In the recent episode of The Security Strategist Podcast, host Richard Stiennon, Chief Research Analyst at IT-Harvest, sat down with John Amaral, Co-Founder and CTO of Root. They discussed how automation, AI agents, and a new approach called “Shift Out” are changing vulnerability management. 

Amaral, who has decades of experience in security leadership, argues for moving beyond the industry’s traditional “shift left” concept. He believes organisations should focus on systems that prioritise scale, speed, and effective fixes.

Amaral says the “shift left” promise never came true. Even with positive intentions, sending vulnerability lists back to developers created overloaded backlogs and slow remediation times, resulting in frustration for everyone involved.

Engineers are experts in their application code, but not in the vast and complex open-source libraries their software relies on. When security scanners present hundreds of CVEs, “roadmap wins out over security,” Amaral explains. Often, maintainers only patch newer versions, leaving production teams stuck with outdated releases and no safe upgrade options.

Read: What is DevSecOps? and Why It Matters

Shift Out is Root’s solution to this flawed workflow. Instead of adding to developers' workloads, organisations can assign the entire fix process—including patch creation, testing, and delivery—to an automated system led by domain experts. 

“Don’t give it to developers, give it to us,” The Root co-founder states. “We’ll take it.”

When discussing the idea of an external system modifying customer code, Amaral clarifies that Root doesn’t alter first-party code. Instead, they fix the open-source libraries that customers use—libraries that are already out of their control.

Amaral points out that the current industry practice of blindly upgrading to new maintainer versions is much riskier. With the rise of supply-chain attacks, and maintainers often unable to apply fixes to older versions, companies increasingly face a troubling maintenance gap.

To build trust and transparency, Root publicly shares all of its backported patches in a GitHub repository. This allows maintainers, independent developers, and the broader open-source community to examine, use, or build upon Root’s work. “If people want to use them, they can,” Amaral states. “It’s our responsibility to make that available.”

Amaral’s message for technology leaders is that as AI changes the software landscape, organisations should adopt a remediation-first mindset. They should begin development with secure, pre-fixed libraries instead of rushing to address CVEs later. With AI-driven remediation now feasible at scale, maintaining secure software should become a standard practice, not an urgent afterthought.

• AI is revolutionising vulnerability management.
• Shift Out is a new approach to security.
• Automation can alleviate the burden on developers.
• Trust is essential for adopting new security solutions.
• Open source maintenance is crucial for security.
• Backported patches benefit the wider community.
• Traditional methods of vulnerability management are becoming obsolete.
• Organisations need to start with secure libraries.
• AI can provide scalable security solutions.
• The future of security lies in automation and AI.

• 00:00 Introduction to AI in Vulnerability Management
• 03:06 The Shift Out Mindset
• 05:51 Make vs. Buy: The Agent Dilemma
• 09:02 Building Trust with Customers
• 11:54 Open Source and Backported Patches
• 14:59 The Future of Vulnerability Management

Root eradicates the CVE grind by delivering open source software that is free of known vulnerabilities, secure by default, and ready to use without additional engineering effort. Powered by thousands of specialised AI agents, Root continuously detects, patches, tests, and ships fixed components across any tech stack in minutes—with full transparency, no forced upgrades, and no vendor-locked images.

AppSec teams get immediate remediation without waiting on developers. Engineers stay focused on building products instead of managing patches. And organisations dramatically reduce exposure windows by moving security at AI speed. Root is building the backbone of the agentic software supply chain, where open source is secure from day one.

As AI tools proliferate inside enterprises, often faster than security teams can track or govern them, a new class of risks are emerging. 

In this episode of the Security Strategist Podcast, IT-Harvest Chief Research Analyst Richard Stiennon sits down with Art Gilliland, CEO of Delinea, to discuss the explosive adoption of AI, the rise of shadow AI, and why identity-centric governance is becoming an urgent priority. Gilliland emphasises the importance of managing AI risks, particularly with machine identities, and the need for intelligent authorization systems to enhance security operations. 

When Gilliland joined Delinea, he believed in focusing on identity, along with policies that govern it. “In the cloud, you share responsibility. In SaaS, you delegate. But you always own your users—human or machine—and your data.”

Delinea has been integrating AI internally for years. One of the most transformative outcomes was the launch of Delinea Expert, an AI assistant built directly into the product interface. Users can upload screenshots, logs, or questions and receive precise guidance on how to fix or configure the product. It acts, Gilliland says, like a support person on your shoulder.

“We shipped it about a year ago, and it reduced our inbound call volume by 60%.”

This dramatic result mirrors what Gilliland sees across customers: rapid adoption, often through quick toy implementations that still deliver massive value.

But with the rapid adoption of AI comes a wider exposure surface. Business teams are driving AI, CEOs are demanding it, and developers are already using it. However, Gilliland believes security is still trying to catch up—again.

