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Perspective & Findings

<h4>How a Guardrail-Free LLM Outsmarted Legacy Cyber Tools</h4>

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Deep Instinct CIO Carl Froggett breaks down new research from Deep Instinct and explains how overconfidence from respondents may be a liability in the new, AI-driven threat landscape.

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AI-generated malware is exploding in volume and sophistication. Legacy cyber tools, built on signatures, heuristics, and aging machine learning, are failing spectacularly in this new era of Dark AI. Yet confidence in these legacy cyber tools remains remarkably high, creating a widening disconnect between perception and reality.In this blog, we dig into the results from our new study of 500 U.S. IT professionals, which clearly highlights that IT professionals, especially in management positions, don’t realize just how quickly the new AI-driven threat landscape is shifting beneath their feet.<h5>AI Threats Are Growing Faster Than Defenders Think</h5>Our study found that 64% of IT professionals believe fewer than one million pieces of AI-generated malware are created each day. Public statistics reveal that more than <a href="https://www.getastra.com/reports/state-of-continous-pentesting-insights/2025">half a million new malware variants</a> are detected daily. The key word: detected. That number reflects only what legacy tools manage to catch. In reality, the daily volume is likely 10x higher, or more. And the more we examined the data, the more concerning the picture became.When Deep Instinct threat analyst Brian Black put legacy tools to the test using AI-generated malware,<a href="https://www.deepinstinct.com/blog/black-hat-hacker-uses-guardrail-free-LLM-to-create-malware-that-evades-legacy-cyber">&nbsp;65 of 73 failed to detect it</a>, a staggering 89% miss rate. If similar patterns hold in production environments, the true daily volume of unseen malware could easily exceed 5M variants.&nbsp;Rather than treat that miss rate as a hard indicator of global malware volume, we frame it as a thought experiment, a way to illustrate just how dramatically detection-based systems can undercount what’s really happening in the wild. And it raises uncomfortable “what ifs.” What if legacy tools are only catching the easiest-to-spot threats (i.e., signature-based)? What if the truly damaging malware is the most evasive? And ultimately, the volume matters because undetected threats compound: as the pool of unseen malware grows, so does the likelihood that a single breach will have catastrophic consequences.As attackers continue automating malware generation with AI, the true scale of the threat is almost certainly orders of magnitude larger than public detection numbers suggest. What we can confidently say is this: threats are accelerating, legacy tools are buckling, and defenders do not realize how far behind they are.<h5>Legacy Systems Are Failing in the Face of AI</h5>This growing threat is concerning on its own, but our study revealed an even deeper issue: confidence in outdated defenses remains insanely high, both literally and figuratively, even as their effectiveness declines.Real-world data reinforces this disconnect. According to the<a href="https://www.idtheftcenter.org/wp-content/uploads/2025/07/ITRC-H1-2025-Data-Breach-Analysis.pdf?utm_source=chatgpt.com">&nbsp;Identity Theft Resource Center’s H1 2025 Data Breach Report</a>, there were 1,732 publicly reported data compromises in the first half of the year, continuing an upward trend that shows how frequently attackers are bypassing legacy security controls. Breaches are rising while confidence remains high, underscoring a widening gap between perception and reality.Here is what we found:<ul><li>Overall confidence remains high: 86% of IT professionals believe their existing tools can stop AI-generated malware pre-execution.<ul><li>A generational confidence curve reinforces the trend: 82% of Baby Boomers, 84% of Gen X, 87% of Millennials, and 90% of Gen Z believe their technologies can stop AI-generated threats. The differences are subtle, but the trend is clear: confidence steadily rises in younger cohorts – yet even the least confident generation reports optimism that far outpaces the real-world performance of legacy defenses. The risk is not that one generation is overconfident; it is that every generation is.</li></ul></li><li>Seniority strongly influences confidence: Directors and above are nearly twice as likely as frontline staff to be very confident their organization can stop malware attacks (42% vs. 24%).</li></ul>This overconfidence is dangerous. Confidence in <a href="https://www.deepinstinct.com/deep-instinct-vs-competitors">legacy cyber tools</a> leads organizations to complacency as they continue to fund defenses that quietly fail, giving attackers the advantage and leaving security teams to fight blind.<h5>FinServ: The Historical Leader Now Falling Behind</h5>For decades, the finance services industry has been at the bleeding edge of cybersecurity – navigating a business environment where risk evaluation is uncompromising, controls are mature, and security spend is nonnegotiable.