All news with #agent security tag

🛡️ Prisma AIRS integrates with Factory’s Droid Shield Plus to secure agent-native software development by inspecting all LLM interactions in real time. The platform monitors prompts, model responses and downstream tool calls to detect prompt injection, secret leakage and malicious code execution. Using an API Intercept pattern, Prisma AIRS can coach, block or quarantine risky inputs and generated outputs before they reach developers or repositories. This native, continuous protection is designed to preserve developer velocity while improving deployment confidence.

🤖 Organizations are adopting agentic AI—systems that coordinate multiple models and tools to act on tasks—but many leaders find limited benefit when bots misinterpret instructions or produce trivial results. The essay argues that agentic systems increasingly exhibit human-like group behaviors and that established management disciplines—delegation, iteration, effective information sharing, and measurement—remain central to success. Drawing on Anthropic’s Claude Research and other studies, it offers practical guidance for designing hybrid human–AI workflows.

🛡️ OWASP published the Agentic Applications Top 10 for 2026 to classify risks unique to autonomous AI agents. Koi Security summarizes multiple real incidents from the past year — malicious MCP servers, poisoned assistants, and RCEs in Claude Desktop extensions — that show how autonomy expands attack surfaces. The report stresses inventorying runtime dependencies, enforcing least privilege, and monitoring agent behavior to detect and contain attacks.

🔒 Many enterprises are racing to deploy autonomous agentic AI without establishing robust identity and authentication controls, creating an identity crisis for CISOs. Experts warn that fewer than 5–10% of organizations assign formal agent identities (for example via PKI) before wider release, leaving deployments vulnerable to hijacking and prompt-injection. Because agents routinely communicate with one another, a compromised agent can cascade malicious instructions across legitimate agents before revocation, and current vendor solutions and kill switches are incomplete or absent.

🔒 The post summarizes a recent Agent Factory episode where Google product leaders discuss running agentic workloads on GKE. It highlights the Agent Development Kit (ADK), containerized deployments to Artifact Registry, and why Kubernetes provides governance and fine-grained control for large-scale agents. Google demonstrated an Agent Sandbox using gVisor and strict network policies, and introduced Pod Snapshots to cut sandbox startup from minutes to seconds, enabling lower-latency, secure agent workflows.

🛡️ The OWASP Top 10 for Agentic Applications identifies the most critical security risks from AI agents—systems that access data, invoke tools, and act autonomously—and offers CISOs practical threat taxonomies, mitigation strategies, and example threat models. Contributors prioritized data-driven, real-world issues discovered during research, including many agentic deployments unknown to IT and security teams. The list is designed to be consumable and directly actionable for threat modeling, governance, and security architecture.

🔒 CrowdStrike outlines a science-backed framework for training, validating, and hardening AI agents to perform analyst-grade triage and response in the SOC. The post emphasizes using expert-annotated data, reproducible benchmarking, continuous human feedback, scalable heterogeneous architecture, strict guardrails, and adversarial testing. CrowdStrike cites over 98% decision accuracy for Charlotte AI Detection Triage and Agentic Response agents and highlights time-savings and auditable recommendations to accelerate investigations while preserving human oversight.

🔗 To build production-ready agentic systems, Google Cloud offers hands-on labs that demonstrate how Agent Development Kit (ADK), the Model Context Protocol (MCP), and the Agent-to-Agent Protocol (A2A) work together. The labs begin with a foundational "Hello World" agent and progress to connecting agents to knowledge sources via MCP, with concrete examples for exposing BigQuery and CloudSQL. By adopting these standards instead of bespoke integrations, teams can scale and maintain multi-agent systems more reliably.

🔒 Microsoft argues that as organizations adopt agentic AI, security must be a strategic priority that enables growth, trust, and continued innovation. The post identifies risks such as oversharing, data leakage, compliance gaps, and agent sprawl, and recommends three pillars: prepare for AI and agent integration, strengthen organization-wide skilling, and foster a security-first culture. It points to resources like Microsoft’s AI adoption model, Microsoft Learn, and the AI Skills Navigator to help operationalize these steps.

🛡️ Google announced a set of layered security measures for Chrome after adding agentic AI features, aimed at reducing the risk of indirect prompt injections and cross-origin data exfiltration. The centerpiece is a User Alignment Critic, a separate model that reviews and can veto proposed agent actions using only action metadata to avoid being poisoned by malicious page content. Chrome also enforces Agent Origin Sets via a gating function that classifies task-relevant origins into read-only and read-writable sets, requires gating approval before adding new origins, and pairs these controls with a prompt-injection classifier, Safe Browsing, on-device scam detection, user work logs, and explicit approval prompts for sensitive actions.

🔐 This post from Adrien Delaroche at Google Cloud outlines three architectures for AI agents that interact with blockchains: the agent-controlled custodial model, a self-hosted variant, and the non-custodial transaction-crafter model. It explains security, performance, and malice risks when agents hold private keys and recommends returning unsigned transactions so users sign locally. The author demonstrates a sample implementation using Google ADK, Gemini 2.0 Flash, Cloud Run, and an Ethereum faucet, and urges MCP servers to support both signing and unsigned flows to balance automation with user safety.

🚨 The emergence of agentic AI browsers converts the browser from a passive viewer into an autonomous digital agent that can act on users' behalf. To perform tasks—booking travel, filling forms, executing payments—these agents must hold session cookies, saved credentials, and payment data, creating an unprecedented attack surface. The piece cites OpenAI's ChatGPT Atlas as an example and warns that prompt injection and the resulting authenticated exfiltration can bypass conventional MFA and network controls. Recommended mitigations include auditing endpoints for shadow AI browsers, enforcing allow/block lists for sensitive resources, and augmenting native protections with third-party browser security and anti-phishing layers.

🤖 Agentic AI is emerging as a practical accelerator for security teams, automating detection, triage, remediation and routine operations to improve speed and scale. Security leaders at Zoom, Dell, Palo Alto and others highlight its ability to reduce alert fatigue, augment SOCs and act as a force multiplier amid persistent skills shortages. Implementations emphasize augmentation over replacement, enabling continuous monitoring and faster, more consistent responses.

🔎 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.