All news with #agent security tag

🔐 The Hacker News is promoting a free webinar that presents a practical framework to secure AI at scale while preserving speed of adoption. Organizers warn of a growing “quiet crisis”: rapid proliferation of unmanaged AI agents and identities that lack lifecycle controls. The session focuses on embedding security by design, governing AI agents that behave like users, and stopping credential sprawl and privilege abuse from Day One. It is aimed at engineers, architects, and CISOs seeking to move from reactive firefighting to proactive enablement.

🛡️ This recap of the Agent Factory episode explains practical strategies for securing production AI agents, demonstrating attacks like prompt injection, invisible Unicode exploits, and vector DB context poisoning. It highlights Model Armor for pre- and post-inference filtering, sandboxed execution, network isolation, observability, and tool safeguards via the Agent Development Kit (ADK). The team demonstrates a secured DevOps assistant that blocks data-exfiltration attempts while preserving intended functionality and provides operational guidance on multi-agent authentication, least-privilege IAM, and compliance-ready logging.

🤖 This post explains how System Integrator partners can build, scale, and manage enterprise-grade AI agents using Google Cloud technologies like Agent Engine, the Agent Development Kit (ADK), and Gemini Enterprise. It summarizes architecture patterns including runtime, memory, the Model Context Protocol (MCP), and the Agent-to-Agent (A2A) protocol, and contrasts managed Agent Engine with self-hosted options such as Cloud Run or GKE. Customer examples from Deloitte and Quantiphi illustrate supply chain and sales automation benefits. The guidance highlights security, observability, persistent memory, and model tuning for enterprise readiness.

📡 This recap of the Agent Factory podcast episode, hosted by Annie Wang with guest Ivan Nardini, explains how to evaluate autonomous agents using a practical, full-stack approach. It outlines what to measure — final outcomes, chain-of-thought, tool use, and memory — and contrasts measurement techniques: ground truth, LLM-as-a-judge, and human review. The post demonstrates a 5-step debugging loop using the Agent Development Kit (ADK) and describes how to scale evaluation to production with Vertex AI.

⚙️ Microsoft is introducing Copilot Actions, a Windows 11 Copilot feature that allows AI agents to operate on local files and applications by clicking, typing, scrolling and using vision and advanced reasoning to complete multi-step tasks. The capability will roll out to Windows Insiders in Copilot Labs, extending earlier web-based actions introduced in May. Agents run in isolated Agent Workspaces tied to standard Windows accounts, are cryptographically signed, and the feature is off by default.

🛡️ Microsoft released ExCyTIn-Bench, an open-source benchmarking tool to evaluate how well AI systems perform realistic cybersecurity investigations. It simulates a multistage Azure SOC using 57 Microsoft Sentinel log tables and measures multistep reasoning, tool usage, and evidence synthesis. The benchmark offers fine-grained, actionable metrics for CISOs, product owners, and researchers.

🤖 Organizations are rapidly adopting agentic AI that does more than suggest actions—it opens tickets, calls APIs, and even remediates incidents autonomously. These agents differ from traditional Non-Human Identities because they reason, chain steps, and adapt across systems, making attribution and oversight harder. The author from Token Security recommends named ownership, on‑behalf tracing, and conservative, time‑limited permissions to curb shadow AI risks.

🔒 A new SquareX Labs report warns that integrating AI assistants into browsers—exemplified by Perplexity’s Comet—introduces architectural security gaps that can enable phishing, prompt injection, malicious downloads and misuse of trusted apps. The researchers flag risks from autonomous agent behavior and limited visibility in SASE and EDR tools. They recommend agentic identity, in-browser DLP, client-side file scanning and extension risk assessments, and urge collaboration among browser vendors, enterprises and security vendors to build protections into these platforms.

⚠️ AI agents are increasingly automating cyberattacks, performing reconnaissance, exploitation, and data theft at machine speed and scale. In 2023 examples include XBOW's mass vulnerability reports, DARPA teams finding dozens of flaws in hours, and reports of adversaries using Claude and HexStrike-AI to orchestrate ransomware and persistent intrusions. This shift threatens accelerated attacks beyond traditional patch cycles while presenting new defensive opportunities such as AI-assisted vulnerability discovery, VulnOps, and even self-healing networks.

🤖 Google Cloud published the Startup technical guide: AI agents, a practical, operations-driven roadmap to design, build, and operate agentic systems for startups. The guide outlines three paths — build with the open-source Agent Development Kit (ADK), design no-code agents in Agentspace, or adopt managed and partner agents via Vertex AI and the Agent Garden marketplace. It details four development steps (identity, prime directive, tools, lifecycle), highlights operational rigor (AgentOps), and promotes interoperability through standards such as MCP and A2A, all aimed at safe production deployment.

