Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

AI vs Security Architects - Augmentation, Not Replacement

Are AI systems replacing security roles? Maybe not the way most people assume. AI isn't eliminating architects — it's augmenting them. Architects sit at the strategic layer: influence, prioritization, long-term posture. AI’s power isn’t replacing that judgment — it’s continuously surfacing what matters, validating configurations, and helping teams scale impact without hiring “more architects.” "If I say something should be done, I need a way to know whether it was done correctly — and continuously.".

We Built Protecto SaaS Because $50K/Month Privacy Tools Didn't Make Sense for Startups

Six months ago, we encountered a problem with no clear solution. We were building an AI agent inside a startup. When customer conversations were flowing in, we started looking for privacy tools that could keep up. Everything we found fell into one of three buckets: Somewhere in the middle of this, we caught ourselves looking for a simple, affordable way to mask data before it hits AI systems.

LLMs, Quantum Computing, and the Top Challenges for CISOs in 2026

Cybersecurity in 2026 is entering its most transformative and volatile phase yet. For CISOs, the landscape is no longer defined only by web, network, and cloud threats. Instead, attackers now target AI/LLM systems, APIs, identity platforms, SaaS ecosystems and supply chains. The surge in attacks across applications, APIs, and GenAI systems indicates that adversaries are scaling faster, using automation, AI-assisted exploitation, and new social engineering vectors.

Your Browser is Becoming an Agent. Zenity Keeps It From Becoming a Threat.

Agentic browsers are quickly becoming part of everyday work. Tools like ATLAS, Comet, and Dia can read web content, navigate SaaS tools, interpret instructions, and act on behalf of a user. They promise faster execution and higher productivity but they also introduce new risks that traditional security tools are not designed to see. As these browser-based agents spread across both managed and unmanaged devices, the enterprise attack surface grows in ways that most teams can’t quantify.

SOAR in the AI era: How SAP uses intelligent workflows to build an AI SOC

SOAR was created to help security teams work faster and more consistently by automating and orchestrating core security operations. It has always had to adapt to new and evolving technologies, but our current AI era has brought about a turning point. As cloud environments scale, manual playbooks can’t keep up. Now, it’s not enough to automate. We need systems that can understand the context they’re running in and adapt accordingly.

The New AppSec Reality: AI Anxiety, Silent Flaws, and Supply Chains

We recently published a series of polls across our social channels to get a pulse on some of today’s application security concerns with AI. These recent conversations with our community reveal a clear and urgent shift in the application security landscape. Results show that while established challenges like software supply chain security remain top of mind, the rapid pace of AI has created a new center of gravity for anxiety.

Prompt Injection Attacks in LLMs: Complete Guide for 2026

In February 2023, a Stanford University student conducted a study that turned into one of the most widely followed security tests in AI history. Kevin Liu performed a simple prompt-injection attack, tricking Microsoft Bing Chat into disclosing its internal codename, Sydney, and exposing the entire list of its system prompts. The attack utilized no high-end toolkit, no zero-day, and no privileges, only specially crafted natural language.

AI in IAM: How much value is it really providing?

Let’s face it, AI is everywhere now. It has moved from novelty to necessity, reshaping the way we work, make decisions and secure our organizations. It guides how we plan trips, shop for essentials and discover information – but one of its most profound impacts is happening across enterprise environments.

Best Practices for Implementing Data Tokenization

Data is no longer confined to a few clean relational systems. It now flows through microservices, data lakes, event streams, vector databases, and LLM pipelines. Sensitive information spreads quickly, and once it reaches ungoverned surfaces—logs, analytics exports, embeddings—it becomes extremely painful to unwind. Tokenization is one of the few controls that can both minimize data exposure and preserve business functionality.