“There's this huge gap between the consumption and use of AI and a company’s ability to get in front of it.”

This gap is what many call shadow AI. Unlike historical shadow IT, this version is often approved—business leaders want it. But they lack visibility, policy, or governance structures to ensure it’s secure. Delinea’s recent survey found that “95 per cent of customers are already using or planning to use AI,” spotlights Gilliland, while just “40 per cent have any governance in place.”

Gilliland warns that the dynamic resembles earlier waves—laptops, mobile, Wi-Fi, cloud—but has accelerated dramatically. “It’s inevitably going to be used because it’s so powerful. You can’t hold it back—and you wouldn’t want to.”

This is the future: using AI to manage AI. “AI behaves differently than traditional machine identities. It can make decisions. It has intent.” Because machine-to-machine connections now operate quickly and with shifting intent, organisations need systems capable of evaluating every single request in real time.

Traditional machine identities are predictable—like a robot performing the same task endlessly. Attacks happened when credentials were stolen and misused by humans with intent, as in the Salesforce/Drift breach.

“AI is going to have a machine connection, which tends to be overprivileged. But it can also make decisions on its own.”

Companies must not only build governance, inventory systems, and manage credentials—they must evolve toward understanding intent.

“AI is not static. There’s intent behind the connection. Your controls must be able to interpret that intent. That’s where AI is taking us,” Delinea CEO tells Stiennon.

• AI is a hot topic in cybersecurity today.
• There is a significant gap between AI adoption and governance.
• Shadow AI is becoming prevalent in organisations.
• Companies need to establish a governance structure for AI.
• AI-driven tools can enhance security operations.
• Zero standing privileges are essential for security.
• Organisations must manage machine identities effectively.
• Intelligent authorisation can reduce security risks.
• Understanding intent in AI interactions is crucial.
• A crawl, walk, run approach is recommended for AI governance.

• 00:00 Introduction to AI in Identity Security
• 03:19 Governance Gaps in AI Usage
• 07:09 The Rise of Shadow AI
• 11:19 Managing AI Risks and Machine Identities
• 16:11 Intelligent Authorisation and Security Operations
• 20:27 Final Thoughts on AI Governance

Delinea is a pioneer in securing human and machine identities through intelligent, centralized authorization, empowering organizations to seamlessly govern their interactions across the modern enterprise. Leveraging AI-powered intelligence, Delinea’s leading cloud-native Identity Security Platform applies context throughout the entire identity lifecycle – across cloud and traditional infrastructure, data, SaaS applications, and AI. It is the only platform that enables you to discover all identities – including workforce, IT administrator, developers, and machines – assign appropriate access levels, detect irregularities, and respond to threats in real-time. With deployment in weeks, not months, 90% fewer resources to manage than the nearest competitor, and a 99.995% uptime, Delinea delivers robust security and operational efficiency without compromise. Learn more about Delinea on Delinea.com, LinkedIn, X, and YouTube.

In the recent episode of The Security Strategist podcast, Jim Waggoner, VP of Product Strategy at N-able, and Joe Ferla, one of N-able’s Head Nerds, speak to host Chris Steffen, Vice President of Research at Enterprise Management Associates (EMA). They addressed one of cybersecurity’s biggest misconceptions – while organizations might be getting better at spotting threats, most still struggle to respond to them in real time.

“We live in a time where the threat landscape is changing instantly,” Steffen said. With threat actors speeding up their tactics, Waggoner and Ferla insist that the only way forward is constant reassessment.

Steffen began by asking the IT leaders about a key challenge faced by many CISOs. He says that the industry often talks about “EDR, MDR, XDR,” yet the promise of real-time response frequently remains unfulfilled.

Ferla identified a major problem here: the wrong people are making purchasing decisions. “In the small to mid market, I often see decision-makers who aren’t security experts, and they’re the ones driving the purchasing,” he explained. These executives “trust that the product works as they want, but they don’t know what they really need in the field,” which leads organizations to buy advanced tools they cannot actually use.

Even more troubling, Ferla noted that many customers request capabilities that no MDR could or should handle. “I have people at N-able coming to me thinking that we can manage backups as a response. And that's simply not possible.”

Waggoner, who spent years developing incident response tools, sees another side of the issue. Vendors often downplay the “response” aspect. “When it came to the R,” he said, “it was a little R.” True MDR has to go well beyond automated blocking. “Can we disable accounts? Can we prevent ransomware from affecting other systems or stop lateral movement?”

Also Read: N-able Annual Threat Report 2025

When asked about the future of detection and response, Ferla shed light on the increasing complexity. He remembered running an MSP alone just a few years ago. “Nowadays, I could not come anywhere near close to doing this,” he said. “It's impossible.”

Waggoner stated that AI will shape the next phase—not just for attackers, but also for defenders who face ongoing staffing shortages. Threat actors are already using AI to change tactics and automate reconnaissance. Defenders need to keep up: “Look at companies like us, using AI for detection models and for responses to address the people shortage.”

