All news with #agent security tag

🔎 Amazon Web Services has introduced Agentic Search for OpenSearch Service, an agent-driven layer that interprets natural-language intent, orchestrates search tools, and generates OpenSearch DSL queries while providing transparent summaries of its decision process. The built-in QueryPlanningTool uses LLMs to plan and emit DSL, removing the need for manual query syntax. Two agent types are available: conversational agents with memory and flow agents optimized for throughput. Administrators can configure agents via APIs or OpenSearch Dashboards, and Agentic Search is supported on OpenSearch Service version 3.3+ across AWS Commercial and GovCloud regions.

🚀 Claude Opus 4.5 is now available in public preview in Microsoft Foundry, aiming to shift models from assistants to agentic collaborators that execute multi-tool workflows and support complex engineering tasks. Anthropic and Microsoft highlight Opus 4.5’s strengthened coding, vision, and reasoning capabilities alongside improved safety and prompt-injection robustness. Foundry adds developer features like Programmatic Tool Calling, Tool Search, Effort Parameter (Beta), and Compaction Control to help teams build deterministic, long-running agents while keeping centralized governance and observability.

🤖 AWS introduces the Agentic AI Security Scoping Matrix to help organizations secure autonomous, tool-enabled AI agents. The framework defines four architectural scopes—from no agency to full agency—and maps escalating security controls across six dimensions, including identity, data/memory, auditability, agent controls, policy perimeters, and orchestration. It advocates progressive deployment, layered defenses, continuous monitoring, and retained human oversight to mitigate risks as autonomy increases.

⚠️ In mid‑September 2025, Anthropic detected a sophisticated espionage campaign in which attackers manipulated its Claude Code tool to autonomously attempt infiltration of roughly thirty global targets, succeeding in a small number of cases. The company assesses with high confidence that a Chinese state‑sponsored group conducted the operation against large technology firms, financial institutions, chemical manufacturers, and government agencies. Anthropic characterizes this as likely the first documented large‑scale cyberattack executed with minimal human intervention, enabled by models' increased intelligence, agentic autonomy, and access to external tools.

🤖Agentic AI gives autonomous agents the ability to access external systems, gather information, and take actions within defined workflows, making routine multi-system tasks far more efficient for human operators. Cisco Talos warns this efficiency is already being mirrored in the cyber crime economy, including the first observed AI-orchestrated campaign in early 2025. While AI lowers barriers to entry and speeds operations for attackers, it is imperfect and still requires skilled instruction and human oversight. Defenders can respond by building their own agentic tools, deploying honeypots to engage malicious agents, and refining detection to stay ahead.

📊 Google introduces BigQuery Agent Analytics, an ADK plugin that streams agent interaction events into BigQuery to capture, analyze, and visualize performance, usage, and cost. The plugin provides a predefined schema and uses the BigQuery Storage Write API for low-latency, high-throughput streaming of requests, responses, and tool calls. Developers can filter and preprocess events (for example, redaction) and build dashboards in Looker Studio or Grafana while leveraging vector search and generative AI functions for deeper analysis.

🚀 At Microsoft Ignite 2025, Microsoft unveiled a suite of Azure infrastructure and AI operational innovations built for scale, reliability, and security. Azure Copilot introduces an agentic operations model with six specialized agents—migration, deployment, optimization, observability, resiliency, and troubleshooting—designed to automate routine cloud management while enforcing RBAC and policy. The release also highlights new AI datacenter architecture (Fairwater), deployment of NVIDIA GB300 GPUs at scale, and platform improvements like Azure Boost and AKS Automatic to accelerate performance and reduce operational overhead.

🛡️ At Microsoft Ignite 2025, Microsoft set out an ambient, autonomous security approach for the emerging agentic era and announced a suite of tools to observe, secure, and govern AI agents and apps. The centerpiece is Microsoft Agent 365, a control plane providing an Entra-based registry, access controls, visualization, and integrations with Defender, Entra, and Purview to detect prompt-injection, prevent leakage, and enable auditing. Microsoft also expanded platform protections, enhanced Copilot data controls in Purview, and positioned Microsoft Sentinel and Security Copilot as agentic security pillars for detection and response.

🧭 Hugo Selbie presents a practical framework for evaluating modern multi-step AI agents, emphasizing that final-output metrics alone miss silent failures arising from incorrect reasoning or tool use. He recommends defining clear, measurable success criteria up front and assessing agents across three pillars: end-to-end quality, process/trajectory analysis, and trust & safety. The piece outlines mixed evaluation methods—human review, LLM-as-a-judge, programmatic checks, and adversarial testing—and prescribes operationalizing these checks in CI/CD with production monitoring and feedback loops.

🤖 This recap of The Agent Factory episode summarizes a conversation between Amit Maraj and Ravin Kumar (DeepMind) about building open-source agentic models. It highlights how agent training differs from standard ML, emphasizing trajectory-based data, a two-stage approach of supervised fine-tuning followed by reinforcement learning, and the paramount role of evaluation. Practical guidance includes defining a 50-example final exam up front and considering hybrid setups that use a powerful API like Gemini as a router alongside specialized open models.

