Aviad Hasnis, CTO at Cynet Security, leads the corporate’s cybersecurity technology strategy, including development of its prolonged detection and response (XDR) platform, threat research, and managed detection and response (MDR) services. Prior to Cynet, he held senior cybersecurity roles within the Israel Defense Forces and holds advanced degrees in engineering and physics from the Technion.
Cynet Security offers an all-in-one automated cybersecurity platform designed to simplify protection for small and mid-sized organizations. Its solution integrates endpoint, network, user, email, and cloud security with built-in automation, XDR capabilities, and 24/7 MDR support.
Cybersecurity is an ever-evolving field. How do you balance staying ahead of threats while keeping solutions user-friendly and accessible to small and mid-sized businesses?
Lean SMB security teams must confront the identical threats facing a Fortune 500 — with a fraction of the personnel or resources or budget. As cyberattacks soar in volume and complexity, SMB security leaders are driving demand for simplified, automated and consolidated security solutions to cut back complexity and improve protection.
At Cynet, my team purposely built the All-in-One Cybersecurity Platform to mix a full suite of security capabilities on a single, easy, AI-enabled solution.
- By unifying environment-wide visibility and protection on one intuitive dashboard, Cynet maximizes user-friendly simplicity.
- By automating key security processes, Cynet helps lean teams maximize efficiency.
Cynet’s platform is described as natively automated—are you able to explain how AI and automation play a job in detecting and mitigating cyber threats?
My team designed Cynet’s All-in-One Cybersecurity Platform to automate processes so people can spend less time managing day-to-day operations and more time constructing their business.
At Cynet, my team also takes pride in a “built, not bought” approach. Every capability, feature and automation of the All-in-One Cybersecurity Platform is developed in-house, from the bottom up, and natively integrated so all the pieces just works seamlessly out of the box. This eliminates integration gaps and overlaps that may compromise automated protections.
The MITRE ATT&CK evaluations ranked Cynet among the many top performers. What AI-driven strategies contributed to this success?
I’m immensely pleased with my team’s contributions to Cynet’s record-breaking performance in essentially the most recent MITRE ATT&CK Evaluation. There’s a great reason MITRE ATT&CK is essentially the most trusted independent assessment amongst cybersecurity decision makers. MITRE uses real-world cyberattack scenarios to measure the performance of competing security platforms. That Cynet was the one vendor to attain 100% Protection and 100% Detection Visibility reflects our commitment to constructing a reliable product for Cynet partners and customers all over 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?
AI-enabled cybersecurity solutions are only when integrated with expert oversight. While AI can process and analyze vast amounts of information rapidly, it’s crucial to have experienced cybersecurity professionals providing ongoing supervision. My team at Cynet ensures that AI systems’ decisions are constantly validated, stopping situations where AI could potentially miss nuanced threats or make incorrect conclusions. In cybersecurity, where risks evolve quickly, human expertise is crucial to interpreting results and making context-sensitive decisions.
To supply partners and customers with an extra layer of protection, Cynet backs the All-in-One Cybersecurity Platform with around-the-clock SOC support. Cynet’s SOC is staffed 24/7 by world-class analysts, ensuring that end-user environments are proactively monitored in any respect times, complementing automated scans. This unique combination of automated protection and hands-on expertise maximizes the peace of mind for Cynet partners and customers.
With the rise of deepfake attacks, AI-generated malware, and complicated social engineering, what emerging cybersecurity threats concern you essentially the most?
We’re closely watching how generative AI is being weaponized—not only to craft deepfakes, but to automate phishing, generate polymorphic malware, and simulate legitimate user behavior. But all these AI-powered tactics are simply evolved means to a well-known end: tricking people. Due to this fact, it just isn’t enough to easily keep cybercriminals “out”. Security teams also must have the opportunity to trace user behavior and network activity for abnormal signals, and that’s a priority AI can assist.
To make sure our automated protections stay a step ahead of AI-enabled cyberattacks, Cynet’s product roadmap incorporates the most recent security analyst insights, in addition to direct input from Cynet partners and customers.
Ransomware attacks proceed to evolve—how does Cynet’s AI-driven protection prevent and mitigate these attacks?
To thwart ransomware attacks, early detection is vital. By mechanically detecting threats, determining their root cause, eradicating all attack components throughout the environment, and delivering a report to substantiate remediation, the All-in-One Cybersecurity Platform reduces manual incident handling by 90% and delivers 50 times faster results.
Do you see autonomous cybersecurity—where AI independently detects and responds to threats without human intervention—becoming a reality soon?
Though AI can automate detection and response, human analysts should at all times have the ultimate say in strategic decisions. At Cynet, we embrace AI-driven automation while ensuring that security professionals remain engaged in high-value problem-solving.
- The Cynet All-in-One Cybersecurity Platform automates key security processes, reducing the burden of manual operations so security teams can concentrate on strategic initiatives moderately than routine tasks.
- In incident response, Cynet mechanically detects threats, determines root causes, eradicates attack components, and delivers detailed reports. This automation reduces manual incident handling by 90% and achieves 50-times faster results.
- Despite this high level of automation, we at all times emphasize human oversight. Our 24/7 SOC team constantly monitors environments, validates alerts, and ensures that AI-driven actions align with security best practices.
This balanced approach ensures that automated systems work as intended while allowing human experts to offer critical insight and intervention when essential.
What role do large language models (LLMs) play in cybersecurity? Can they be leveraged for each offense and defense?
Cybercriminals are putting LLMs to all forms of no good. Guardrails to forestall mainstream GenAI platforms from performing malicious activity may be bypassed with relative ease. Social engineering scams may be launched at scale with the press of a button. Combined with easy accessibility to malware kits and RaaS in cybercriminal forums, the bar for cybercriminals to do damage is lower than ever. With genAI, aspiring script kiddies now not need advanced hacking skills to do real damage.
AI can also be getting used by threat actors to automate cyberattacks. How do you see the AI arms race in cybersecurity playing out?
The AI arms race in cybersecurity is well underway, with attackers using AI to automate phishing campaigns, generate deepfake content and create more advanced malware. These technologies allow cybercriminals to scale their attacks rapidly and make them tougher to detect, increasing the general threat landscape.
My Cynet teammates and I help security teams fight AI-enabled fire with AI-enabled fire. We automate detection, evaluation, response and reporting to facilitate results far faster than human teams alone could. The important thing to maintaining an edge is to constantly refine models with up-to-date, high-quality data, enhance automated defenses, and integrate real-world threat intelligence to adapt to evolving tactics. As AI-driven threats grow more sophisticated, proactive defense strategies will probably be critical in staying ahead of attackers.
How do you see quantum computing affecting cybersecurity in the following decade? Is Cynet preparing for potential quantum threats?
Quantum computing is an intriguing but distant frontier in cybersecurity. While it has the potential to interrupt traditional encryption methods, I don’t see it as an instantaneous risk in the following few years. Unlike generative AI, which is widely accessible and already impacting cybersecurity, quantum computing stays largely confined to research labs and nation-state-level initiatives.
Currently, financially motivated adversaries would face significant hurdles to access and use quantum computing for malicious purposes. The complexity and resources required to conduct a quantum-based cyberattack likely preclude mainstream deployment in the interim. That said, it’s essential for cybersecurity vendors to take care of a proactive approach to R&D. Quantum is definitely an area my team will probably be maintaining a tally of because the technology advances from theoretical to proof of concept to something organizations might actually face within the wild.