&nbsp;But our new data tells a different story:&nbsp;<ul><li>Only 26% of IT professionals in the finance industry feel very confident in stopping AI-generated attacks pre-execution – the lowest among major industries.&nbsp;</li><li>Meanwhile, tech and software show the highest confidence (46% very confident), despite operating in some of the most rapidly changing and highly targeted environments.&nbsp;</li></ul>Finance’s pullback should be a clear warning to all other industries. The sector’s declining confidence is not theoretical. Recent attacks, <a href="https://www.cybersecuritydive.com/news/bank-vendor-cyberattack-supply-chain/806293/">such as the breach at financial services vendor SitusAMC</a>, which exposed sensitive data tied to major banks, show how even well-defended institutions remain vulnerable when third-party systems rely on outdated models.&nbsp;If the most sophisticated and well-resourced sector – the one built on risk modeling and paranoia – is losing confidence, it signals a broader unraveling underway, and the outlook for other industries is alarming.&nbsp;Healthcare, for instance, is already struggling to keep pace. Its attack surface is large, porous, aging, and expanding faster than security leaders can reinforce it. Healthcare environments remain deeply dependent on legacy infrastructure, fragmented systems, and outdated tech and vendor stacks. Within the last year, more than <a href="https://www.hipaajournal.com/healthcare-data-breach-statistics/">500</a> healthcare breaches were reported. Their attack surfaces are sprawling, their budgets are strained, and modernization is routinely slowed by regulatory complexity and technical misalignment.&nbsp;If finance is signaling concern, healthcare is already on the front lines. And as both sectors face growing pressure, organizations across every industry are accelerating their AI adoption to keep up, often moving faster than their strategies can support.<h5>The Paradox: Too Slow. Too Fast. Never Strategic Enough.</h5>Organizations across industries are racing to adopt AI technologies to stay competitive, innovate quickly, and keep pace with a rapidly shifting threat landscape. According to our survey, 45% consider themselves early adopters or fast followers (20% early adopters; 25% fast followers).But being the first or fastest to adopt new technology is not a strategy. Speed without direction is how organizations drive straight into the risks they’re trying to outrun. In the rush to modernize, many organizations default to large, familiar security vendors. Not because these vendors offer the strongest protection, but because they appear to be the safest choice. This creates the most dangerous inversion of all.&nbsp;The faster organizations move, the more likely they are to adopt tools that still rely on outdated detection models, leaving them more vulnerable even as they lower their guard.<h5>Closing the Gap: Why Deep Learning is the Only Path Forward</h5>Traditional security models built on signatures, heuristics, and legacy machine learning models weren’t designed for today’s modern threats. Malware mutates in seconds, AI-generated variants bypass static logic instantly, and attackers automate creativity at a scale defenders cannot match. Detection-based systems simply cannot keep up.<a href="https://www.deepinstinct.com/glossary/deep-learning">Deep learning</a> changes that equation by enabling true preemptive data security. It operates at machine speed, identifies never-before-seen threats before execution, and delivers consistent outcomes that give leaders and practitioners a clear view of their real readiness. In an environment defined by rapid mutation and automation, preemptive protection is no longer optional. It is the only viable path forward.Our <a href="https://www.deepinstinct.com/blog/dianna-explains-4-nimbus-manticore-monstrous-malware">research</a> illustrates just how urgent this shift has become. In another recent blog, we detailed Nimbus Manticore, a sophisticated, AI-engineered malware strain that bypassed every legacy on VirusTotal, except for Deep Instinct – for a full week. Discoveries like this highlight a growing and dangerous reality: attackers are advancing faster than detection-based defenses can respond, leaving organizations exposed to threats they never even see.In 2026 and beyond, the organizations that endure will be those that proactively confront the gap between perception and reality and move beyond legacy detection models that attackers already know how to evade. Achieving real preparedness will require leaders to retire outdated assumptions and adopt deep learning-native approaches built for the speed, scale, and sophistication of modern threats.Finance’s caution is a warning. Healthcare’s exposure is a preview. And the broader industry’s naive optimism is a dangerous miscalculation. As millions of AI-generated malware variants rewrite the rules of cyber defense each day, survival will depend on a willingness to rebuild security strategies from the foundation up through a preemptive lens.

