacted cybersecurity, quantum computing remains largely limited to research lab and nation-state-level programs.
Currently, financially motivated opponents will face enormous obstacles to accessing and using quantum computing to achieve malicious purposes. The complexity and resources required to conduct quantum-based cyberattacks may temporarily rule out mainstream deployments. That is to say, it is important for cybersecurity providers to maintain proactive R&D methods. Quantum is certainly an area my team will focus on, as technology goes from theory to proof of concept to what organizations may actually face.
Thanks for your excellent interview, and readers who hope to learn more should visit Cynet Security.