🔒 Google announced a set of AI security measures: the AI-powered agent CodeMender, a dedicated AI Vulnerability Reward Program (AI VRP), and Secure AI Framework 2.0 (SAIF 2.0). CodeMender leverages advanced reasoning to find, self-validate, and propose patches at scale. SAIF 2.0 introduces an agent risk map and secure-by-design controls, while the AI VRP centralizes reporting and incentives to accelerate remediation.

🔒 Databricks has introduced Data Intelligence for Cybersecurity, an AI-driven platform that unifies fragmented security telemetry on its Lakehouse architecture to provide real-time, context-rich threat detection. The offering includes Agent Bricks to build governed AI agents, conversational dashboards, and natural-language queries for nontechnical stakeholders. Early adopters such as Arctic Wolf, Palo Alto Networks, and SAP report sharper detection, lower costs, and faster operations, while Databricks expands integrations across a broad partner ecosystem to challenge established SIEM and analytics vendors.

🛡️ Agentic AI is moving from lab experiments into real-world SOC deployments, where autonomous agents triage alerts, correlate signals across tools, enrich context, and in some cases enact first-line containment. Early adopters report fewer mundane tasks for analysts, faster initial response, and reduced alert fatigue, while noting limits around noisy data, false positives, and opaque reasoning. Most teams begin with bolt-on integrations into existing SIEM/SOAR pipelines to minimize disruption, treating standalone orchestration as a second-phase maturity step.

🔒 Okta introduced an Identity Security Fabric to secure AI agents and unify identity, application, and agent management across enterprises. The platform combines AI agent lifecycle management, a Cross App Access protocol, and Verifiable Digital Credentials (VDC) to enforce least privilege, discover and monitor agents, and replace fragmented point solutions. Early access features begin in fiscal 2027.

🧪 OpenAI is internally testing a new AI agent, GPT-Alpha, built on a special GPT-5 variant and briefly exposed to users in an accidental push. A screenshot shared on X showed an 'Agent with Truncation' listing under Alpha Models, and the agent's system prompt outlines capabilities to browse the web, generate and edit images, write, run, and debug code, and create or edit documents, spreadsheets, and slides. OpenAI says the agent uses GPT-5 for advanced reasoning and tool use and may initially be offered as a paid feature due to increased compute demands.

🔧This wrap-up of the Agent Factory series lays out a repeatable blueprint for designing and deploying enterprise-grade AI agents and introduces the agentic web stack. It catalogs eight essential components—communication protocols, discovery, identity and trust, tool invocation, orchestration, telemetry, memory, and governance—and positions Azure AI Foundry as an implementation. The post stresses open standards such as MCP and A2A, emphasizes interoperability across organizations, and highlights observability and governance as core operational requirements.

🤖 Amazon Web Services announced the Nova Act extension, embedding the agent development workflow directly into popular IDEs such as Visual Studio Code, Kiro, and Cursor. The extension unifies natural-language script creation, fine-grained scripting controls, and integrated browser testing into a single interface, reducing context switching across tools. Built on the Nova Act SDK (research preview since March 2025), the extension is available today from IDE extension marketplaces and the project’s GitHub repository includes documentation and examples to get started.

⚠️ Agentic AI is proliferating inside enterprises, embedding autonomous agents into development, customer support, process automation, and employee workflows. Security experts warn these systems create substantial visibility and governance gaps: organizations often do not know where agents run, what data they access, or how independent their actions are. Key risks include risky autonomy, uncontrolled data sharing among agents, third-party integration vulnerabilities, and the potential for agents to enable or mimic multi-stage attacks. CISOs should prioritize real-time observability, strict governance, secure-by-design development, and cross-functional coordination to mitigate these threats.

🚀 The Gemini CLI is an open-source, agentic command-line assistant built to reason, select tools, and execute multi-step developer workflows while keeping users informed. In a recent Agent Factory episode, creator Taylor Mullen discussed the project's origin, design philosophy, and roadmap. Demonstrations showed onboarding to codebases, converting research papers into interactive explainers, and creating reusable slash commands. The team emphasizes extensibility, transparency, and community-driven contributions.

🛠️ Vertex AI Agent Builder is a unified platform for building, grounding, and deploying production-grade AI agents, designed to move organizations from prototype to scalable, secure services. It centers development on five pillars: Agent frameworks, Model choice, Tools for taking actions, Scalability and performance, and Built-in trust and security, and supports the Agent Development Kit (ADK) and third-party models including Gemini 2.5 Flash Pro. The platform offers managed runtime features such as sandboxed code execution, Agent-to-Agent collaboration, Bidirectional Streaming, and a streamlined one-line path from ADK prototype to Agent Engine deployment, while enterprise controls like VPC-SC and CMEK address compliance and data protection.