Overconfident and Underprepared: IT Leaders Misjudge AI Cyber Risk

Deep Instinct CIO Carl Froggett takes a brief dive into a recent attack distributed to clients of an unnamed MSP in this micro-blog.

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As I’ve been meeting with customers and prospects lately, one question keeps coming up: “Why do I need to protect my storage and applications?”I wanted to share my perspective, shaped by past experience, and explain why I deployed Deep Instinct.The short answer: Assume everything is malicious. Don’t rely on a single layer of defense. Why? At the endpoint, the attacker is already one step from winning. You want to prevent the threat as far away from your critical business services, infrastructure, and data as possible. Cyber technologies are not bullet proof, especially against shifting threats, and supply chain risk is real. (I include any third party in the supply chain, including customers of your business). We tend to trust that our partners and vendors are doing the right thing. And while they may have compliance programs in place, time and again, we’ve seen real world breaches of 'compliant' third parties.An example of this exact situation was recently <a href="https://www.helpnetsecurity.com/2025/05/28/attackers-hit-msp-use-its-rmm-software-to-deliver-ransomware-to-clients/">reported by</a> Help Net Security when an unnamed MSP was compromised by an attacker who then used their access to client environments to upload the DragonForce ransomware. This breakdown in security is significant because the ransomware came from a ‘trusted’ source that had legitimate access, who could push files (various updates) into client environments—because the ability to curate the patches, software updates, and hotfixes going to customer environments is necessary for MSPs.While supply-chain attacks like this have the potential to degrade the trust in an entire industry and create a chokepoint for management, the danger isn’t limited to MSPs. There are many such examples from M&amp;A, zero-trust (between zones), customer-facing documents, and file transfer systems—the list is endless. This incident demonstrates why organizations need to scan everything, including updates from trusted partners.<a href="https://www.deepinstinct.com/dsx/dsx-applications">Data Security X (DSX) for Applications</a> provides an elegant solution to this problem—and it is what I deployed at scale to neutralize this threat vector while at Citi. Using advanced deep learning AI, DSX-A can be deployed by either the customer, or the MSP in this case, to scan and verify the updates being pushed to client environments. Because DSX-A doesn’t rely on rigid machine learning capabilities, known signatures, or human-biased heuristics, it’s able to prevent novel attacks as well as known attacks. Industry-best scan speed also ensures that managed updates don’t become a bottleneck or organizational headache.&nbsp; All of this is done with data privacy in mind, ensuring we neither see nor use your data for any purpose.This deployment provides a significant reduction in risk, adding an advanced layer of <a href="https://www.deepinstinct.com/dsx">preemptive data security</a> before the attacker achieves their objective, which is usually access to your devices and data. Criminals are getting bolder and better every day at bypassing traditional security measures and technologies that the industry has long relied upon. New solutions that can match the flexibility of cybercriminals are an operational imperative in the era of AI-driven threats.Deep Instinct is uniquely capable of providing this new form of preemptive data security. By implementing comprehensive scanning across all data and updates—regardless of source—organizations can better protect themselves against evolving threats. Get your <a href="https://www.deepinstinct.com/free-scan">free scan</a> to see it in action.

Managed Service Malware: The Case for Scanning Everything

Follow along with Deep Instinct on a postmortem of the 2023 MGM attacks. Learn what went wrong, what could have been done to prevent the attack, and what having Deep Instinct would have changed.

