Yariv Fishman is Chief Product Officer (CPO) at Deep Intuition, he is a seasoned product administration govt with greater than 20 years of management expertise throughout notable international B2B manufacturers. Fishman has held a number of distinguished roles, together with management positions with Microsoft the place he led the Cloud App Safety product portfolio and initiated the MSSP and safety associate program, and Head of Product Administration, Cloud Safety & IoT Safety at CheckPoint. He holds a B.Sc in Data Techniques Engineering from Ben Gurion College and an MBA from the Technion, Israel Institute of Know-how.
Deep Intuition is a cybersecurity firm that applies deep studying to cybersecurity. The corporate implements AI to the duty of stopping and detecting malware.
Are you able to inform us about your journey within the cybersecurity trade and the way it has formed your strategy to product administration?
All through my 20 yr profession, I’ve labored at a number of international B2B organizations, together with Examine Level Software program Applied sciences and Microsoft, the place I led product administration and technique and constructed my cybersecurity expertise throughout public cloud, endpoint, community, and SaaS utility safety.
Alongside the way in which, I’ve realized completely different finest practices – from find out how to handle a staff to find out how to inform the right technique – which have formed how I lead at Deep Intuition. Working for quite a few cybersecurity corporations of varied sizes has allowed me to get a holistic view of administration kinds and discover ways to finest create processes that assist fast-moving groups. I’ve additionally seen first-hand find out how to launch merchandise and plan for product-market match, which is crucial to enterprise success.
What drew you to affix Deep Intuition, and the way has your position advanced because you began as Chief Product Officer?
As an trade veteran, I not often get enthusiastic about new expertise. I first heard about Deep Intuition whereas working at Microsoft. As I realized in regards to the potentialities of predictive prevention expertise, I shortly realized that Deep Intuition was the true deal and doing one thing distinctive. I joined the corporate to assist productize its deep studying framework, creating market match and use circumstances for this first-of-its-kind zero-day information safety answer.
Since becoming a member of the staff three years in the past, my position has modified and advanced alongside our enterprise. Initially, I targeted on constructing our product administration staff and related processes. Now, we’re closely targeted on technique and the way we market our zero-day information safety capabilities in in the present day’s fast-moving and ever-more-treacherous market.
Deep Intuition makes use of a novel deep studying framework for its cybersecurity options. Are you able to focus on some great benefits of deep studying over conventional machine studying in risk prevention?
The time period “AI” is broadly used as a panacea to equip organizations within the battle in opposition to zero-day threats. Nevertheless, whereas many cyber distributors declare to convey AI to the struggle, machine studying (ML) – a much less refined type of AI – stays a core a part of their merchandise. ML is unfit for the duty. ML options are educated on restricted subsets of obtainable information (sometimes 2-5%), supply solely 50-70% accuracy with unknown threats, and introduce false positives. In addition they require human intervention as a result of they’re educated on smaller information units, rising the probabilities of human bias and error.
Not all AI is equal. Deep studying (DL), probably the most superior type of AI, is the one expertise able to stopping and explaining identified and unknown zero-day threats. The excellence between ML and DL-based options turns into evident when inspecting their skill to establish and forestall identified and unknown threats. Not like ML, DL is constructed on neural networks, enabling it to self-learn and prepare on uncooked information. This autonomy permits DL to establish, detect, and forestall advanced threats. With its understanding of the elemental parts of malicious information, DL empowers groups to shortly set up and preserve a sturdy information safety posture, thwarting the following risk earlier than it even materializes.
Deep Intuition just lately launched DIANNA, the primary generative AI-powered cybersecurity assistant. Are you able to clarify the inspiration behind DIANNA and its key functionalities?