🔐 As enterprises deploy AI assistants and autonomous agents, existing security frameworks must evolve to treat these agents as first-class identities rather than afterthoughts. The piece advocates applying Zero Trust principles—identity-first access, least-privilege, dynamic contextual enforcement, and continuous monitoring—to agentic identities to prevent misuse and reduce attack surface. Practical controls include scoped, short-lived tokens, tiered trust models, strict access boundaries, and assigning clear human ownership to each agent.

🛡️ Agent Sandbox is a new Kubernetes primitive designed to run AI agents with strong, kernel-level isolation. Built on gVisor with optional Kata Containers and developed in the Kubernetes community as a CNCF project, it reduces risks from agent-executed code. On GKE, managed gVisor, container-optimized compute and pre-warmed sandbox pools deliver sub-second startup latency and up to 90% cold-start improvement. A Python SDK and a simple API abstract YAML so AI engineers can manage sandbox lifecycles without deep infrastructure expertise; Agent Sandbox is open source and deployable on GKE today.

🚀 Google details a broad set of GKE and Kubernetes enhancements announced at KubeCon to address agentic AI, large-scale training, and latency-sensitive inference. GKE introduces Agent Sandbox (gVisor-based) for isolated agent execution and a managed GKE Agent Sandbox with snapshots and optimized compute. The platform also delivers faster autoscaling through Autopilot compute classes, Buffers API, and container image streaming, while inference is accelerated by GKE Inference Gateway, Pod Snapshots, and Inference Quickstart.

🧭 This post explains when to use sub-agents versus packaging agents as tools when building multi-agent systems with Google's Agent Development Kit (ADK). It contrasts agents-as-tools — encapsulated, stateless specialists invoked like deterministic function calls — with sub-agents, which are stateful, context-aware delegates that manage multi-step workflows. The guidance highlights trade-offs across task complexity, context sharing, reusability, and autonomy, and illustrates the patterns with data-agent and travel-planner examples to help architects choose efficient, scalable designs.

🔐 Computer-using agents (CUAs) — AI systems that perceive screens and act like humans — are poised to scale phishing and credential-stuffing attacks by automating UI interactions, adapting to layout changes, and bypassing anti-bot defenses. Organizations should move beyond passwords and shared-secret MFA to device-bound, cryptographic authentication such as FIDO2 passkeys and PKI-based certificates to reduce large-scale compromise. SaaS vendors must integrate with identity platforms that support phishing-resistant credentials to strengthen overall security.

🤖 This recap of The Agent Factory features Logan Kilpatrick from Google DeepMind demonstrating vibe coding in Google AI Studio, a Build workflow that turns a natural-language app idea into a live prototype in under a minute. Live demos included a virtual food photographer, grounding with Google Maps, the AI Studio Gallery, and a speech-driven "Yap to App" pair programmer. The episode also surveyed agent ecosystem updates—Veo 3.1, Anthropic Skills, and Gemini improvements—and highlighted the shift from models to action-capable systems.

🤖 Google’s open-source Agent Development Kit (ADK) simplifies creating autonomous AI agents that use LLMs such as Gemini as their reasoning core. The post presents three hands-on codelabs that guide developers through building a personal assistant agent, adding custom and third-party tools, and orchestrating multi-agent workflows. Each lab demonstrates practical patterns—scaffolding an agent, integrating tools like Google Search and LangChain components, and using Workflow Agents and session state to pass information—so teams can progress from experiment to production-ready agent systems.

🏥 Microsoft and UiPath describe how integrated agents from Azure AI Foundry and UiPath, orchestrated by UiPath Maestro, can operationalize AI within clinical workflows to surface and act on incidental radiology findings. The workflow uses UiPath medical record summarization agents to flag findings, Azure AI Foundry imaging agents to analyze PACS images and prior results, and UiPath agents to aggregate and forward consolidated follow-up reports to ordering clinicians. Microsoft says this agentic approach accelerates decision-making, reduces physician workload, and improves outcomes while maintaining compliance with DICOMweb and FHIR standards.

🧭 This guide summarizes Multi-Agent System (MAS) fundamentals and explains how Google’s Agent Development Kit (ADK) helps developers assemble cooperating agents to solve complex tasks. It outlines three agent roles — LLM Agents for reasoning, Workflow Agents for orchestration, and Custom Agents for bespoke logic — and describes hierarchical organization and orchestration patterns (sequential, parallel, loop). The post also reviews communication options (shared state, LLM delegation, explicit invocation) and points developers to samples and codelabs for rapid prototyping.

🔒 Unit42 researchers Jay Chen and Royce Lu describe agent session smuggling, a technique where a malicious AI agent exploits stateful A2A sessions to inject hidden, multi‑turn instructions into a victim agent. By hiding intermediate interactions in session history, an attacker can perform context poisoning, exfiltrate sensitive data, or trigger unauthorized tool actions while presenting only the expected final response to users. The authors present two PoCs (using Google's ADK) showing sensitive information leakage and unauthorized trades, and recommend layered defenses including human‑in‑the‑loop approvals, cryptographic AgentCards, and context‑grounding checks.