Waggoner encouraged IT decision-makers to find ways AI can strengthen their security, not make it more complicated. “Get ahead of it. See how you can truly use AI's capabilities to better protect yourself,” he stated.

• Detection and response tools are evolving rapidly.
• Organizations often have unrealistic expectations of their security capabilities.
• Continuous review of security strategies is essential.
• MSPs play a crucial role in enhancing security for small to mid-sized businesses.
• Proactive measures are necessary to stay ahead of threats.
• AI is transforming the cybersecurity landscape.
• Maturity in security means recognizing gaps and seeking help.
• Implementing effective detection requires visibility across all systems.
• The threat landscape is constantly changing, requiring adaptive strategies.
• Basic security practices must be done well to mitigate risks.

• 00:00 Introduction to Cybersecurity Strategies
• 02:54 Understanding Detection and Response Tools
• 05:52 The Gap Between Expectation and Reality
• 09:06 The Importance of Continuous Strategy Review
• 12:11 The Role of Managed Service Providers (MSPs)
• 15:09 Implementing Effective Detection and Response
• 17:52 Future Trends in Cybersecurity
• 20:47 Final Thoughts and Key Takeaways

Modern enterprises face a growing challenge in managing thousands of devices, applications, and identities across increasingly complex IT environments. Unmanaged assets, shadow IT, and inconsistent processes can quietly create security gaps that expose organisations to significant risk.

In this episode of Security Strategist, Syed Ali, Chief Executive Officer of EZO, joins host Chris Steffen to discuss how IT asset management (ITAM) and deterministic automation provide the visibility and control organizations need to secure their digital landscapes.

“There are risks lying around in the organization,” Ali explains. “A good ITAM solution helps identify them and forms the foundation for maturing IT operations.” His insights are drawn from years of experience as both an IT practitioner and entrepreneur, offering practical lessons for IT leaders and security professionals alike.

Effective ITAM solutions are more than just inventory tools; they are central to reducing cybersecurity risk. By automating asset discovery, monitoring, and reporting, organizations gain accurate, up-to-date visibility into every device, software, and identity across their networks.

“Automation runs in IT; it has always run in IT,” Ali notes. Deterministic automation ensures processes are consistent and predictable, allowing IT teams to spot vulnerabilities, reduce the likelihood of human error, and respond quickly to emerging threats. This approach also makes data reliable for decision-making, supporting procurement, patch management, and risk mitigation strategies.

Unmanaged assets, he warns, can “come back to bite us,” particularly when organizations lack visibility into endpoints, applications, and shadow identities. Implementing ITAM proactively rather than reactively is crucial for organizations that want to minimize risk rather than simply meet compliance requirements.

Looking forward, agentic AI and identity-aware assets are shaping the future of ITAM. While AI introduces powerful capabilities, keeping it separate from deterministic automation ensures organizations maintain control while enhancing visibility and security.

Investing in effective ITAM and automation is an enduring strategy for securing assets, reducing risk, and enabling informed decision-making. As Syed explains, “The system is meant to work for you, but that only happens if there’s discipline and awareness in identifying risks. The danger of not having a solid item in place is very real. I also understand that an understaffed IT team, constantly reacting to issues, can’t always prioritise these risks effectively. Unfortunately, that’s the reality we’re dealing with.”

To learn more about effective ITAM solutions, visit EZO.

For more insights follow EZO:

• X: @ezosolutions
• Instagram: @ezo.solutions
• Facebook: https://www.facebook.com/EZOsolutions/
• LinkedIn: https://www.linkedin.com/company/ezosolutions/

• IT asset management is crucial for reducing cybersecurity risks.
• Automation in IT has always been a fundamental practice.
• Unmanaged assets pose significant risks to organizations.
• Effective ITAM solutions provide reliable data for decision-making.
• Organizations often implement ITAM reactively after incidents occur.
• IT departments face challenges of being understaffed and prioritizing tasks.
• Organizational maturity influences readiness for advanced ITAM tools.
• Future ITAM trends include identity-aware items and usage-based pricing models.
• A good ITAM solution helps identify risks faster and more effectively.
• CISOs should focus on managing unmanaged assets and shadow identities.

00:00 Introduction to IT Asset Management and Automation

07:59 The Importance of Deterministic Control in IT Management

13:06 Cybersecurity Risks and IT Asset Visibility

15:05 Challenges in Implementing IT Asset Management

19:11 Organizational Maturity and Tooling Readiness

21:27 Future Trends in IT Asset Management

EZO began as EZ Web Enterprises in 2011 with a mission to build easy-to-use yet powerful cloud-based applications for organizations worldwide. Our team is passionate about delivering consistently amazing user experiences with best-in-class functionality and enterprise scalability. EZO’s products help thousands of organizations around the globe streamline operations in many key areas, including physical asset management with EZOfficeInventory, IT asset management with EZO AssetSonar, equipment maintenance management with EZO CMMS and rental business management with EZRentOut. 

