Saryu Nayyar is an internationally acknowledged cybersecurity skilled, creator, speaker and member of the Forbes Expertise Council. She has greater than 15 years of expertise within the info safety, identification and entry administration, IT threat and compliance, and safety threat administration sectors.
She was named EY Entrepreneurial Successful Girls in 2017. She has held management roles in safety services technique at Oracle, Simeio, Solar Microsystems, Vaau (acquired by Solar) and Disney. Saryu additionally spent a number of years in senior positions on the expertise safety and threat administration observe of Ernst & Younger.
Gurucul is a cybersecurity firm that focuses on behavior-based safety and threat analytics. Its platform leverages machine studying, AI, and massive information to detect insider threats, account compromise, and superior assaults throughout hybrid environments. Gurucul is understood for its Unified Safety and Danger Analytics Platform, which integrates SIEM, UEBA (Consumer and Entity Habits Analytics), XDR, and identification analytics to offer real-time menace detection and response. The corporate serves enterprises, governments, and MSSPs, aiming to cut back false positives and speed up menace remediation by clever automation.
What impressed you to start out Gurucul in 2010, and what downside had been you aiming to unravel within the cybersecurity panorama?
Gurucul was based to assist Safety Operations and Insider Danger Administration groups receive readability into essentially the most important cyber dangers impacting their enterprise. Since 2010 we’ve taken a behavioral and predictive analytics strategy, fairly than rules-based, which has generated over 4,000+ machine studying fashions that put person and entity anomalies into context throughout a wide range of totally different assault and threat eventualities. We’ve constructed upon this as our basis, transferring from serving to massive Fortune 50 corporations remedy Insider Danger challenges, to serving to corporations acquire radical readability into ALL cyber threat. That is the promise of REVEAL, our unified and AI-Pushed Information and Safety Analytics platform. Now we’re constructing on our AI mission with a imaginative and prescient to ship a Self-Driving Safety Analytics platform, utilizing Machine Studying as our basis however now layering on Generative and Agentic AI capabilities throughout the whole menace lifecycle. The aim is for analysts and engineers to spend much less time within the myriad in complexity and extra time centered on significant work. Permitting machines to amplify the definition of their day-to-day actions.
Having labored in management roles at Oracle, Solar Microsystems, and Ernst & Younger, what key classes did you deliver from these experiences into founding Gurucul?
My management expertise at Oracle, Solar Microsystems, and Ernst & Younger strengthened my skill to unravel complicated safety challenges and supplied me with an understanding of the challenges that Fortune 100 CEOs and CISOs face. Collectively, it allowed me to realize a front-row seat the technological and enterprise challenges most safety leaders face and impressed me to construct options to bridge these gaps.
How does Gurucul’s REVEAL platform differentiate itself from conventional SIEM (Safety Data and Occasion Administration) options?
Legacy SIEM options depend upon static, rule-based approaches that result in extreme false positives, elevated prices, and delayed detection and response. Our REVEAL platform is totally cloud-native and AI-driven, using superior machine studying, behavioral analytics, and dynamic threat scoring to detect and reply to threats in actual time. Not like conventional platforms, REVEAL constantly adapts to evolving threats and integrates throughout on-premises, cloud, and hybrid environments for complete safety protection. Acknowledged because the ‘Most Visionary’ SIEM answer in Gartner’s Magic Quadrant for 3 consecutive years, REVEAL redefines AI-driven SIEM with unmatched precision, pace, and visibility. Moreover, SIEMs battle with an information overload downside. They’re too costly to ingest every part wanted for full visibility and even when they do it simply provides to the false constructive downside. Gurucul understands this downside and it’s why now we have a local and AI-driven Information Pipeline Administration answer that filters non-critical information to low-cost storage, saving cash, whereas retaining the flexibility to run federated search throughout all information. Analytics programs are a “rubbish in, rubbish out” scenario. If the information coming in is bloated, pointless or incomplete then the output won’t be correct, actionable or in the end trusted.
Are you able to clarify how machine studying and behavioral analytics are used to detect threats in actual time?
Our platform leverages over 4,000 machine studying fashions to constantly analyze all related datasets and determine anomalies and suspicious behaviors in actual time. Not like legacy safety programs that depend on static guidelines, REVEAL uncovers threats as they emerge. The platform additionally makes use of Consumer and Entity Habits Analytics (UEBA) to determine baselines of regular person and entity conduct, detecting deviations that might point out insider threats, compromised accounts, or malicious exercise. This conduct is additional contextualized by an enormous information engine that correlates, enriches and hyperlinks safety, community, IT, IoT, cloud, identification, enterprise utility information and each inside and exterior sourced menace intelligence. This informs a dynamic threat scoring engine that assigns real-time threat scores that assist prioritize responses to important threats. Collectively, these capabilities present a complete, AI-driven strategy to real-time menace detection and response that set REVEAL aside from standard safety options.
How does Gurucul’s AI-driven strategy assist cut back false positives in comparison with standard cybersecurity programs?
