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Penetration testing is intended to help organizations identify weaknesses before attackers can exploit them. Once testing ends, findings must be documented, reviewed, formatted, delivered, assigned, tracked, remediated, and eventually retested. In many organizations, each of those steps happens in a different system and depends on a manual handoff. Testers work in one set of tools. Reports are assembled in Word or spreadsheets. Findings are delivered through PDFs. Security teams recreate them in ticketing systems. Engineering teams update remediation status somewhere else. Retesting is coordinated through email or meetings. By the time the right owner receives the information needed to act, days or weeks may have passed. At PlexTrac , we see this as one of the largest operational gaps in modern offensive security: organizations have invested in finding vulnerabilities, but the process surrounding the pentest has not kept pace. The next phase of pentest modernization is removin...

Identity is the attack surface now. Most identity governance and administration (IGA) programs still run on manual certifications, static role models, and quarterly reviews that go stale the day someone signs off on them. That's not a compliance inconvenience for a CISO. It's a structural gap. Attackers don't wait for the next recertification cycle, so identity risk detection can't either. Autonomous identity governance turns IGA from a periodic, human-driven exercise into something that runs continuously, watching real usage, learning what normal looks like, and acting on deviations before they turn into incidents. That autonomy applies across every identity and entitlement placed under governance, continuously reassessing access as usage, roles, and risk signals change. Three things are colliding to force this shift. Identity sprawl across cloud and SaaS environments has grown past what manual reviews can realistically handle, service accounts and non-human identi...

A security leader at a global finance company told us recently that his team discovered three times more AI tools running in their environment than IT had approved. Nobody had smuggled them in. Employees had simply pointed agents at their work, and the agents brought their own tools with them. That conversation is not unusual. It is the conversation. Over the past year, in customer discussions across finance, healthcare, manufacturing, and government, the same four struggles come up so consistently that we have started treating them as the shape of the problem itself. Every company effectively hired a second workforce this year, human workers and agentic workers side by side, and the agentic workers never went through onboarding. No handbook, no scoped credentials, no acceptable-use policy they can actually read. Here is what teams are struggling with, what our research says about why, and what closing each gap actually requires. Struggle one: "I can't tell you what age...

Security is fundamentally about knowing what a system is supposed to do, then catching it when it does something else. For software with deterministic execution paths, that is a tractable problem. For AI agents, it is not. An agent does not follow a fixed code path. It reasons toward a goal, selects tools based on that reasoning, and adapts its next action based on what those tools return. The same input can produce a different sequence of actions depending on context, session history, and what an external tool happened to return. Behavior is the attack surface, and behavior changes. Traditional proxies and AI firewalls were built to inspect content: what a user sent, what a model returned. Intent security asks a different question: is this agent doing what it was built to do, in this context, for this user, right now? Answering that requires building a behavioral baseline for every agent and measuring deviation from it continuously. That is the problem Lasso was built to solve....

Cybersecurity is entering a new phase. It's one where the gap between awareness and operational execution is becoming the industry's biggest challenge. That's what stood out to me most after reviewing the results of the 2026 Bitdefender Cybersecurity Assessment , which found that organizations have never had greater insight into the risks they face, yet turning that understanding into meaningful action remains a persistent challenge. Nowhere is that gap more visible, in my view, than in how organizations handle breach transparency. We surveyed 1,200 IT and cybersecurity professionals across six countries: France, Germany, Italy, Singapore, the United Kingdom, and the United States. Respondents ranged from frontline employees to IT managers to CISOs, all working within organizations with 500 or more employees. A Governance Problem, Not an Attacker Problem One of the most troubling findings in our report is not about attacker behavior. It's about internal respons...

The structural flaw in detection-only security postures runs deeper than tooling choices. Every hour a security team spends triaging runtime alerts is an hour not spent governing what entered the pipeline in the first place. And in modern CI/CD environments, that means the handful of alerts that represent genuine software supply chain compromise arrive only after the malicious dependency has already executed its payload, exfiltrated credentials, or established persistence inside the environment. The industry built an entire market category on that backwards logic, and enterprises are now paying for it in breach costs, developer burnout, and regulatory exposure that carries personal liability for the security leaders whose names appear on the program. The shift that actually reduces risk is not better monitoring at the end of the pipeline; it is governing the point of ingestion before code ever enters your lifecycle, which is a fundamentally different problem requiring a fundamental...

New Bitdefender research reveals that 97.7% of respondents now use endpoint detection and response (EDR). That number might seem high compared to commonly accepted market penetration estimates, particularly for mid-market organizations. But it is further confirmation that the vast majority of businesses have already upgraded their endpoint protection. This is hardly surprising. The conversation in enterprise security is no longer just about blocking malware or stopping known threats. It is about "proving" that an organization can detect, investigate, and respond to modern attacks before they escalate into operational disruption, financial loss, or reputational damage. This shift was driven by a new reality: endpoint protection alone is no longer enough. The laggards, typically mid-market organizations with lean IT and security teams, are now realizing this. Threat actors are AI-enabled, more evasive, and increasingly successful at bypassing traditional defenses. At the...

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...