Follow EM360Tech for more insights:

Website: www.em360tech.com

X: @EM360Tech

LinkedIn: EM360Tech

“People love the idea that an agent can go out, learn how to do something, and just do it,” Jeff Hickman, Head of Customer Engineering, Ory, said. “But that means we need to rethink authorization from the ground up. It’s not just about who can log in; it’s about who can act, on whose behalf, and under what circumstances.”

In the latest episode of The Security Strategist Podcast, Ory’s Head of Customer Engineering, Jeff Hickman, speaks to host Richard Stiennon, the Chief Research Analyst at IT-Harvest. They discuss a pressing challenge for businesses adopting AI: managing permissions and identity as autonomous agents start making their own decisions.

They particularly explore the implications of AI agents acting autonomously, the need for fine-grained authorization, and the importance of human oversight. The conversation also touches on the skills required for effective management of AI permissions and the key concerns for CISOs in this rapidly changing environment.

The fear that AI agents can go rogue or exceed their bounds is very real. They are not just tools anymore; instead, they can now negotiate data, trigger actions, also process payments. Without the right authorisation model, Hickman warns that organizations will encounter both security gaps and operational chaos.

Also Watch: Is Your CIAM Ready for Web-Scale and Agentic AI? Why Legacy Identity Can't Secure Agentic AI

Traditional IAM frameworks aren’t designed for agents that think, adapt, and scale quickly. Anticipating a major shift, Hickman says, “It’s not just about role-based access anymore. We’re moving toward relationship-based authorization—models that understand context, identity, and intent among users, agents, and systems.”

Citing Google’s Zanzibar model, the Ory lead customer engineer says that it’s a starting point for this new era. Unlike static roles, it outlines flexible, one-to-one relationships between people, tools, and AI systems. This flexibility will be crucial as organizations deploy millions of autonomous agents operating under various levels of trust.

But technology alone won’t solve the issue. Hickman stresses the importance of the human element, saying, “We need humans to define the initial set of permissions. The person who creates an agent should be able to establish the boundaries—in plain language, if possible. The AI should understand those instructions as a core part of its operating model.”

This leads to a multi-pronged identity system where humans, agents, and services all verify authorization on behalf of the user before any action takes place—ensuring accountability even when AI acts autonomously.

As AI systems grow more sophisticated, the people managing them must also evolve. Hickman outlines a three-part skill structure every organization should develop:

• Identity and Access Architects: To define how agents authenticate, represent and act on behalf of users, and scale securely.
• AI Behaviour Analysts: A new role that bridges technical and business insights, understanding how LLMs make decisions and how to align that behaviour with enterprise goals.
• Business Strategists: To figure out what data and capabilities the organization is willing to expose to agents and how those choices support the company’s broader objectives.

“This is more than IAM,” Hickman tells Stiennon. “It’s about understanding how AI consumes, interprets, and acts on information. We’ll need specialists who can analyse agent behaviour much like data analysts examine purchasing trends.”

Hickman adds that, similar to cybersecurity reputation systems, directories of “known good agents” will help organizations confirm the legitimacy and trustworthiness of the AI systems they interact with.

“The future of AI security,” Hickman concludes, “isn’t just about protecting data; it’s about protecting decisions.”

Explore how Ory helps global businesses build fine-grained, scalable, and future-ready identity systems for humans and machines. Visit Ory.com.

• AI agents are increasingly autonomous and can operate outside defined boundaries.
• Permissions for AI agents must evolve beyond traditional models like OAuth.
• The scale of AI agents will significantly impact identity infrastructure.
• Fine-grained authorization is essential for managing AI agent access.
• Human oversight is crucial in ensuring AI agents operate within acceptable limits.
• Organizations need to define clear guardrails for AI agent behaviour.
• The role of traditional IAM professionals will change with AI integration.
• Understanding AI behaviour patterns will become a necessary skill.
• CISOs should prioritise the prompt identification of risks in AI security.
• A new class of professionals will emerge to manage AI interactions.

• 00:00 Introduction to AI Agents and Permissions
• 02:47 Challenges in AI Agent Authorization
• 05:59 The Scale Problem of AI Agents
• 09:01 Fine-Grained Authorization for AI Agents
• 12:07 The Role of Human Oversight in AI
• 14:56 Evolving Responsibilities in AI Permissions
• 17:56 Skills Needed for Effective AI Management
• 20:46 Key Concerns for CISOs Regarding AI Agents

With more and more organisations adopting AI as part of their operations, a new layer of data risk has begun to emerge. 