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In late 2023, MGM Resorts experienced the beginning of a ransomware cyberattack that would cost them nearly $100M USD. The multi-stage attack was launched by ScatteredSpider, a subgroup of AlphV, and progressed quickly from infiltration to exploitation. By taking advantage of social engineering tactics, injection, and inadequate security practices, ScatteredSpider pulled off one of the highest profile attacks in years. And it didn’t have to happen.&nbsp;&nbsp;<h5>The MGM Attack&nbsp;</h5>In the first phase of the attack, ScatteredSpider (<a href="https://therecord.media/mgm-hack-teenager-arrest-britain">who recently had a 17-year-old member arrested</a> in connection with the MGM hack) used LinkedIn to gather information about an MGM employee and then impersonated that employee on a call to MGM’s IT help desk. Using that access, ScatteredSpider was able to convince the help desk to grant them access, bypassing every existing security control. The attackers then quickly established persistence, installed sniffers, and exfiltrated key admin credentials for Azure, Windows, and Okta. MGM was, at this point, a very securely stuck fly in ScatteredSpider’s web. Because the credentials had already been exfiltrated, MGM’s subsequent attempt to stop the cyberattack by shutting down critical infrastructure was too little, too late.&nbsp;As soon as services came back online, ScatteredSpider was able to use the exfiltrated credentials and persistence to attack their main objective. They identified critical MGM business services running on VMware with 100 ESXi Hypervisors. Hitting this one target caused massive disruption to their hotel reservation systems, gambling, slot machines, digital key room access, and so much more - achieving their desired outcome. Having established Internet communication to their cloud services, they exfiltrated MGM customer data/PII, and deployed ransomware to 100 ESXi VMware Hypervisors: MGM’s entire Virtual Server and some virtual desktop environments. That, kids, is the ballgame.&nbsp;&nbsp;<h5>Rewriting a Successful Attack&nbsp;</h5>Learning the right lessons after a cyberattack is an important part of both remediation and preparation for the next attack. When a high-profile attack like MGM happens, the entire cybersecurity industry gets the chance to analyze, dissect, and ultimately battle game the attack to see what would have worked and what wouldn’t. Everyone should be admitting the same thing about the first phase of the attack: there is not a policy in place, a training you could give, or a tool available that can remove the human element from an attack. The tools malicious actors use are complex, effective, and malleable. With the rise of AI, they’ve only become more dangerous. AI voice and video impersonations are an excellent example of this danger.&nbsp;Initial infiltration was just step one. The real battle took place in the hours and days following the vishing. The attackers installed sniffers and compromised critical infrastructure. The strategy of ‘detect and respond’ falls short here: how much time does it take to detect an attack and how much more time does it take to adequately respond?&nbsp;It’s during that ‘detect and respond’ period that Deep Instinct could have been a difference maker, not just slowing the attack, but preventing it altogether. ScatteredSpider were smart about their attack. The payload was delivered directly to the hypervisor layer; it wasn’t staged on end points, in storage, or delivered via email, thus avoiding several detection and prevention layers. This leaves two points to prevent the attack: the hypervisor layer and the internet delivery. In our tests, Deep Instinct was able to secure both points.