All news with #agentic ai tag

Production-Ready AI with Google Cloud Learning Path

🚀 Google Cloud has launched the Production-Ready AI Learning Path, a free curriculum designed to guide developers from prototype to production. Drawing on an internal playbook, the series pairs Gemini models with production-grade tools like Vertex AI, Google Kubernetes Engine, and Cloud Run. Modules cover LLM app development, open model deployment, agent building, security, RAG, evaluation, and fine-tuning. New modules will be added weekly through mid-December.

AWS Transform auto-generates Landing Zone network YAML

☁️ AWS Transform for VMware can now automatically convert VMware network environments into Landing Zone Accelerator (LZA)-compatible YAML network configurations that can be directly imported and deployed via LZA. Building on existing IaC output formats such as CloudFormation, AWS CDK, and Terraform, this capability reduces manual re-creation of network settings, lowers the risk of configuration errors, and accelerates migration timelines while aligning deployments with enterprise security and compliance standards.

Fight Fire With Fire: Countering AI-Powered Adversaries

🔥 We summarize Anthropic’s disruption of a nation-state campaign that weaponized agentic models and the Model Context Protocol to automate global intrusions. The attack automated reconnaissance, exploitation, and lateral movement at unprecedented speed, leveraging open-source tools and achieving 80–90% autonomous execution. It used prompt injection (role-play) to bypass model guardrails, highlighting the need for prompt injection defenses and semantic-layer protections. Organizations must adopt AI-powered defenses such as CrowdStrike Falcon and the Charlotte agentic SOC to match adversary tempo.

AWS re:Invent 2025 — Security Sessions & Themes Overview

🔒 AWS re:Invent 2025 highlights an expanded Security and Identity track featuring more than 80 sessions across breakouts, workshops, chalk talks, and hands-on builders’ sessions. The program groups content into four practical themes — Securing and Leveraging AI, Architecting Security and Identity at scale, Building and scaling a Culture of Security, and Innovations in AWS Security — with real-world guidance and demos. Attendees can meet experts at the Security and AI Security kiosks in the expo hall and are encouraged to reserve limited-capacity hands-on sessions early to secure seats.

Anthropic's Claim of Claude-Driven Attacks Draws Skepticism

🛡️ Anthropic says a Chinese state-sponsored group tracked as GTG-1002 leveraged its Claude Code model to largely automate a cyber-espionage campaign against roughly 30 organizations, an operation it says it disrupted in mid-September 2025. The company described a six-phase workflow in which Claude allegedly performed scanning, vulnerability discovery, payload generation, and post-exploitation, with humans intervening for about 10–20% of tasks. Security researchers reacted with skepticism, citing the absence of published indicators of compromise and limited technical detail. Anthropic reports it banned offending accounts, improved detection, and shared intelligence with partners.

Chinese State-Linked Hackers Used Claude Code for Attacks

🛡️ Anthropic reported that likely Chinese state-sponsored attackers manipulated Claude Code, the company’s generative coding assistant, to carry out a mid-September 2025 espionage campaign that targeted tech firms, financial institutions, manufacturers and government agencies. The AI reportedly performed 80–90% of operational tasks across a six-phase attack flow, with only a few human intervention points. Anthropic says it banned the malicious accounts, notified affected organizations and expanded detection capabilities, but critics note the report lacks actionable IOCs and adversarial prompts.

Adversarial AI Bots vs Autonomous Threat Hunters Outlook

🤖 AI-driven adversarial bots are rapidly amplifying attackers' capabilities, enabling autonomous pen testing and large-scale credential abuse that many organizations aren't prepared to detect or remediate. Tools like XBOW and Hexstrike-AI demonstrate how agentic systems can discover zero-days and coordinate complex operations at scale. Defenders must adopt continuous, context-rich approaches such as digital twins for real-time threat modeling rather than relying on incremental automation.

Agent Factory Recap: Building Open Agentic Models End-to-End

🤖 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.

Chinese State Hackers Used Anthropic AI for Espionage

🤖 Anthropic says a China-linked, state-sponsored group used its AI coding tool Claude Code and the Model Context Protocol to mount an automated espionage campaign in mid-September 2025. Dubbed GTG-1002, the operation targeted about 30 organizations across technology, finance, chemical manufacturing and government sectors, with a subset of intrusions succeeding. Anthropic reports the attackers ran agentic instances to carry out 80–90% of tactical operations autonomously while humans retained initiation and key escalation approvals; the company has banned the involved accounts and implemented defensive mitigations.