In the recent episode of The Security Strategist Podcast, guest Gidi Cohen, CEO and Co-Founder of Bonfy.AI, sat down with host Richard Stiennon, Chief Research Analyst at IT Harvest. They discussed the reasons traditional data loss prevention (DLP) systems fail. Cohen stressed that understanding data context is now crucial for securing AI-driven enterprises.

The rise of generative AI, from chatbots to embedded assistants in SaaS platforms, has created a complex web of data interactions that many organisations do not fully grasp. Cohen argues that this new reality has made legacy DLP technologies completely irrelevant.

“Even before generative AI, DLP never really worked well,” he told Stiennon. “It relied on static classification and outdated detection models that created noise and false positives. Now, with dynamic content generated and shared instantly — and humans often out of the loop — those tools can’t keep up.”

While “shadow AI” applications have gained much attention, Cohen believes the larger threat lies in the trusted tools organisations already use. “We’re using Microsoft 365, Google Workspace, Salesforce — all of which now embed AI models,” the Bonfy CEO explains. “They process vast amounts of sensitive data every day. Yet most companies have no control or visibility over how that data is accessed, transformed, or shared.”

This lack of visibility creates a perfect storm for data exposure. “You might use an LLM to summarise a customer meeting, which is fine,” Cohen says. “But if that summary is later shared with the wrong client or synced with another app, you’ve just leaked confidential information — and no one will even notice.”

The main issue, he adds, isn’t about whether AI vendors misuse data. “The model itself isn’t the main problem. It’s what happens afterwards — how the data and outputs move through the organisation.”

Cohen’s solution to this growing complexity is what he calls a context-driven, multichannel architecture. Such a way perceives data protection as an ecosystem rather than a single checkpoint.

“The flows are too complex for simple guardrails,” he explains. “You can’t just block uploads of credit card numbers and call it a day. You need to understand the context — who’s sharing the information, through what channel, for what purpose, and whether it’s leaving the organisation.”

Bonfy’s approach looks across multiple communication layers — from email and file sharing to APIs, AI agents, and web traffic. They create a complete view of how information moves. Cohen says it’s essential for spotting risky behaviour, whether it comes from a careless employee or an autonomous AI agent working in the background.

As organisations start using multimodal AI — incorporating text, images, audio, and video — this overall visibility becomes even more important. Browser extensions or regex-based filters, he notes, simply won’t catch everything. “An AI agent isn’t using a browser. It’s running somewhere on your network, processing sensitive data on its own. You need a system that can detect that.”

Alluding to turning points in cybersecurity, Cohen explained: “What happened with firewalls 20 years ago or endpoint protection 15 years ago is happening again with data security. We’re entering a new generation.”

“AI is moving faster than defenders. Waiting to figure it out later is not an option. The risks are growing rapidly — and the time to act is now.”

Ultimately, as AI changes how organisations create, share, and use information, traditional data security methods are struggling to keep up. The Bonfy co-founder believes the future belongs to tools that understand context — not just content — and that can protect data wherever and however AI is used.

• The rise of LLMs introduces significant new risks to data security.
• Traditional DLP solutions are inadequate for modern data flows.
• Shadow AI poses hidden risks that organisations often overlook.
• Embedded models in SaaS applications increase data leakage risks.
• Contextual understanding is crucial for effective data protection.
• Organisations must adapt to the dynamic nature of data sharing.
• Guardrails are essential to prevent data misuse and leaks.
• Data security controls need to evolve with technological advancements.
• The integrity of data can be compromised by AI hallucinations.
• Trust in AI tools must be balanced with robust security measures.

• 00:00 Introduction to Cybersecurity Challenges
• 02:47 The Rise of LLMs and Data Risks
• 06:04 Shadow AI and Embedded Models
• 08:59 Guardrails and Data Protection Strategies

Bonfy.AI empowers enterprises to safely adopt GenAI and productivity platforms, such as Microsoft 365 and Copilot, without sacrificing security, compliance, or innovation. Legacy DLP and DSPM is increasingly inadequate against the risks of prompt injection, shadow AI, and over-permissioned access inherited by AI agents. Bonfy.AI’s solutions go beyond static detection, offering a context-driven, multi-channel data security architecture that understands not just content, but the full context of data flows within the modern enterprise.

Bonfy Adaptive Content Security™ (Bonfy ACS™) enables real-time monitoring, automated labeling, and risk-based remediation of AI-generated content across email, file sharing, cloud applications, and enterprise collaboration platforms. Deep integrations with Microsoft 365 ensure full visibility and policy enforcement in critical channels (Mail, SharePoint, Entra, Purview, and Copilot outputs) while adaptive knowledge graphs and behavioral analytics detect and prevent ten times more real-world risk scenarios with far fewer false positives.

