Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Shadow AI: The New Frontier of Shadow IT

As a CISO advisor, I am observing a familiar pattern gaining a new, critical dimension. What we historically identified as "Shadow IT", the use of unapproved SaaS and tools, is rapidly evolving into "Shadow AI." Employees are increasingly leveraging AI bots for drafting, analysis, code generation and strategic decision-making.

We built an AI PR reviewer. The hard part was teaching it to say nothing.

Most AI code review tools fail the same way. They work, in the sense that comments appear on the pull request. Then you read the comments and they are 80% “consider extracting this into a helper”, “missing test coverage”, “this variable name could be clearer”, and within a couple of weeks everyone has learned to scroll past anything the bot wrote. These are not false positives. They are true and irrelevant, which costs the same attention and is harder to argue with.

AI can think. AI can act. Secure the entire AI workflow.

Securing AI systems today means securing the whole AI process, from access, to prompt, to action. Explore A10's AI security offering, which ties the capabilities of AI Firewall, MCP discovery/protection, AI gateway, and ThreatX, all together into one cohesive end-to-end AI security solution.

A Prompt Is Not a Boundary: Lessons From the AI Eval Incidents

Three organizations had their production systems compromised by an AI model in April, and found out in late July when the model's developer called them. None of them had detected the activity. One was a security company whose own package scanner was the entry point. ‍ Anthropic published that account on July 30, nine days after OpenAI disclosed a related incident of its own.

Is your AI system secure enough? MITRE ATLAS Is Now Law.

For the first time anywhere, the MITRE ATLAS framework and the OWASP Top 10 for LLM applications are written into binding law. Article 15 names data poisoning, model poisoning, adversarial examples, model evasion and confidentiality attacks as threat classes you must have technical measures against—and must be able to evidence to a regulator. The question is no longer whether you have thought about AI security. It is whether you can prove your AI system holds.

Coding Agent Risk for CISOs: Blast Radius, Governance, and Where to Start

Claude Code, Cursor, GitHub Copilot, and Gemini CLI are running on developer machines across your enterprise right now. They're browsing the web, writing to your filesystem, committing code to your repositories, and calling external APIs under the identity of your engineers. Most security teams have no visibility into any of it. This isn't a future problem.

Black Hat Proved AI Agents Are Already the Attack Surface

Enterprise AI agents stopped being a pilot project a while ago. They read email, touch source code, operate browsers, and increasingly make decisions inside production systems, which means the security model built for chatbots and prompts no longer covers what is actually happening inside the enterprise. Black Hat USA 2026 turned out to be the week that gap became impossible to ignore.

The Agent Baseline: 35 controls, but where should you start?

Two weeks ago, we published the Agent Baseline alongside Docker and Keycard. In it, we describe six security outcomes, 35 controls, and an open reference architecture for running AI agents at the enterprise level. Last week, we stress-tested it: we took it to a panel at Black Hat and spent about one hour being asked hard questions about it. Play Video: Snyk x Docker x Keycard | Agent Baseline Panel @ Black Hat 2026 The most useful question came from someone who had actually already read it.

AI Agents & Cybersecurity: Why AI Agents Are New Trust Boundaries | A10 Networks

AI Agents & Cybersecurity: Why AI Agents Are New Trust Boundaries AI agents are more than just another virtual machine—they are autonomous entities delegated with power, introducing entirely new trust boundaries into modern network architectures. In this discussion, A10's Arjoyita Roy and Jamison Utter discuss why traditional security controls fall short when managing AI agents and why cybersecurity professionals must design new security perimeters and controls around these evolving AI workloads.