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AI-driven vulnerability discovery is no longer a research project. Claude Mythos proved that. In a single sweep, it uncovered thousands of vulnerabilities in software we use every day, generated working exploits, and exposed bugs that had survived decades of human review. Other AI models are rapidly catching up, and we've entered into an entirely new operating environment for cybersecurity. The industry is treating this as a turning point, and it is. But not for the reason most people might think. The Real Problem Was Never Finding Vulnerabilities Most of the conversation around AI security focuses on discovery: AI can now identify vulnerabilities faster than human teams ever could. That is certainly true, but it also misses the larger operational reality organizations have been struggling with for years. Security teams were already overwhelmed long before AI entered the picture. Vulnerability scanners, fuzzers, and static analysis tools have consistently generated more...

For most managed service providers (MSPs), ransomware recovery is not a problem that affects one client at a time. It is a multitenant, high-pressure scenario where recovery failures impact multiple clients at once. Testing ransomware recovery is not just a technical exercise but a business-critical requirement. The green check of a successful backup job does not guarantee successful ransomware recovery. Attackers today do more than encrypt files. They compromise identity systems, alter configurations, and create persistence mechanisms that survive system restoration. So, a "clean" backup can still reintroduce dormant malware or broken dependencies into your environment. Recovery success depends on whether systems are usable, trusted and operational after restore, not whether data simply exists. Modern ransomware protection and recovery strategies require correlation between security events and backup data. Without that, MSPs are forced into guesswork across multiple cl...

Identity sprawl, agentic AI risk, and the path to NHI governance maturity When security leaders talk about identity risk, the conversation almost always centers on humans: Privileged users, compromised accounts, insider threats. But for most enterprises, the greater risk has already shifted. And it has nothing to do with your employees. Non-human identities (NHIs) — service accounts, API keys, OAuth tokens, SSH keys, RPA bots, cloud workload credentials and AI agents — are the fastest-growing, least-governed attack surface in the modern enterprise. And the industry is beginning to reckon with what that means. $4.88M Global average cost of a data breach — IBM Cost of a Data Breach 2024 The scope of the problem The numbers are striking. Research from Rubrik Zero Labs puts the NHI-to-human identity ratio at 45:1 in the modern enterprise. For cloud-native and DevOps environments, Entro Labs H1 2025 research puts that figure at 144:1.  These identities are not passive: They au...

Higher education institutions operate some of the most complex identity environments of any industry. Universities often struggle to balance open access for learning and research with strong security controls to protect students, faculty, and sensitive institutional data. This contrast creates unique identity security and management challenges that require specialized strategies and tools. A Highly Complex Identity Ecosystem Unlike corporate businesses, the ecosystem that is common at universities requires them to manage a variable and highly diverse population of users. Churn is a constant challenge, with students, faculty, alumni, researchers, contractors, and affiliate colleges and labs, and other contributors enrolling, changing roles or status, tracks or departments, and leaving frequently.  This dynamic ecosystem results in an identity lifecycle that is far more fluid than most corporate environments. "Joiners", or new identities, are created continuously, while "movers a...

As identity-based attacks continue to rise, the most damaging breaches increasingly begin with valid credentials rather than vulnerability exploits. That's why identity resilience will define the maturity of your cybersecurity in 2026.  A unified identity defense layer, combining privileged access management (PAM) with identity threat detection and response (ITDR), is emerging as the foundation of that resilience. This article explores why integrating these capabilities into your security strategy is no longer optional and how, together, they form the backbone of modern organizational security. The shift to identity-centric security Traditional PAM solutions that allow you to safely authenticate users are no longer enough to protect your business against modern threats. Instead of breaking through technical barriers, threat actors are now using compromised credentials to sign in as legitimate users. According to IBM's X-Force 2025 Threat Intelligence Index, identity-driven intr...

AI hype is everywhere. Every security vendor claims their platform is "AI-powered." Dashboards promise automation. Generative AI is positioned as the solution to staffing shortages. For small and mid-sized organizations with lean IT and cybersecurity teams, these messages are understandably compelling. But this leads to a critical question: Can AI realistically strengthen your security program — and is it worth the effort? The Current Reality: Under-Resourced and Overwhelmed Small and midsized organizations face a difficult equation. Threat actors are becoming more sophisticated. Attack surfaces continue to expand. Compliance pressures are rising. Meanwhile, security teams are small — often just a few professionals wearing multiple hats. AI sounds like a relief. In theory, it can accelerate detection, reduce alert fatigue, automate triage, improve response times, and surface hidden threats buried in large volumes of data. But AI is not plug-and-play magic for defenders. For l...

According to research by IBM, organizations use an average of 83 separate security solutions. It is hardly surprising that 52% of security professionals identify complexity as the biggest impediment to effective operations. For IT and security leaders in mid-market organizations, who know they have gaps in security coverage, this challenge can feel particularly difficult to solve. At Bitdefender , we see this challenge play out consistently across mid-market environments. Most organizations have the fundamentals in place, such as Endpoint Protection Platforms (EPP), email filtering, and patch management. However, many are not fully realizing the capabilities of these existing tools. This creates security gaps and, when combined with a lack of preventative exposure management controls, severely limits visibility across attack surfaces. Maximize Your ROI: Exploit Underused Tools Many mid-market organizations already have powerful Endpoint Detection and Response (EDR) in place as part...

Open-source intelligence (OSINT) was once a discipline primarily associated with criminal investigations and national intelligence work. Today, it has become a critical pillar in a wide range of corporate and operational processes from internal investigations and fraud detection to KYC, third-party validation, and due-diligence assessments. However, despite this shift in importance, OSINT is still frequently performed in an ad-hoc manner: how data is collected, how evidence is preserved, and operational security mechanisms often depend on individual habits rather than standardised practice. In many cases, investigations are even conducted directly from managed corporate devices, putting both the integrity of the intelligence operation and the wider enterprise network at unnecessary risk. This lack of standardisation introduces operational, security, and compliance risks that many organisations do not fully recognise until something goes wrong. Operational Risk Glazer is a sandboxed...

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: "...