Bonfy ensures audit-readiness and regulatory compliance for frameworks such as GDPR, HIPAA, PCI, and CCPA by blocking unauthorized AI access, labeling confidential data in real time, and providing security teams with actionable visibility across all information flows. Organizations in regulated industries, including financial services, healthcare, insurance, and technology, leverage Bonfy.AI to enable secure AI adoption, prevent costly data leaks, and achieve balanced productivity gains without introducing compliance crises or reputational risk. To learn more, visit bonfy.ai and follow us on LinkedIn.

In this episode of The Security Strategist podcast, host Jonathan Care, Lead Analyst at KuppingerCole Analysts, speaks with Sudhir Reddy, the Chief Technology Officer (CTO) of Esper, about how to build trust in ‘Zero Trust.’. They explore this paradox in Zero Trust systems, where human trust is essential for the system to function effectively. 

Reddy emphasises the need for intelligent friction in security measures, allowing for a balance between security and business operations. The conversation also highlights the importance of understanding user needs and building trust within security systems to ensure effective implementation of Zero Trust strategies.

“Security should be a seatbelt, not a straightjacket,” Esper CTO said, describing the nature of zero trust in cybersecurity. For Reddy, zero trust isn’t just about “trust no one.” It’s about verifying everything while still allowing people to do their work.

“Zero Trust is really about verification,” he explains. “But the paradox is that it’s built to create trust among the people using it.” As systems, devices, and AI tools grow, security can’t just mean adding more barriers. “The number of people interacting with systems has increased a lot,” Reddy adds. 

“But if the system doesn’t support the business, people will find a way around it.” That, he says, poses a risk where extremely rigid security could defeat its own purpose.

The Esper CTO explains Intelligent Friction designs systems that adjust security based on the situation. “You want the least friction where there is friction,” he says. “Add friction where it matters most, and make it disappear when it doesn’t.”

Alluding to an example of banking apps, Reddy explains intelligent friction as a simple login for checking balances and extra verification for large transfers. “That’s intelligent design — progressive, contextual, and trusted.”

When asked about the key message for CISOs, CEOs and IT decision-makers, he urges them to “stop measuring adherence to rules.” Instead, “start measuring where people are bypassing them — that’s where your friction is hurting the business.”

At Esper, this approach guides everything from device management to enterprise policy design: security that protects without slowing you down. Discover how Esper is redefining Zero Trust through Intelligent Friction. Learn more at Esper.io.

• Zero Trust is fundamentally about verification at every step.
• The shift to Zero Trust is driven by increased exposure and sophisticated attack vectors.
• Human trust is essential for Zero Trust systems to function effectively.
• Intelligent friction allows for security measures that adapt to user needs.
• Security should not hinder business operations; it should support them.
• CISOs should measure rebellion against security rules, not just adherence.
• Progressive security checks can enhance user trust in systems.
• Cultural change is necessary for effective security implementation.
• Feedback from users is crucial for improving security systems.
• Trust should be the primary driver in designing security systems.

• 00:00 Introduction to Zero Trust and Its Importance
• 02:07 Understanding Zero Trust: Verification at Every Step
• 03:03 The Shift to Zero Trust: Why Now?
• 04:34 The Trust Paradox in Zero Trust Systems
• 06:10 Real-World Examples of Trust Breakdown
• 08:15 Intelligent Friction: A Solution to the Paradox
• 10:48 Implementing Intelligent Friction in Retail
• 12:40 Measuring Security: Moving Beyond Rule Adherence
• 14:40 Balancing Security and Business Velocity
• 16:39 Actionable Insights for CISOs
• 18:51 Key Takeaway: Embracing Trust in Security Systems

Can your organization truly trust every identity, human, machine, and AI?

The traditional security perimeter is no longer a reliable boundary. As enterprises adopt hybrid infrastructures, cloud services, and autonomous AI systems, identity has emerged as the central element of effective cybersecurity.

In the latest episode of The Security Strategist Podcast, Richard Stiennon speaks with StrongDM’s Chief Executive Officer Tim Prendergast about how organizations can secure human users, machines, and agentic AI through identity-based controls.

Both Stiennon and Prendergast believe identity has become the true control plane for modern cybersecurity. While Zero Trust frameworks are widely promoted, they often remain theoretical until grounded in strong identity governance. By continuously verifying and managing every identity—human, machine, and AI—organizations can strengthen access control, reduce the risk of credential theft, and enforce clear operational boundaries across their environments.

As Prendergast explains, “No one wants to go out of business tomorrow, no matter how good their security is. You have to balance the needs of the business, the needs of your user or customer populations, and practical security.

For human users, particularly those with privileged access, identity management must strike a balance between security and productivity. CISOs need visibility into who is accessing critical assets, when, and under what context. StrongDM’s approach emphasizes just-in-time access, ensuring users receive only the permissions they need, precisely when they need them.

Deploying identity-based security requires a strategic, phased approach. Prendergast stresses that security measures must align with business priorities to minimize disruption. By treating users, machines, and AI agents as identities rather than simply devices or services, organizations can enforce dynamic policies, respond to threats more effectively, and maintain compliance in increasingly distributed IT environments.