&nbsp;<a href="https://www.deepinstinct.com/endpoint-security" target="_self">Deep Instinct EPP</a> running on the hypervisor layer detected and quarantined the payload before it could execute. Similarly, <a href="https://www.deepinstinct.com/dsx/dsx-applications" target="_blank">DSX for Applications</a> integrated into the internet layer via API or ICAP would have also prevented the payload. &nbsp;&nbsp;<h5>Debrief, DIANNA, Do-Over&nbsp;</h5>MGM lost control of their situation the moment the social engineering attack was successful. Their lack of hypervisor partition, secondary credentials, scanning capabilities, and other industry-standard security controls meant that once the attackers had established persistence and exfiltrated admin credentials they would have free run of the place. Having those defenses would have at least hardened MGM as a target but they would not necessarily have prevented the attack completely.&nbsp;Unfortunately, much of the cybersecurity industry’s value-prop isn’t true prevention, it’s disaster mitigation. The biggest success of most tech stack configurations would be that they stopped the bleeding. This cybersecurity philosophy can be cynically distilled into one key question: How much are you willing to lose? At a large enterprise like MGM, even successfully defending against a cyberattack can be costly.&nbsp;Where Deep Instinct makes a difference is the focus on prevention. Barring the human element that allowed access to critical infrastructure, Deep Instinct DPE and DPA would have prevented the actual substantive parts of the MGM attack. The bleeding didn’t have to happen, and the “success” of only a small number of accounts being affected didn’t have to happen. The malicious payload used in the MGM attack could have been immediately caught, quarantined, and deleted pre-execution when scanned by Deep Instinct. Using DIANNA, MGM could have immediately figured out why the payload was caught and deleted.&nbsp;<a href="https://www.deepinstinct.com/news/deep-instinct-introduces-dianna">DIANNA, our generative AI powered cybersecurity companion</a>, was able to tell us nearly instantly (okay, seven seconds) in real language why the Alphv ransomware was malicious, including the markers it used to make that determination. In short order we had both stopped the attack and developed a framework for investigating the attack. In addition to stopping the attack, there are other key benefits for some groups:&nbsp;<ul><li>SOC Teams: In terms of both efficacy and stress, SOC teams are a main beneficiary of effective prevention-first cybersecurity. Given rising rates of burnout among SOC professionals, tools that support their mission are invaluable. Read more about the rates of burnout among SOC professionals in our <a href="https://www.deepinstinct.com/voice-of-secops-reports">2024 Voice of SecOps report</a>.&nbsp;</li></ul><ul><li>MGM: Better cybersecurity reduces organizational risk and increases confidence. A prevention-first approach eliminates the death-by-a-thousand-cuts damage to organizational reputation and budget caused by the current cybersecurity paradigm.&nbsp;</li></ul><ul><li>MGM Customers: Having personal data stolen is incredibly dangerous for consumers and puts them at risk for fraud, identity theft, and other targeted attacks. Not allowing a breach to occur at all increases confidence and mitigates the legal and personal ramifications of allowing personal data to be stolen.&nbsp;</li></ul>Novelty is a weapon. Most of the time it’s a very effective one. The introduction of deepfakes has revolutionized social engineering attacks. Malicious AI has similarly revolutionized cyberattacks. There are more methods than ever for bad actors to gain access to secure systems. AI-powered mutations allow attacks to constantly refresh and renew themselves in novel ways to evade existing cybersecurity. To keep up, defenders need tools that make them equally responsive.&nbsp;<a href="https://info.deepinstinct.com/request-a-demo">Get a demo</a> to see the power of a prevention-first approach for yourself.&nbsp;

