All news with #agentic ai tag

🧭 This Google Cloud blog summarizes findings from a survey of over 1,400 IT leaders showing a widening gap between AI ambitions and existing infrastructure. It explains why agentic AI stresses legacy systems and highlights needs for fluid compute, unified data layers, hybrid deployments, and energy-efficient co-designed silicon like TPU 8t. The post also promotes Google Cloud’s AI Hypercomputer and governance solutions such as Agent Gateway.

🤖 This post introduces the Gemini Enterprise Agent Platform and offers 20 practical questions for IT and engineering leaders to consider when building AI agents. It covers who builds agents, which development tools to use, how to connect data and other agents, strategies for scaling, and methods for securing execution and preserving context. The article pairs guidance with recommended Google tools like ADK, Antigravity, Agent Runtime, MCP, A2A, and Agent Studio.

🛡️ Zscaler tested 26 LLMs and found several autonomous agents susceptible to indirect prompt injection (IPI) traps, with some high-end models failing while a few lower-tier models fared better. The vendor identified hidden instructions on websites that manipulated agent behavior and caused real-world impacts in controlled tests. Experts warn that agent risk is dynamic, the attack surface is architectural, and binary "safe/vulnerable" labels are overly simplistic for CISOs. The findings highlight that agentic AI introduces new trust boundaries and insider-like threats to enterprise security.

🛡️ Zscaler tested 26 LLM-based autonomous agents and found several susceptible to indirect prompt injection (IPI) schemes, with some high-end models failing while a few lower-tier models fared better. The vendor reported four models as "vulnerable" and three as "safe," but experts warn that agent behavior evolves and binary classifications can be misleading. The findings highlight the architectural risks in agentic AI where untrusted content in the context window can be treated as authoritative, expanding the attack surface for enterprises.

🔒 This post describes a reference implementation using Cedar on AWS to prevent silent privilege escalation in multi-agent AI delegation chains. It outlines a three-layer policy model—agent-to-tool, agent-to-agent delegation, and originating user authorization—using verified token claims and HMAC-signed context. The architecture uses an MCP adapter Lambda and a Cedar evaluator Lambda to enforce policies sequentially and halt on the first deny. It includes schema, entity registrations, policy examples, deployment steps, and end-to-end test scenarios demonstrating how the model enforces least privilege.

🔒 Google Cloud and Valtech introduce Nexus SDV, an open-source, modular platform that enables AI-native, scalable management of software-defined vehicles. The platform integrates with Android Automotive OS and supports up to 100 million devices while emphasizing TCO reduction via Arm-based compute and Bigtable. Nexus AI leverages Gemini models and the Gemini Enterprise Agent Platform for real-time telemetry analysis and agentic vehicle capabilities. Security is built-in with mTLS/PKI, identity brokering, secret management, network isolation, and an enterprise Secure AI Framework.

🔍 Zscaler ThreatLabz uncovered real-world campaigns using indirect prompt injection, where hidden instructions embedded in web pages steer AI agents. Attackers used SEO poisoning to surface malicious pages and hid prompts via CSS and JSON-LD metadata. One campaign impersonated a Python library to trick agents into paying a $3 bogus API key; another typosquatted a DeBank site to claim authority. Tests across 26 LLMs showed varying susceptibility depending on model and context.

🤖 Stephen Wilson of HashiCorp describes agentic AI as “really smart kindergartners” — capable of execution but lacking judgment. This mismatch strains traditional zero trust models that authenticate humans and grant privileges gradually, because agents can be created and destroyed rapidly. Organizations often respond by lowering controls, risking incidents such as accidental deletion of production data. Wilson argues this will force necessary long-term improvements like zero standing privilege and dynamic credentials while keeping humans "on the loop."

🛡️ Existing security controls weren’t built for autonomous AI agents, and static credentials and standing privileges are insufficient. Organizations must define agentic identity, secure agent-to-agent communication, adopt dynamic secrets management, enforce least privilege for delegated workflows, and unify workforce identity. Governance across the identity lifecycle is essential to ensure auditable, revocable, and context-aware access for agents.

🤖 Stephen Wilson of HashiCorp explains how enterprise AI is evolving from human-assisted tools to autonomous agents and operators, and why governance must mature accordingly. He describes three adoption patterns—AI as assistant, AI as agent, and AI as operator—and details the increasing needs for identity, access controls, auditability, and accuracy at each stage. As organizations grant agents more autonomy, security controls must expand from user-level boundaries to team and organizational governance.

