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Employees are increasingly using personal AI tools, AI-powered extensions, and emerging agentic browsers to accelerate their work. But unlike sanctioned AI platforms, these tools operate inside the browser runtime, where neither CASBs, SWGs, EDRs, nor DLP solutions have visibility. This has quietly turned the browser into an unmanaged AI execution environment, giving way to a new threat known as shadow AI. Shadow AI isn't just the latest buzzword; it's a serious risk that leaves organizations vulnerable to data loss, cyberattacks, compliance violations, and more.  What is Shadow AI? Shadow AI refers to GenAI-powered tools, browser extensions, and browsers that workers use on their own, without any company vetting or guidance. Different from shadow IT, where unsanctioned apps or devices slip through the cracks, shadow AI lives directly in the browser.  For example, employees might use their personal Claude accounts to work with sensitive company data or work on important pr...

Insider threats are rising in both number and cost, forcing security teams to seek stronger cybersecurity solutions. At the same time, IT teams face more frequent audits and more complex data security requirements. Add to this a distributed workforce and third-party contractors, and it's clear why managing privileged access and monitoring user activity is so challenging.  Modern cybersecurity solutions must offer streamlined access management, complete oversight of user activity within your network, and a privacy-first approach to monitoring. This article offers practical tips on enhancing your cybersecurity strategy by addressing these three pillars. We'll also explore how Syteca's new release can help security leaders protect sensitive data, secure access, and improve audit readiness without IT overhead.  Monitoring User Activity while Preserving Their Privacy Keeping a close watch on user actions is critical for insider threat defense, but it raises a dilemma: "...

The proliferation of AI agents in the enterprise has moved from theoretical to practical at a remarkable pace. These agents, whether developed internally or licensed, are increasingly integrated into core business workflows. While they promise substantial gains in automation and productivity, they also introduce a new and complex class of security risks that demand immediate attention.  The core challenge is not whether to adopt AI agents, but how to govern them effectively. A disciplined approach to balancing innovation with security is essential for any organization looking to leverage AI without exposing itself to unacceptable risk.  Recent research highlights the urgency of this issue. A comprehensive study found that 82% of companies are already using AI agents, with 53% acknowledging they access sensitive information daily . This rapid adoption, often occurring without adequate oversight, creates significant vulnerabilities. The imperative is clear: organizations must...

For nearly two decades, managed-security models have defined how most organizations handle detection and response. Faced with alert overload, chronic staffing shortages, and the high cost of 24/7 coverage, many teams turned to Managed Security Service Providers (MSSPs) and later to Managed Detection and Response (MDR) vendors to fill the gap. Beyond staffing and capacity, many also lacked in-house expertise in building detection systems. It was a rational choice. MSSPs and MDRs provided 24/7 monitoring, experienced analysts, and predictable coverage. They gave companies without an in-house SOC a viable way to maintain security coverage in an increasingly complex threat landscape. But the ground has shifted. AI-driven SOC platforms are now automating large parts of what human analysts once did: triaging alerts, correlating signals, enriching incidents, and recommending or even executing responses. That raises a simple but profound question: what happens to the managed-security m...

CISOs know their field. They understand the threat landscape. They understand how to build a strong and cost-effective security stack. They understand how to staff out their organization. They understand the intricacies of compliance. They understand what it takes to reduce risk. Yet one question comes up again and again in our conversations with these security leaders: how do I make the impact of risk clear to business decision-makers? Boards want to hear how risk affects revenue, governance, and growth. They have a limited attention span for lists of vulnerabilities or technical details. When the story gets too technical, even urgent initiatives lose traction and fail to get funded. CISOs need to translate technical issues into terms the board understands. Doing so builds trust, garners support and shows how security decisions connect directly to long-term growth. It was the urgent need to bridge the CISO-Board communication gap that led us to create a new paradigm in CISO continu...

Artificial Intelligence (AI) has served as a great resource for cyber defenders by enabling real-time detection and response through advanced pattern recognition and predictive analysis that traditional methods weren't able to achieve. However, AI has recently become a dangerous and widely available enabler for attackers to leverage. CISOs now face adversaries who easily scale large-scale cyberattacks like spear-phishing and polymorphic malware at machine speed.  This article examines the rising AI-driven cyberthreat landscape and presents the browser, the enterprises' new endpoint, as the most strategic control plane for defense. By adopting a Secure Enterprise Browser (SEB) into the security stack, enterprises can reduce their attack surface, contain incidents at scale, and future-proof themselves against these advanced attacks.  Why Traditional Defenses Struggle Against AI  Most organizations have robust defense in place against cyberattacks, such as firewalls, EDR...

As hybrid and multi-cloud environments become the standard, organizations are under growing pressure to deliver scalable and secure remote access. Traditionally, Virtual Private Networks (VPNs) have been the go-to solution for connecting remote users to corporate networks. While VPNs have been essential for remote access, they were originally designed for simpler, perimeter-based security models. Organizations that rely solely on VPNs face significant limitations, including weak access control, increased risk of lateral movement and poor visibility. Continue reading to learn the limitations of VPN-based access and how KeeperPAM® provides a strong, modern alternative for securing remote access. Why VPNs are no longer enough Although VPNs have been used to enable remote access within organizations, the limitations of VPNs are becoming increasingly clear as IT environments span across multiple on-premises, hybrid and remote systems. Relying on VPN-based access alone can actually make ...

Automated tools give you visibility. Adversarial testing gives you clarity. In Salesforce environments, you need both. The Problem with Checkbox Security in a Platform-Centric World Salesforce has become more than just a CRM—it's the backbone of how many organizations operate. It holds customer data, governs workflows, drives revenue, and connects to dozens of internal and third-party systems. But that complexity is exactly what makes it hard to secure. And too often, security teams rely solely on generic scans or scheduled audits that were never designed to handle the nuance of Salesforce's layered permissions, custom logic, and evolving integrations. The result? A lot of surface-level findings—and a lot of assumptions about what those findings actually mean. Automation Is Essential—But It's Only One Layer There's no question that modern scanning tools play a vital role in Salesforce security. The right platforms can surface deeply nested permissions, cross-object access paths,...

Generative AI has quietly become a part of the SaaS ecosystem that businesses use every day. Platforms like Zoom, Slack, Microsoft 365, and Salesforce now have AI assistants. You can use these tools to do things like write summaries of meetings or perform routine tasks. A recent  survey found that 95% of U.S. businesses now use generative AI. This is a big increase from last year. But this quick growth of AI features is making security leaders worried. Sensitive information could be leaked or used in the wrong way if there aren't enough controls in place. Shadow AI and Its Far-Reaching Risks When employees use AI apps without the knowledge or approval of IT, it creates shadow AI . This is akin to the shadow IT problem of unsanctioned cloud apps, but now with AI services. The unauthorized use of AI platforms can unknowingly expose organizations to data privacy issues, compliance violations, and even disinformation risks. We're already seeing these risks play out. Samsung engin...