Cybersecurity Dive

As your organization scales, the identity access management (IAM) difficulties can compound quickly as the environment becomes more distributed and complex, and new security threats continue to evolve. Year after year, industry threat intelligence reports find that compromised credentials remain the number one threat to security, according to the Verizon 2025 Data Breach Investigations Report. The good news? With the right preparation, you can stay ahead of the most common IAM risks.

AI agent gateways like OpenClaw feel like a portal to a future that, even a few months ago, felt impossibly distant. That future is genuinely transformative, but it’s also scary in some very specific ways. OpenClaw works due to a kind of Faustian bargain. It is compelling precisely because it has real access to your local machine, your apps, your browser sessions, your files, and often long-term memory.

Cybercriminals continue to exploit human behavior as a gateway into organizations, despite strengthened detection and defense tools. Security infrastructure has hardened, but stealing valid credentials and logging in is often easier than breaking through perimeter defenses. This is not merely a matter of employee oversight; rather, the rapid expansion of accounts, access permissions, and predictable workflows introduces exploitable vulnerabilities.

AI agents are no longer theoretical. They’re executing database queries, modifying configurations, and managing workflows based on natural language instructions – often with minimal governance oversight. The challenge isn’t just what AI agents can do. It’s establishing the governance frameworks to control how they do it. December 2024 marked a significant shift when the Model Context Protocol (MCP) 2.0 introduced structured control mechanisms that enable governance frameworks for agentic AI.

Congrats—you got the green light to move forward with improving identity access management (IAM). While you realize this is great news for your organization’s security, that initial excitement can quickly turn into unease as you face the next hurdle in your security quest: implementation. According to Cisco Duo’s 2025 State of Identity Security, 82% of financial decision-makers have increased their identity security budget.

Enterprise resilience is failing because organizations still operate security, identity, and recovery as separate functions, while disruptions now span all three at machine speed. As AI accelerates operations and cloud, SaaS, and third-party dependencies multiply, failures no longer remain contained.

The landscape of data sanitization is evolving. With emerging technologies like cryptographic erasure gaining traction alongside traditional physical destruction methods, security leaders face a critical question: which approach should we use and when? The answer isn't either/or, it's both. Organizations that get data sanitization right understand that different scenarios demand different solutions. Here's how to build a risk-based sanitization strategy that uses the right tool for the right job.

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The most secure endpoints are secure by design, equipped from the outset with a purpose-built security platform that integrates deeply with contextual telemetry across the environment. This integrated, security-by-design foundation minimizes vulnerabilities and establishes a resilient defense against AI-powered cyberattacks. For decades, cybersecurity operated on signatures and samples. Antivirus engines scanned files, compared them to known malware, and blocked what looked suspicious.

As AI adoption deepens, security teams face a tricky dilemma: how to move quickly while managing new security, privacy, and data exposure risks. Tines’ Voice of Security 2026 report surveyed over 1,800 security leaders and practitioners to understand how security teams are evolving in the era of AI. The findings show AI governance is now a central priority for 2026. Half of organizations (50%) already have a formalized and active AI policy in place, while another 42% are establishing one.