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By Molly Bauer
Enterprises aren't standardizing on one AI agent platform. Security teams are watching Copilot run alongside ChatGPT Enterprise, homegrown agents built on internal frameworks, and endpoint coding agents like Claude and Codex, often all inside the same organization. Each platform brings its own credentials, tool access, and blind spots, and none of them wait for a security review before taking an action.
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By Taylor Roberts
Ask ten people what "AI regulation" means, and you'll get ten different answers, and most of them will assume the others are talking about the same thing. They're not. "Regulate AI" has become a catch-all phrase covering several genuinely distinct regulatory questions, each with its own goal, its own toolkit, and its own plausible answer, bundled together so tightly that arguing about one gets mistaken for arguing about all of them.
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By Tomer Teller
Security teams evaluating an AI agent security platform tend to ask the same question after the first demo: will this keep up? Agentic AI changes shape every few weeks, with new frameworks, new coding agents, and new ways for an agent to reach a tool or a credential. A platform that covers today's stack and stalls on next quarter's isn't much of a bet.
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By Tomer Teller
AI agents are moving into production faster than security teams can govern them. And unlike traditional applications, agents continuously make decisions, invoke tools, access data, and take actions. Every one of those interactions creates security context that needs to be understood. At enterprise scale, asking analysts to manually evaluate every finding becomes impossible.
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By Ian Miller
Cursor has become one of the primary AI coding environments for development teams, and its agents increasingly reach into the outside world through MCP servers: databases, ticketing systems, cloud consoles, and internal APIs. Every connection extends what an agent can do. It also extends what could go wrong if that access goes unmonitored or unchecked.
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By Ben Hanson
Ask AI to Choose a prompt Write a TLDR of this post Explain the security risk Summarize what CISOs should know When I walked to the stage in Copenhagen, I had a lot on my mind. For 3 days I'd had countless conversations with leaders and practitioners about AI and agentic security. The one word on everyone's lips was "governance"; day 3 at the conference was "Governance Day," in fact. This is a bag one vendor was giving out: But governance of what? To what end?
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By Rock Lambros
Ask AI to Choose a prompt Write a TLDR of this post Explain the security risk Summarize what CISOs should know Every AI security framework names the risks you have to control. Zenity is built to implement those controls at runtime. Here's the 2026 OWASP Top 10 for LLM Applications, entry by entry, with the gaps marked honestly. Paste a booby-trapped instruction into a chat window, and nothing much happens.
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By Emily Wise
Ask AI to Choose a prompt Write a TLDR of this post Explain the security risk Summarize what CISOs should know The rules have changed. In every AI deployment, the agent itself is now part of the threat model, and that's a first for enterprise security. Prompt injection gets most of the attention, and for good reason: it doesn't require access to source code, credentials, or network infrastructure. It exploits the fundamental mechanism by which language models process instructions.
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By Dina Durutlic
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.
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By Anna Schibli
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.
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By Zenity
Zenity's low-code security research team is exposed to real world low-code applications on a daily basis, and we're glad to share our knowledge in this domain in order to help you to design and develop secure low-code applications.
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Continuously protecting all low-code/no-code applications and components! Design and implement governance policies, identify security risks, detect emerging threats and drive automatic mitigation and response.
Low-code/no-code development and automation platforms are the wave of the future. The largest companies in the world are already adopting low-code/no-code development for their core business units. But with all their benefits, low-code/no-code development brings with it a host of governance challenges and risks that are unaddressed by existing InfoSec and AppSec solutions.
Zenity, the first and only governance and security platform for low-code/no-code applications, creates a win-win environment where IT and information security can give business and pro developers the freedom and independence they want in order to continue pushing their business forward while retaining full visibility and control.
Our Platform:
- Discover: Identify shadow-IT business applications across your low-code/no-code fleet and track sensitive and business data movement.
- Mitigate: Identify insecure, vulnerable and risky configurations. Drive mitigation and remediation immediately.
- Govern: Design policies and implement automatic enforcement. Eliminate risks without disrupting business.
- Protect: Detect suspicious and malicious activity, such as supply-chain attacks, malware obfuscation and data leakage.
Governance and Security for Low-Code/No-Code Applications.