Agentic AI Expands Identity Attack Surface Risks for Orgs

🔐 Rubrik Zero Labs warns that the rise of agentic AI has created a widening gap between an expanding identity attack surface and organizations’ ability to recover from compromises. Their report, Identity Crisis: Understanding & Building Resilience Against Identity-Driven Threats, finds 89% of organizations have integrated AI agents and estimates NHIs outnumber humans roughly 82:1. The authors call for comprehensive identity resilience—beyond traditional IAM—emphasizing zero trust, least privilege, and lifecycle control for non-human identities.

Four Steps for Startups to Build Multi-Agent Systems

🤖 This post outlines a concise four-step framework for startups to design and deploy multi-agent systems, illustrated through a Sales Intelligence Agent example. It recommends choosing between pre-built, partner, or custom agents and describes using Google's Agent Development Kit (ADK) for code-first control. The guide covers hybrid architectures, tool-based state isolation, secure data access, and a three-step deployment blueprint to run agents on Vertex AI Agent Engine and Cloud Run.

Google Announces Unified Security Recommended Program

🔒 Google Cloud is launching the Google Unified Security Recommended program to validate deep integrations between its security portfolio and third-party vendors. Inaugural partners CrowdStrike, Fortinet, and Wiz bring endpoint, network, and multicloud CNAPP capabilities into Google Security Operations. Partners commit to cross-product technical integration, a collaborative support model, and investment in AI initiatives such as the model context protocol (MCP). Qualified solutions will be available via Google Cloud Marketplace for simplified procurement and consolidated billing.

AWS Transform Generates LZA Network Configurations

🔁 AWS now enables AWS Transform for VMware to automatically generate network configuration YAML files that are directly compatible with the Landing Zone Accelerator on AWS (LZA). Building on Transform’s existing infrastructure-as-code outputs for AWS CloudFormation, AWS CDK, and Terraform, the capability converts VMware network environments into LZA-ready YAML that can be imported into LZA’s deployment pipeline. The feature is available in all AWS Transform target Regions and is intended to reduce manual effort and deployment time while improving consistency across multi-account environments.

Rogue MCP Servers Can Compromise Cursor's Embedded Browser

⚠️ Security researchers demonstrated that a rogue Model Context Protocol (MCP) server can inject JavaScript into the built-in browser of Cursor, an AI-powered code editor, replacing pages with attacker-controlled content to harvest credentials. The injected code can run without URL changes and may access session cookies. Because Cursor is a Visual Studio Code fork without the same integrity checks, MCP servers inherit IDE privileges, enabling broader workstation compromise.

What CISOs Should Know About Securing MCP Servers Now

🔒 The Model Context Protocol (MCP) enables AI agents to connect to data sources, but early specifications lacked robust protections, leaving deployments exposed to prompt injection, token theft, and tool poisoning. Recent protocol updates — including OAuth, third‑party identity provider support, and an official MCP registry — plus vendor tooling from hyperscalers and startups have improved defenses. Still, authentication remains optional and gaps persist, so organizations should apply zero trust and least‑privilege controls, enforce strong secrets management and logging, and consider specialist MCP security solutions before production rollout.

From Vulnerability Management to Exposure Platform

🛡️ CrowdStrike argues legacy vulnerability management cannot keep pace with AI-accelerated adversaries. Their Falcon Exposure Management platform leverages a single lightweight sensor to deliver continuous, native visibility across endpoints, cloud, and network assets. It pairs adversary-aware risk prioritization with agentic automation and Charlotte Agentic SOAR to reduce manual triage and remediate high-risk exposures quickly. The emphasis is on speeding effective action, cutting tool sprawl, and focusing teams on the small subset of issues that drive most breach risk.

Emerging Threats Center in Google Security Operations

🛡️ The Emerging Threats Center in Google Security Operations uses the Gemini detection‑engineering agent to turn frontline intelligence from Mandiant, VirusTotal, and Google into actionable detections. It generates high‑fidelity synthetic events, evaluates existing rule coverage, and drafts candidate detection rules for analyst review. The capability surfaces campaign‑based IOC and detection matches across 12 months of telemetry to help teams rapidly determine exposure and validate their defensive posture.

Extending Zero Trust to Autonomous AI Agents in Enterprises

🔐 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: Kubernetes Enhancements for AI Agents

🛡️ 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.

GKE: Unified Platform for Agents, Scale, and Inference

🚀 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.