Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Credentialed Scanning: The Accuracy Upgrade that Comes with a Loaded Gun

Credentialed scanning (also called authenticated vulnerability scanning) is a vulnerability scan that logs into the target system with valid credentials and inspects it from the inside. Instead of poking at open ports and guessing versions from banners, a credentialed vulnerability scan reads the installed package list, patch level, registry keys, and configuration files directly, the same way an administrator would. The payoff is accuracy.

Best Cloud Penetration Testing Providers in 2026

Most cloud breaches begin with a configuration error the customer made. Gartner projected that through 2025, 99% of cloud security failures would be the customer’s responsibility, caused by misconfigured identity and access management, exposed storage, and over-permissioned services. Cloud penetration testing is the simulation of real-world attacks against cloud infrastructure on AWS, Azure, and GCP to find those exploitable gaps before an attacker does.

The Hugging Face Incident Proved the Real AI Risk Is in the Action Layer

Last week, an AI system crossed a line many still considered theoretical. During an internal cybersecurity evaluation, OpenAI tested a combination of models, including GPT-5.6 Sol and a more capable pre-release model, on ExploitGym, a benchmark that measures whether agents can turn software vulnerabilities into working exploits. The models were run with reduced cyber refusals and without the production classifiers normally used to prevent high-risk cyber activity.

AI Data Pipeline Security: How to Protect Personal Data Before, During, and After Model Use

Artificial intelligence is reshaping how enterprises process information, but it is also redefining where sensitive data is exposed. Every prompt, retrieval request, API call, and AI-generated response creates another opportunity for personal or confidential information to move beyond its intended boundaries.

Runtime Security for LLM Applications: How to Monitor Prompts, Context, Tools, and Outputs

Large language models are becoming the operational layer behind enterprise AI, powering intelligent assistants, automated workflows, and AI agents that interact with sensitive business systems. But as LLMs process confidential prompts, retrieve enterprise context, and execute connected actions, every runtime interaction introduces new security risks.

The Open-Source Paradox: Navigating the New Frontier of AI Supply Chain Risk

The recent developments surrounding vulnerabilities in major AI repositories like Hugging Face serve as a critical wake-up call for the cybersecurity community. As we accelerate toward an agentic future, the platforms we rely on for innovation are increasingly becoming the primary vectors for systemic risk.

Introducing The Hybrid Nudge Experience: Outbound Email Security Built for Your Risk Appetite

When it comes to outbound email security, every organization operates under different operational constraints and security requirements. Some security teams prioritize in-app nudges and coaching to catch risky behavior the moment an email is drafted. Others want to avoid friction, particularly for executives, sales teams or mobile-first employees who rarely interact with desktop add-ins.

Why Most Automation Projects Stall Before They Reach ROI

Automation has a credibility problem hiding behind its success stories. For every celebrated deployment, there's a quieter statistic: analysts and consultancies have repeatedly found that a large share of automation initiatives - by some estimates a third to half of early RPA programs - fail to scale or deliver their expected return. The technology usually works; the project is what breaks.