🔒 Sysdig reports a novel ransomware campaign, dubbed JadePuffer, driven entirely by a large language model agent that exploited CVE-2025-3248 in an internet-facing Langflow instance. The automated attack conducted reconnaissance, credential harvesting, lateral movement, and destructive actions against production databases, encrypting and deleting Nacos configurations so they could not be recovered. Sysdig highlights automation of old vulnerabilities, agent narration that may aid detection, and the erosion of response time for defenders.

🔒 This article explains how traditional identity lifecycle management — built around HR-driven joiner, mover, and leaver events — fails to govern AI agents. It describes how agents are created outside HR and IGA workflows, arrive with embedded credentials, and expand access dynamically at runtime. The piece highlights gaps in provisioning, access reviews, and offboarding when agents proliferate across parallel instances and orchestration layers.

🛡️ Researchers discovered two vulnerabilities in the Cursor AI-enabled IDE that enable prompt-injection-driven remote code execution by escaping the command execution sandbox. The flaws, CVE-2026-50548 and CVE-2026-50549, allow attackers to change the working directory and exploit symlink canonicalization fallbacks to write or overwrite files outside the project scope. Cursor patched the issues in version 3.0, and the findings underscore broader risks in agentic AI workflows and the difficulty of defending against prompt injection.

🛠️ This post outlines an architecture using Google's ADK and Gemini Flash to replace static prompt-driven agents with a just-in-time, metadata-driven orchestration. It externalizes JSON schema descriptors to a Central Metadata Registry and employs a lightweight discovery prompt plus dynamic validation hooks (Cloud Run) to ensure deterministic, schema-compliant payloads. The pattern reduces context bloat, lowers token costs, and prevents attention diffusion in multi-agent workflows.

🛡️ Cloudflare updates its bot management to distinguish between three AI use cases—Search, Agent, and Training—so site owners can better control access and compensation for their content. The company will change defaults on September 15, 2026, blocking Training and Agent bots on ad-bearing pages while leaving Search allowed. Cloudflare also launched BotBase, a searchable directory of tracked bots, and added a new content-use signal for robots.txt to express preferences like use=reference.

🧭 Cloudflare reports a rapid shift toward an agent-driven Internet where AI training and mixed-use crawlers dominate. Publishers face falling referral traffic as over 50% of Internet traffic is now non-human, and AI companies increasingly ingest content without compensation. Cloudflare highlights tools and marketplace developments that restore publisher control, enable attribution, and support licensing between content owners and AI firms.

🖥️ Amazon WorkSpaces for agents is generally available, enabling AI agents to securely access and operate desktop applications inside managed WorkSpaces. The service lets agents interact with legacy ERP, CRM, mainframe, and proprietary tools without application modernization or custom integrations, while preserving identity controls, network isolation, and compliance boundaries. It supports any agent framework using the Model Context Protocol (MCP), and pricing is based on active session time.

🔒 This update summarizes June 2026 releases across Microsoft Security that strengthen identity, multicloud, data, and developer protections. Highlights include codename MDASH for multi-model agentic vulnerability scanning, expanded Microsoft Defender agent and MCP detection, GA for Microsoft Entra Backup and Recovery, and extended database threat protection for AWS RDS. New reporting, multicloud coverage, and a unified identity risk score help teams detect, prioritize, and recover faster.

🔒 New research from Adversa AI, dubbed GuardFall, shows a decades-old shell trick can bypass simple blocklist checks in open-source AI coding agents, letting hidden destructive commands run. The flaw arises because filters inspect the command as plain text while shells like bash rewrite and expand that text before execution. Ten of eleven tested agents were vulnerable; only Continue defended by parsing commands the same way the shell does.

🔒 Two new models are now available in the Kiro IDE and CLI for the AWS GovCloud (US-West) Region. OpenAI GPT-5.4 supports complex reasoning, coding, document analysis, and multi-step agentic workflows, running on Amazon Bedrock with a 272K context window and 1.2x credit multiplier. NVIDIA Nemotron 3 Super 120B is offered as an open weight, hybrid MoE option with a 256K context window, 32K max output, and 0.25x credit multiplier. Update your IDE or CLI and restart to access the new models.