Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

What nearly 10,000 developer environments reveal about agentic development risk

For years, application security teams have focused on a familiar set of questions: Is the code secure? Are the dependencies vulnerable? Is the build pipeline protected? Are issues being caught before they reach production? Agentic development adds a new question: What systems, tools, instructions, and permissions helped produce this code? AI coding agents are no longer just suggesting snippets or completing lines of code.

Announcing Agentic Development Security (ADS)

Today, we're announcing Agentic Development Security (ADS), a new Evo solution designed for securing AI-driven software development. AI agents are now active participants in the software development process, selecting tools, executing actions across systems, and generating production-ready code at machine speed.

The New Security Control Point: Governing AI Agents Inside the Execution Loop

As organizations adopt AI agents to build software, security teams face a new challenge: risk is no longer introduced only through the code that gets produced. It emerges continuously through the tools agents use, the actions they take, and the code they generate. This is the problem Evo Agentic Development Security (ADS) was designed to solve. ADS secures all three layers of the agentic development system—what agents use, what they do, and what they generate.

CVE-2026-42271: Unauthenticated RCE in LiteLLM AI Gateway

LiteLLM, a widely deployed open-source AI gateway, is affected by a critical exploit chain that allows unauthenticated attackers to execute arbitrary commands on vulnerable hosts. CISA added CVE-2026-42271 to its Known Exploited Vulnerabilities (KEV) catalog on June 9, 2026, confirming active exploitation in the wild. The Qilin ransomware group has been linked to exploitation activity. What makes this especially dangerous is the chain: CVE-2026-42271 on its own required a valid API key.

How Modern POS Platforms Help Retailers Reduce Operational Risk

Ask a store owner to name their biggest operational risk, and you'll usually hear about the dramatic stuff. A break-in. A card-skimming scam. The walk-in cooler that quits at 2 a.m. on a holiday weekend. Those things happen, and they hurt. But they're rarely what bleeds a retail business dry.

IoT Security vs Traditional Endpoint Security: What Changes?

IoT security changes the way cybersecurity teams think about assets, identity, updates, and monitoring. A laptop, server, or phone usually supports endpoint agents and user-based controls, while an IoT device often runs quietly with limited interfaces, fixed firmware, and a specific operational task.

How Cuffless Blood Pressure Monitors Are Redefining Patient Privacy in Digital Health

Healthcare technology is undergoing a fundamental shift in how we monitor vital signs. Cuffless blood pressure monitors represent one of the most significant advances in this transformation-not just for their convenience, but for how they're addressing one of modern medicine's most pressing concerns: patient data privacy. As health monitoring becomes increasingly digital and continuous, the question of who controls our most intimate health information has never been more critical.

The Hidden NetSuite Delete-All-Data Risk: How to Recover Faster and Protect Historical Records

Enterprise Resource Planning (ERP) platforms have become the operational backbone of modern organizations. Finance teams rely on them for reporting and compliance, operations teams depend on them for workflows, and executives use them to make business-critical decisions. Because of this reliance, most organizations assume their ERP data is always recoverable. However, one often-overlooked risk in cloud ERP environments is the possibility of large-scale data deletion, accidental overwrites, failed imports, or configuration changes that impact historical records.

Implementing AI Governance to Identify and Mitigate Critical AI Risks

Artificial intelligence (AI) is transforming businesses worldwide, offering powerful tools to automate, analyze, and innovate. Yet, with this power comes significant risk. Organizations must implement AI governance frameworks that map, measure, and manage AI risks continuously. ‍ This article explains how effective AI governance helps prioritize risks aligned with business goals, enabling companies to mitigate threats before they escalate.