The REVEAL platform reduces false positives by leveraging AI-driven contextual evaluation, behavioral insights, and machine studying to tell apart professional person exercise from precise threats. Not like standard options, REVEAL refines its detection capabilities over time, bettering accuracy whereas minimizing noise. Its UEBA detects deviations from baseline exercise with excessive accuracy, permitting safety groups to deal with professional safety dangers fairly than being overwhelmed by false alarms. Whereas Machine Studying is a foundational side, generative and agentic AI play a big position in additional appending context in pure language to assist analysts perceive precisely what is going on round an alert and even automate the response to stated alerts.
What position does adversarial AI play in fashionable cybersecurity threats, and the way does Gurucul fight these evolving dangers?
First all we’re already seeing adversarial AI being utilized to the bottom hanging fruit, the human vector and identity-based threats. Because of this behavioral, and identification analytics are important to with the ability to determine anomalous behaviors, put them into context and predict malicious conduct earlier than it proliferates additional. Moreover, adversarial AI is the nail within the coffin for signature-based detection strategies. Adversaries are utilizing AI to evade these TTP outlined detection guidelines, however once more they’ll’t evade the behavioral based mostly detections in the identical method. SOC groups usually are not resourced adequately to proceed to write down guidelines to maintain tempo and would require a contemporary strategy to menace detection, investigation and response. Habits and context are the important thing elements. Lastly, platforms like REVEAL depend upon a steady suggestions loop and we’re continuously making use of AI to assist us refine our detection fashions, advocate new fashions and inform new menace intelligence our total ecosystem of shoppers can profit from.
How does Gurucul’s risk-based scoring system enhance safety groups’ skill to prioritize threats?
Our platform’s dynamic threat scoring system assigns real-time threat scores to customers, entities, and actions based mostly on noticed behaviors and contextual insights. This allows safety groups to prioritize important threats, decreasing response instances and optimizing assets. By quantifying threat on a 0–100 scale, REVEAL ensures that organizations deal with essentially the most urgent incidents fairly than being overwhelmed by low-priority alerts. With a unified threat rating spanning all enterprise information sources, safety groups acquire larger visibility and management, resulting in quicker, extra knowledgeable decision-making.
In an age of accelerating information breaches, how can AI-driven safety options assist organizations forestall insider threats?
Insider threats are an particularly difficult safety threat as a result of their refined nature and the entry that staff possess. REVEAL’s UEBA detects deviations from established behavioral baselines, figuring out dangerous actions equivalent to unauthorized information entry, uncommon login instances, and privilege misuse. Dynamic threat scoring additionally constantly assesses behaviors in actual time, assigning threat ranges to prioritize essentially the most urgent insider dangers. These AI-driven capabilities allow safety groups to proactively detect and mitigate insider threats earlier than they escalate into breaches. Given the predictive nature of behavioral analytics Insider Danger Administration is race in opposition to the clock. Insider Danger Administration groups want to have the ability to reply and collaborate rapidly, with privateness top-of-mind. Context once more is important right here and appending behavioral deviations with context from identification programs, HR functions and all different related information sources provides these groups the ammunition to rapidly construct and defend a case of proof so the enterprise can reply and remediate earlier than information exfiltration happens.
How does Gurucul’s identification analytics answer improve safety in comparison with conventional IAM (identification and entry administration) instruments?
Conventional IAM options deal with entry management and authentication however lack the intelligence and visibility to detect compromised accounts or privilege abuse in actual time. REVEAL goes past these limitations by leveraging AI-powered behavioral analytics to constantly assess person threat, dynamically modify threat scores, and implement adaptive entry entitlements, minimizing misuse and illegitimate privileges. By integrating with current IAM frameworks and implementing least-privilege entry, our answer enhances identification safety and reduces the assault floor. The issue with IAM governance is identification system sprawl and the shortage of interconnectedness between totally different identification programs. Gurucul provides groups a 360° view of their identification dangers throughout all identification infrastructure. Now they’ll cease rubber stamping entry however fairly take risk-oriented strategy to entry insurance policies. Moreover, they’ll expedite the compliance side of IAM and reveal a steady monitoring and totally holistic strategy to entry controls throughout the group.
What are the important thing cybersecurity threats you foresee within the subsequent 5 years, and the way can AI assist mitigate them?
Identification-based threats will proceed to proliferate, as a result of they’ve labored. Adversaries are going to double-down on gaining entry by logging in both by way of compromising insiders or attacking identification infrastructure. Naturally insider threats will proceed to be a key threat vector for a lot of companies, particularly as shadow IT continues. Whether or not malicious or negligent, corporations will more and more want visibility into insider threat. Moreover, AI will speed up the variations of standard TTPs, as a result of adversaries know that’s how they’ll be capable of evade detections by doing so and it will likely be low price for them to inventive adaptive ways, technics and protocols. Therefore once more why specializing in conduct in context and having detection programs able to adapting simply as quick will probably be essential for the foreseeable future.
Thanks for the nice interview, readers who want to study extra ought to go to Gurucul.