Would Have, Could Have, Should Have: Dissecting the 2023 MGM Hack

Explore how Deep Instinct integrated Deep Instinct Prevention for Applications (DPA) with our internal Microsoft SharePoint and OneDrive and strengthened our security. 

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Deep Instinct is well-versed in the need for speed. The unique pressures of the startup environment necessitate near-constant communication and filesharing between employees and our eco-system of partners to meet the needs of our customers. Those files need to be two things: secure and speedy.&nbsp;&nbsp;
To address our needs, we’ve developed the capability to integrate <a href="https://www.deepinstinct.com/prevention-for-applications">Deep Instinct Prevention for Applications (DPA)</a> with our internal Microsoft SharePoint and OneDrive. Let’s look at what this means for us at Deep Instinct and how you can benefit from the same integration.&nbsp;
Exciting things first: this integration isn’t theoretical — it's already live for Deep Instinct and is delivering four key benefits that help us achieve more as a company:&nbsp;&nbsp;
<ul>
 <li>Real-time threat prevention&nbsp;</li>
 <li>Event-driven actions&nbsp;</li>
 <li>Seamless user experience&nbsp;</li>
 <li>Privacy&nbsp;</li>
</ul>
These benefits accelerate our already fast-paced environment and help safeguard the file sharing capabilities we rely on. Now we can be certain when we send or receive files via SharePoint or OneDrive, they’re not malicious.&nbsp;&nbsp;
<h5>Real-Time Threat Prevention&nbsp;</h5>
By integrating Deep Instinct Prevention for Applications with our SharePoint and OneDrive deployments, we scan and classify every file in the environment, quickly quarantining malicious files and stopping them in their tracks. (Of course, those malicious files are coming from outside our organization; we use <a href="https://www.deepinstinct.com/endpoint-security" target="_self">Deep Instinct Prevention for Endpoints</a> to ensure we're not the ones spreading malware.)
Because the scan process happens in near real time, users sharing and receiving files won’t notice the it taking place. Instead of waiting for a file to be scanned and returned, interrupting the flow of work, files scanned by DPA are available immediately, when we need them.
Regardless of size, DPA integrated in your organization would function much the same. It would give you the same real-time threat prevention capabilities without disrupting workflows. In addition to the regular benefits of a Deep Instinct deployment, your organization would no longer need to rely on inconsistent, cumbersome, and slow tools or worry about blind spots in the data estate. One of our biggest customers scans billions of files a month across their organization in a “real-time” data/file collaboration use case. Deep Instinct works on a huge scale.&nbsp;
<h5>Decide How You Defend&nbsp;</h5>
We see the efficacy of this integration every day at Deep Instinct. Clarity into file delivery and scanning gives us peace of mind, while automatic deletion and notification streamlines the security process – still letting people know why a file may not have arrived.&nbsp;
Rather than introducing a laborious identification and remediation process, users can choose to allow Deep Instinct to automatically delete malicious files and notify the recipient, or just issue an alert without deleting the file. Instead of waiting for a breach to happen or leaving you in the dark about the status of a file you’ve requested, this method empowers you to choose your next steps to defend against this attack and the next.
Sole reliance on endpoint security solutions should be a last resort. This integration gives us another layer of security before we have to rely on EDR and prevents bad actors from ever reaching the endpoint in the first place. We keep ourselves safe using the same combination of solutions and tools we use to protect our customers.
And when this integration is combined with <a href="https://www.deepinstinct.com/news/deep-instinct-introduces-dianna">DIANNA, the industry’s first generative AI cyberassistant to provide malware analysis</a> on known and unknown threats, our security teams can easily examine any quarantined and deleted file to determine in seconds why it was flagged, not hours or days.
<h5>Seamless User Experience</h5>
This integration continues to offer the seamless Deep Instinct user experience that only we can offer. It’s an experience we trust and that we’re happy to integrate into our own environment and security posture. The combination of speed, accuracy, and information makes Deep Instinct an invaluable tool for our own teams and accelerates our business processes and yours.
<h5>Privacy</h5>
Deep Instinct is focused on privacy, which is why users are always in control of their own data. Microsoft allows users to “bring your own keys” meaning only the “keyholder” can see the file content. In this case, users control the encryption of SharePoint and OneDrive, not Microsoft. Deep Instinct doesn’t need users to send their data elsewhere to be effective, meaning the chain of custody, encryption, and privacy isn’t broken by a third party. Unlike legacy scanning tools, file provenance can be safeguarded by keeping it within your environment.
The DPA + SharePoint and OneDrive integration is an excellent example of how Deep Instinct implements our products in our own environment. It also illustrates how we can integrate with the same tools your organization already uses to provide a better, safer experience.
Ready to dive deeper? Effective prevention and cybersecurity relies on speed and accuracy. Deep Instinct uses deep learning to prevent threats with more accuracy and speed than any other solution. <a href="https://www.deepinstinct.com/blog/defeat-AI-cyber-threats-with-deep-learning">Learn why deep learning powered threat prevention is at the forefront of the cybersecurity battle</a>.
Security doesn't end with just one tool. Defense in depth is a strategy to keep your organization safe using multiple tools to build an effective wall against breach and attack. <a href="https://info.deepinstinct.com/file-upload-security?_ga=2.109077509.1025104848.1720546918-1577162200.1714240296&_gac=1.238305844.1718135387.EAIaIQobChMIq7m80N3xhQMVc6VaBR19bAn5EAAYASAAEgIJRPD_BwE" target="_self">Explore how Deep Instinct secures your file uploads</a> to see another step you can take to secure your organization.
And if you're ready to take the next step, <a href="https://info.deepinstinct.com/request-a-demo?_ga=2.215978322.475833869.1717446548-1577162200.1714240296&_gac=1.208487718.1716560633.EAIaIQobChMIq7m80N3xhQMVc6VaBR19bAn5EAAYASAAEgIJRPD_BwE">request a demo</a> with one of our knowledgable team to see what Deep Instinct can do for you.