StrongDM’s approach demonstrates that the future of security lies in identity-first models where humans, machines, and AI agents are governed under the same principles, ensuring that the right identities have the right access at the right time.

• Identity is the new control plane for security.
• Zero Trust is often theoretical; real progress lies in identity-based security.
• Stolen credentials are the primary attack vector.
• A Renaissance in identity security is overdue.
• StrongDM offers just-in-time access for identities.
• Real-time interrogation of entities is crucial for security.
• CISOs need better visibility and resources for identity management.
• Agentic AI presents both risks and opportunities for businesses.
• Implementation of identity security must be strategic and gradual.
• The shift from authentication to authorization is essential for future security.

 Whether you’re a CISO, security leader, or tech enthusiast, this episode shows you how to rethink trust in a hybrid, AI-driven world.

Follow StrongDM for more insights:

• Twitter: @strongdm
• LinkedIn: @strongdm
• Facebook: @strongDM
• YouTube: StrongDM Channel
• Website: www.strongdm.com

00:00 Introduction to Identity-Based Security

03:08 The Role of Identity in Zero Trust

06:45 Understanding Critical Assets and Identity Approaches

09:41 Agentic AI and Its Implications

17:51 Implementation Challenges in Identity Security

21:32 Key Takeaways for CISOs

Founded in 2015, StrongDM helps organizations manage and audit access to databases, servers, clusters, and web applications. Trusted by technical teams worldwide, our platform is secure by design, operationally effective, and easy to use. With a 98 per cent customer retention rate, we turn customers into lifelong fans. Our mission-driven values ensure we stay true to helping organizations simplify access management while keeping security uncompromised.

In today’s cybersecurity industry, Managed Service Providers (MSPs) who do not adapt risk falling behind. 

In the recent episode of The Security Strategist podcast, host Richard Stiennon, Chief Research Analyst at IT-Harvest, talks with Stefanie Hammond, Head Nerd at N-able, and Jim Waggoner, Vice President of Product Management at N-able. They discuss how MSPs can tackle rising threats, bridge the talent gap, and maintain profitability in a quickly evolving market.

The speakers particularly explore the critical need for MSPs to adopt Managed Detection and Response (MDR) services, the importance of internal security investments, and how AI can enhance efficiency. The conversation also touches on compliance challenges and future trends in pricing strategies for MSPs, emphasising the need for continuous adaptation in a rapidly changing threat environment.

When Stiennon asked, “How quickly must an MSP change their entire model to a managed detection and response offering to stay competitive?” Hammond's answer was straightforward: “If an MSP hasn’t done that yet, I don’t know how much longer they can wait.” 

This sets the stage for the podcast.

For MSPs serving clients in tightly regulated fields like finance, healthcare, government, or education, Managed Detection and Response (MDR) is a necessity.

“Organisations in those sectors face a greater risk,” says Hammond. “Managed Service Providers (MSPs) need to incorporate MDR into their security offerings and make it standard for their customers to stay competitive.”

However, Hammond cautions against selling MDR as a standalone solution.“We shouldn’t sell any security tools as a separate service.” Instead, she suggests packaging MDR with other prevention, detection, and recovery options—like backup and data protection—to create a layered cybersecurity package.

Agreeing, Waggoner steps in and describes this as a natural growth process for MSPs: “It becomes a maturity lifecycle. You start by managing hardware and software, move on to daily security, and eventually cover full detection and response. If MSPs don’t want to develop that in-house, N-able can assist—we can co-manage it or handle it for them as they grow.”

The speakers also talked about howtalked how AI and automation are changing cybersecurity, not just for spotting threats but also for improving operations and driving sales. “We automatically handle 90 per cent of security alerts using AI,” expressed Waggoner. 

“If you’re not automating, you’re falling behind,” the Vice President of Product Management at N-able added.

For Hammond, AI is equally beneficial in marketing and communication. She recommends MSPs not to manage sales and marketing on their own but to use AI to support themselves. 

Both experts agree that compliance, identity protection, and education are essential parts of a resilient security framework. “It always comes down to identity,” Waggoner emphasises. “Use unique logins, change passwords regularly, and set up MFA—those basics prevent most attacks.”

As for the future of MSPs, Hammond envisions a shift beyond just technology.

“Don’t stick with the status quo. The market keeps evolving, and if you fail to update your pricing, services, and messaging, you’ll risk becoming obsolete within five years.”

Listen to the full episode to discover how N-able’s experts are assisting MSPs in reshaping their business models, adopting MDR, and turning security challenges into new opportunities. 

Stream now on your favourite podcast platform or visit n-able.com.