Deep Intuition is the one supplier available on the market that may predict and forestall zero-day assaults. Enterprise zero-day vulnerabilities are on the rise. We noticed a 64% improve in zero-day assaults in 2023 in comparison with 2022, and we launched Deep Intuition’s Synthetic Neural Community Assistant (DIANNA) to fight this rising pattern. DIANNA is the primary and solely generative AI-powered cybersecurity assistant to offer expert-level malware evaluation and explainability for zero-day assaults and unknown threats.
What units DIANNA other than different conventional AI instruments that leverage LLMs is its skill to offer insights into why unknown assaults are malicious. At present, if somebody needs to elucidate a zero-day assault, they must run it by a sandbox, which might take days and, ultimately, will not present an elaborate or targeted rationalization. Whereas precious, this strategy solely provides retrospective evaluation with restricted context. DIANNA would not simply analyze the code; it understands the intent, potential actions, and explains what the code is designed to do: why it’s malicious, and the way it would possibly affect programs. This course of permits SOC groups time to concentrate on alerts and threats that really matter.
How does DIANNA’s skill to offer expert-level malware evaluation differ from conventional AI instruments within the cybersecurity market?
DIANNA is like having a digital staff of malware analysts and incident response consultants at your fingertips to offer deep evaluation into identified and unknown assaults, explaining the methods of attackers and the behaviors of malicious information.
Different AI instruments can solely establish identified threats and current assault vectors. DIANNA goes past conventional AI instruments, providing organizations an unprecedented stage of experience and perception into unknown scripts, paperwork, and uncooked binaries to arrange for zero-day assaults. Moreover, DIANNA offers enhanced visibility into the decision-making means of Deep Intuition’s prevention fashions, permitting organizations to fine-tune their safety posture for max effectiveness.
What are the first challenges DIANNA addresses within the present cybersecurity panorama, significantly relating to unknown threats?
The issue with zero-day assaults in the present day is the lack of awareness about why an incident was stopped and deemed malicious. Menace analysts should spend important time figuring out if it was a malicious assault or a false optimistic. Not like different cybersecurity options, Deep Intuition was routinely blocking zero-day assaults with our distinctive DL answer. Nevertheless, clients have been asking for detailed explanations to higher perceive the character of those assaults. We developed DIANNA to boost Deep Intuition’s deep studying capabilities, scale back the pressure on overworked SecOps groups, and supply real-time explainability into unknown, refined threats. Our skill to focus the GenAI fashions on particular artifacts permits us to offer a complete, but targeted, response to handle the market hole.
DIANNA is a big development for the trade and a tangible instance of AI’s skill to resolve real-world issues. It leverages solely static evaluation to establish the habits and intent of varied file codecs, together with binaries, scripts, paperwork, shortcut information, and different risk supply file sorts. DIANNA is greater than only a technological development; it is a strategic shift in the direction of a extra intuitive, environment friendly, and efficient cybersecurity surroundings.
Are you able to elaborate on how DIANNA interprets binary code and scripts into pure language stories and the advantages this brings to safety groups?
That course of is a part of our secret sauce. At a excessive stage, we are able to detect malware that the deep studying framework tags inside an assault after which feed it as metadata into the LLM mannequin. By extracting metadata with out exposing delicate info, DIANNA offers the zero-day explainability and targeted solutions that clients are in search of.
With the rise of AI-generated assaults, how do you see AI evolving to counteract these threats extra successfully?
As AI-based threats rise, staying forward of more and more refined attackers requires transferring past conventional AI instruments and innovating with higher AI, particularly deep studying. Deep Intuition is the primary and solely cybersecurity firm to make use of deep studying in its information safety expertise to stop threats earlier than they trigger a breach and predict future threats. The Deep Intuition zero-day information safety answer can predict and forestall identified, unknown, and zero-day threats in <20 milliseconds, 750x sooner than the quickest ransomware can encrypt – making it an important addition to each safety stack, offering full, multi-layered safety in opposition to threats throughout hybrid environments.
Thanks for the good interview, readers who want to study extra ought to go to Deep Intuition.
