Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Agentic AI Visibility and Risk Scoring: What Cyberhaven Sees That Others Miss | (Part 3 of 4)

Knowing an AI tool exists is not the same as knowing what it did with your data. This is Part 3 of Cyberhaven's 4-part AI Security product launch series, covering Agentic AI Visibility and AI Risk IQ, Cyberhaven's evidence-based risk scoring system for every AI app and agent in your environment.

Why AI Projects Stall and How CIOs Can Respond

Across enterprises, a familiar pattern is emerging. A business unit identifies an AI tool with a clear upside in productivity or revenue. Their proposal moves into procurement. Security raises concerns, and the legal team asks new questions about the tool. Compliance starts hesitating and the momentum slows. Finally, the project stalls. This friction is not due to resistance to innovation. It reflects a deeper structural issue: Most enterprise governance models were not designed for AI.

AI Kill Switch Architecture: How to Stop a Rogue AI Agent

AI agents today are becoming a part and parcel of everyday enterprise operations. They can access databases, trigger workflows, send emails, approve requests, and interact with business systems with very little human involvement. What started as AI assistants is now evolving into autonomous operators capable of making decisions and executing actions at machine speed.

It's Not If Attackers Get In. It's What Happens Next | Insurity CISO Jay Wilson

"Usually it's not a question of if the bad guys get in. It's a question of what happens when they do." Jay Wilson, CISO and CIO at Insurity, and Garrett Hamilton, CEO of Reach, joined Shubhangi Dua on The Security Strategist from EM360Tech to talk about why the controls you already own are where exposure quietly builds up. That's Jay's line, and one every security leader has lived. Defense in depth only holds if every inner layer is configured the way you think it is. The outer door gets the attention. The inner doors are where incidents actually get stopped, or don't.

The Ultimate Guide to API Security in AI Applications

API security is the practice of protecting the interfaces that connect your applications, models, and data from unauthorized access, abuse, and data theft. In AI applications, APIs carry prompts, model responses, customer PII, and agent instructions, which makes them the single most exposed layer of your AI stack. Securing them requires authentication, rate limiting, encryption, and a layer most teams miss: protection of the sensitive data in every API call.

AI Data Exfiltration: Types, Risks, Prevention Strategies

Generative AI has revolutionized productivity — but it has also introduced a massive, often invisible new vulnerability: AI data exfiltration. Whether it’s a well-meaning engineer pasting source code into an LLM for debugging, or a marketer feeding sensitive customer data into a prompt for analysis, your organization’s most valuable intellectual property is likely walking out the virtual front door.

How to Secure AI Agents: 4 Best Practices

Imagine you give an AI agent permission to triage support tickets. A few weeks later, it’s accessing a system no one intended it to reach, putting the data within at risk of exposure or misuse. Nothing dramatic happens at the moment. That’s what makes the risk tricky. AI agents don’t wait for approval the way traditional systems do, and they move faster than the controls you’ve set around them.

7 Agentic AI Security Threats in DevOps That Multiply Your Attack Surface

AI adoption in the DevOps field has been extensive. Developers use agents daily to broaden context, automate coding, prototype, etc., saving time and minimizing the footprint of mundane tasks. But it’s not all about gains. Agentic AI enables and introduces security threats that were unknown just a few years ago. With machine speed and scale, these can impact your corporate repos in a number of highly dangerous ways. The trend is on the rise, including at the level of popular DevOps platforms.

Nightfall's integration with Claude's Compliance API is now live

What this milestone means for enterprise AI security - and why we built it. AI adoption inside the enterprise didn't slow down and wait for security to catch up. It accelerated. And nowhere is that more visible than in the rapid deployment of large language models like Claude across enterprise workflows. Customer support teams use it to summarize tickets. Legal teams use it to review contracts. Engineers use it to write and review code. Finance teams use it to draft reports.