Guest Blog Post

GUEST ESSAY: AI pipelines are shattering network security — most companies haven’t even noticed yet

By Kajal Singh

For the past two decades, enterprise security teams have gotten good at one thing: keeping sensitive data where it belongs.

Related: Leaked secrets no. 1 exposure

Production data stays in production. Test environments get masked or synthetic data. Access is controlled. Ownership is defined. The system, while imperfect, largely works.

Then AI arrived — and that discipline quietly broke.

Not because teams forgot what to do, but because the workflows changed faster than the controls did.

Today, production data routinely flows into AI pipelines with far less scrutiny than it ever faced in traditional software development. It moves through data lakes, feature stores, training pipelines, evaluation sets, and sometimes third-party platforms. Along the way, the original boundary — the question of whether that data should have left production at all — often disappears.

Comment | Read | May 26th, 2026 | Guest Blog Post | Top Stories

GUEST ESSAY: Executives trust AI security even as security teams confront blind spots, new risks

By Daniel Bardenstein

In our recent report, Beyond the Black Box, we found a striking gap: 80% of executives believe their organizations have strong security coverage for AI systems. Only about 40% of AppSec practitioners agree.

Related: AI moves mainstream

That’s not just a perception problem. It’s a visibility problem.

The numbers back that up. Sixty-three percent of organizations report discovering “shadow AI” inside their environments — tools, models, or integrations adopted without formal oversight.

Executives tend to measure security by the presence of programs, policies, and governance structures. Practitioners measure it by what they can actually see, inspect, and test. When it comes to AI systems, those two measures rarely land on the same number.

Comment | Read | March 20th, 2026 | Guest Blog Post | Top Stories

GUEST ESSAY: The hidden risks lurking beneath legal AI — permission sprawl, governance drift

By Ariel Perez

In many law firms today, leadership believes their data is secure. Policies are documented, annual reviews are completed, and vendor questionnaires are answered with confidence. On paper, the safeguards look strong.

Related: The cost of law firm breaches

Yet in practice, few firms have a clear, current view of how their systems actually behave. That gap between written policy and operational reality has existed for years. The rapid adoption of AI tools is now bringing it into sharp focus.

Research assistants, document review platforms, and productivity copilots are arriving quickly in legal environments. They promise efficiency, and in many cases they deliver it. But these tools are often introduced into data environments where permissions have accumulated without review, access rules are poorly understood, and no one can clearly explain who has access to what, or why. Over time, that drift creates real exposure in how work is performed.

GUEST ESSAY: Observability is no longer passive — it’s now a real-time driver of security action

By Dean Lewis and Anna Kapuscinska

Modern enterprises generate a steady stream of telemetry from infrastructure and applications.

This data spans infrastructure layers, workloads, and communication patterns across hybrid and multi-cloud environments.

Traditionally, performance-focused engineering teams have relied on one set of observability tools, while security teams have used another. The result is a divide in tooling and perspective, where performance optimization and threat detection are treated as separate disciplines.

Kernel-level programmability is beginning to bridge that gap. A technology called eBPF now makes it possible to capture security-relevant signals directly from inside the operating system, in real time. With this, observability becomes more than a tool for performance tuning; it becomes a frontline source of security intelligence.

GUEST ESSAY: Why cyber defenses need a framework — and a clearer map of boundaries

By Jed Salazar

In the early years of enterprise computing, isolation had a clear home in the networking domain.

Network isolation meant a strong perimeter that kept internal traffic separate from the external world. Firewalls, VLANs, and DMZs were the primary tools. The edge was guarded, and anything inside the walls was assumed safe.

Related: The state of cloud security

That model broke down as applications shifted from monoliths on dedicated servers to microservices spread across hybrid clouds. Multitenancy became the default, and AI workloads began sharing GPUs. Attackers stopped focusing only on the front door and instead moved laterally through weak internal boundaries and under-protected runtime environments.

GUEST ESSAY: The AI illusion: Don’t be fooled, innovation without guardrails is just risk–at scale

By Naómi L Oosthuizen

Artificial intelligence is changing everything – from how we search for answers to how we decide who gets hired, flagged, diagnosed, or denied.

Related: Does AI take your data?

It offers speed and precision at unprecedented scale. But without intention, progress often leaves behind a trail of invisible harm. We are moving fast. Too fast. And in our excitement, we’ve stopped asking the most important question of all: at what cost?

AI’s influence is already everywhere, even when we don’t see it. It hides behind dashboards, recommendation engines, productivity scores, and predictive analytics. It tells us what’s trending, what’s risky, and what to do next. But just because it’s quiet doesn’t mean it’s safe. These tools are shaping human lives in deeply personal ways, and too often, they’re doing it invisibly and without accountability.

GUEST ESSAY: Cybercrime for hire: small businesses are the new bullseye of the Dark Web

By Doni Brass

Small businesses make up 90% of all companies worldwide and account for half of global GDP. Yet despite their importance, many lack the cybersecurity expertise and resources to fend off a rising tide of digital threats.

Rich in sensitive data and often connected to larger supply chains, small businesses have become prime targets for attackers. And thanks to an explosion of inexpensive “cybercrime-as-a-service” offerings on the dark web, launching an attack is easier — and cheaper — than ever.

Cybercrime industrialized

The dark web has become a marketplace where bad actors can buy tools and access with the ease of shopping for software. Many of these services exploit unpatched software flaws — some disclosed years ago — that remain active in business environments.

Recent Guardz research shows that more than 15% of the tools advertised on dark web forums target vulnerabilities like EternalBlue,

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