Practicing What We Preach: Preventing Threats in SharePoint and OneDrive

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Job change decisions are always difficult, especially when you've spent over two decades working for the same organization. For me, the challenge was getting out of my comfort zone and embracing a fresh change.So, what inspired me to take the plunge and make Deep Instinct my choice?Having spent most of my career in different roles in what was an ever changing, but still the same organization, I had an itch that I wanted to try something different. At the time I was not able to articulate exactly what would scratch the itch until meeting with some members of Deep Instinct and then it clicked. I realized this is the change that I wanted.<h2>Unparalleled Innovative Technology</h2>I had been a part of Citi for over 25 years, and spent much of this time leading teams responsible for security strategies and engineering aspects, plus day-to-day running of security products/services that protected Citi’s global business units. After more than two decades, I felt like I wanted to do something different in cybersecurity, not just go to another large company and do the same thing again. But how could I utilize my learning and experiences while giving me something of a new fresh perspective and remaining close to technology?This is where Deep Instinct comes in. Moving into the cyber start-up community would enable me to have an impact on many organizations, while being part of something I already knew I enjoyed. I believe that is Deep Instinct and its innovation in deep learning that provides continuous prevention that other approaches cannot match.When Deep Instinct first came across my desk, like most, I felt we had a good solution already. However, the Deep Instinct name kept popping up, so one Saturday morning I reviewed without the distraction of day-to-day activities. It clicked for me what was unique about Deep Instinct, and how I came to believe that deep learning is the next evolution in cybersecurity – just like we leapt from traditional signatures to machine learning. I had such a “ah ha” moment in previous start-up waves; a gem of an idea or approach hidden in a smaller company. Some of those previous moments that I was involved in are now very successful cybersecurity companies today, and myself and the teams I ran had a part to play in their development and strategy that helped them get there. The scratch for my itch had been found!The prevention capabilities of this technology and the ability to constantly expand its knowledge base like the human mind, give deep learning unparalleled potential in our endless fight to protect the enterprise, or now for me, customers and enterprises. History will show Deep Instinct to be the first disruptive company in this next evolutionary wave of preventionThe most exciting aspect of deep learning is that we are yet to explore its full potential. It’s such a scalable technology that can be applied to both devices and non-device specific workloads such as cloud platforms. There’s a massive landscape of security risks and gaps that can be explored with deep learning which I can now explore within the company, expanding our capabilities addressing real problems in cyber. So, who wouldn’t want to be a part of this revolutionary journey?<h2>Great Leadership and Culture</h2>“Blimey! What a passionate group of people” – this was my first impressions when I met the Deep Instinct team – I am British after all. Everyone was genuinely excited, and they really believed in the product. This is not something you see in every cybersecurity company.Due to the stressful nature of the industry, I find that workforces are often unengaged with their organizations and as a leader of large global teams, this was always a priority for me. The Deep Instinct team was very different – they didn’t just talk about their technology stack, we spent time talking about leadership, people, and culture – they really cared. As impressive as the technology is, this feeling is more important to me.<h2>Amazing Reputation</h2>A perk of being in the security industry for so long is that you make a fair share of connections. I asked my friends, ex-colleagues, partners, and former clients about Deep Instinct. None of them had negative feedback about the company or technology, in fact most pushed me into the direction that I really shouldn’t miss the opportunity no matter what else was in my path.Deep Instinct has already achieved a strong foundation, and credibility in the market and with customers all based on the talent and technology with a focus on customer success. The research team continues to excel, combined with the products and technology Deep Instinct is unparalleled today.I am honored and very excited to start a new journey of my life with such an innovative and prospective organization.

DIANNA, the DSX Companion, provides real-time explainability of the threats that matter.

Carl Froggett

From Carl Froggett.