• MDR is essential for MSPs in regulated industries.
• MSPs must adopt a proactive approach to security.
• Identity management is crucial to prevent breaches.
• AI can significantly improve operational efficiency.
• Compliance should be viewed as a revenue opportunity.
• MSPs need to evolve their pricing strategies.
• Security awareness training is vital for employees.
• The threat landscape is constantly changing.
• MSPs should focus on value-based pricing models.
• Continuous learning and adaptation are key for MSP success.

• 00:00 Introduction to Managed Service Providers (MSPs) and Cybersecurity
• 05:55 The Importance of Managed Detection and Response (MDR)
• 12:10 Internal Security Investments for MSPs
• 14:55 Developing an AI Strategy for Efficiency
• 19:59 Navigating Compliance Challenges
• 25:01 Future Trends in Cybersecurity and MSP Pricing Strategies
• 29:01 Key Takeaways for CIOs and CTOs

"You have to think about how the online world really operates and how we make sure that data is secure. How can we trust each other in the digital world?" Robert Rogenmoser, the CEO of Securosys, asks. The answer is "encryption and digital signature."

According to Robert Rogenmoser, the CEO of Securosys, storing keys insecurely creates immediate risk. This makes it crucial to maintain strong key security. "If it's just in a software system, you can easily get hacked. If I have your encryption key, I can read your data. If I have your Bitcoin keys, I can spend your money,” says Rogenmoser.

In the recent episode of The Security Strategist podcast, host Richard Stiennon, Chief Research Analyst at IT-Harvest, speaks to Robert Rogenmoser, the CEO of Securosys, about safeguarding the digital world with cryptographic keys. Rogenmoser puts up a case to rally Hardware Security Modules (HSMs) as the best solution for this critical challenge.

In addition to discussing how hardware security modules (HSMs) protect encryption keys, they also talk about the evolution of HSMs, their applications in financial services, the implications of post-quantum cryptography, and the integration of AI in security practices. 

The conversation stresses the importance of key management and the need for organisations to adapt to emerging technologies while ensuring data security.

In order to mitigate the cybersecurity risks, the priority is to securely store the keys, control access, and generate impenetrable keys that cannot be easily guessed by cyber criminals. HSMs are the ultimate solution to the key issue, believes Rogenmoser. 

Firms tend to shift their data to the cloud, making it even more essential to secure keys. The main challenge arises when both the data and the keys are managed by the same cloud provider, as this setup can compromise the integrity of key control and raise concerns about data sovereignty. 

However, Securosys approaches this challenge differently. Rogenmoser explains that organisations can keep their data encrypted in the cloud. At the same time, they keep the key somewhere else, where only they have control over it.

Rogenmoser pointed out the company's patented system for multi-authorisation of Bitcoin keys. This system is essential because blockchain transactions are high-stakes and irreversible.

"Crypto custody for bitcoins or any cryptocurrency is a major business for our HSM," he said. Banks that hold large amounts of customer crypto cannot afford a single point of failure. "A blockchain operation is a one-way thing. You sign a transaction, and the money is gone."

The multi-authorisation system addresses this issue by requiring a "quorum" of people to approve each transaction. Rogenmoser explained, "You can say this transaction can only be signed and sent to the blockchain if one out of three compliance officers signs this, plus two out of five traders." 

This approach creates a "more secure system" because "the HSM then checks, do we have a quorum? Did everyone actually sign the same transaction?" Only after verification is "the actual key for the blockchain […] used to sign a transaction and send it to the blockchain."

Looking to the future, Rogenmoser believes HSMs will be vital for securing the growth of artificial intelligence (AI). With "AI and AI agents doing tasks for us, they might modify things or purchase items on our behalf," which requires both authorisation and attestation.

• HSMs are essential for protecting encryption keys.
• The Swiss National Bank was a key client for Securosys.
• Securosys HSMs are used to secure financial transactions worth trillions.
• Cloud-based HSMs offer convenience but require careful key management.
• Post-quantum cryptography is a significant industry transition.
• NIST is developing algorithms resistant to quantum attacks.
• Multi-authorisation systems enhance security in cryptocurrency transactions.
• AI will require new security measures and audit trails.
• Organisations must assess their key management practices.
• Transitioning to post-quantum systems will take time and planning.

• 00:00 Introduction to HSMs and Their Importance
• 03:55 The Role of HSMs in Financial Services
• 08:44 Post-Quantum Cryptography: Preparing for the Future
• 13:30 Multi-Authorisation Systems in Cryptocurrency
• 16:48 AI and the Future of HSMs
• 19:19 Key Takeaways for IT Decision Makers

Securosys SA, based in Zurich, is a global leader in cyber security, encryption and digital identity protection, prioritising data sovereignty. Their Swiss-built Hardware Security Modules (HSM) secure financial markets, serving over half of the Tier 1 banks worldwide. Certified to the highest standards, their on-premises and cloud HSM solutions offer secure key generation, encryption, digital signing, and post-quantum readiness for finance, healthcare, government, and other industries.