All news with #agentic ai tag

Falcon for XIoT Enhances OT Visibility and Speed at Scale

🔍 Falcon for XIoT introduces zero-touch asset discovery, native segmentation visibility, and a unified OT/XIoT view to reduce blind spots across industrial networks. The solution leverages DHCP data and the existing Falcon sensor to build continuous, agentless inventories and to monitor inter-device traffic without manual scan configuration. These enhancements aim to accelerate detection, simplify operations, and provide richer context for faster security decisions across IT, OT, and XIoT environments.

Cybersecurity Forecast 2026: AI, Cybercrime, Nation-State

🔒 The Cybersecurity Forecast 2026 synthesizes frontline telemetry and expert analysis from Google Cloud security teams to outline the most significant threats and defensive shifts for the coming year. The report emphasizes how adversaries will broadly adopt AI to scale attacks, with specific risks including prompt injection and AI-enabled social engineering. It also highlights persistent cybercrime trends—ransomware, extortion, and on-chain resiliency—and evolving nation‑state campaigns. Organizations are urged to adapt IAM, secure AI agents, and harden virtualization controls to stay ahead.

CISO Predictions 2026: Resilience, AI, and Threats

🔐 Fortinet’s CISO Collective outlines priorities and risks CISOs will face in 2026. The briefing warns that AI will accelerate innovation while expanding attack surfaces, increasing LLM breaches, adversarial model attacks, and deepfake-enabled BEC. It highlights geopolitical and space-related threats such as GPS jamming and satellite interception, persistent regulatory pressure including NIS2 and DORA, and a chronic cybersecurity skills gap. Recommendations emphasize governed AI, identity hardening, quantum readiness, and resilience-driven leadership.

Building an AI Champions Network for Enterprise Adoption

🤝 Getting an enterprise-grade generative AI platform in place is a milestone, not the finish line. Sustained, distributed adoption comes from embedding AI into everyday processes through an organized AI champions network that brings enablement close to the work. Champions act as multipliers — translating strategy into team behaviors, surfacing blockers and use cases, and accelerating normalized use. With structured onboarding, rotating membership, monthly working sessions, and direct ties to the core AI program, the network converts tool access into measurable business impact.

BigQuery's Data Engineering Agent: Automating Pipelines

🔧 The preview of the Data Engineering Agent in BigQuery introduces a Gemini-powered assistant that automates pipeline development, maintenance, and migrations. The agent converts natural-language requirements into SQL, enforces engineering best practices, and supports custom instructions and UDFs to reflect organizational logic. Integrated with Dataplex, it uses governance metadata to improve table descriptions, data quality assertions, and PII-aware handling, and it also generates documentation and troubleshooting guidance. The feature is available in preview via BigQuery Pipelines and the Dataform UI.

OpenAI Aardvark: Autonomous GPT-5 Agent for Code Security

🛡️ OpenAI Aardvark is an autonomous GPT-5-based agent that scans, analyzes and patches code by emulating a human security researcher. Rather than only flagging suspicious patterns, it maps repositories, builds contextual threat models, validates findings in sandboxes and proposes fixes via Codex, then rechecks changes to prevent regressions. OpenAI reports it found 92% of benchmark vulnerabilities and has already identified real issues in open-source projects, offering free coordinated scanning for selected non-commercial repositories.

OpenAI Unveils Aardvark: GPT-5 Agent for Code Security

🔍 OpenAI has introduced Aardvark, an agentic security researcher powered by GPT-5 that autonomously scans source code repositories to identify vulnerabilities, assess exploitability, and propose targeted patches that can be reviewed by humans. Embedded in development pipelines, the agent monitors commits and incoming changes continuously, prioritizes threats by severity and likely impact, and attempts controlled exploit verification in sandboxed environments. Using OpenAI Codex for patch generation, Aardvark is in private beta and has already contributed to the discovery of multiple CVEs in open-source projects.

Choosing Google Cloud Managed Lustre for External KV Cache

🚀 This post explains how an external KV Cache backed by Google Cloud Managed Lustre can accelerate transformer inference and lower costs by offloading expensive prefill compute to I/O. In experiments with a 50K token context and ~75% cache-hit, Managed Lustre increased inference throughput by 75% and cut mean time-to-first-token by 44%. The analysis projects a 35% TCO reduction and up to ~43% fewer GPUs for the same workload, and the article summarizes practical steps: provision Managed Lustre in the same zone, deploy an inference server that supports external caching (for example vLLM), enable o_direct, and tune I/O parallelism.

Conversational AI Agents: Designing for Retail UX, Commerce

🛍️ Google Cloud outlines UX and implementation guidance for building conversational AI agents tailored to online shopping. The article presents seven practical design principles — including multimodal input, intelligent query handling, rich visual presentation, and clear trust signals — that improve discovery and reduce friction. It highlights features like predictive assistance and contextual clarification and offers a Figma component library plus developer resources to accelerate deployment.

GKE and Gemini CLI Integration Enhances Developer Workflows

🚀 Google has open-sourced the GKE Gemini CLI extension, bringing Google Kubernetes Engine directly into the Gemini CLI ecosystem while also functioning as an MCP server for other MCP clients. The extension injects GKE-specific context, tools, and tailored prompts so developers can use shorter, more natural language interactions and integrated slash commands to complete complex workflows. It simplifies common operations—like selecting models and accelerators or generating Kubernetes manifests for inference—while improving compatibility with Cloud Observability. The project is actively maintained with regular releases and community contributions.

Agent Session Smuggling Threatens Stateful A2A Systems

🔒 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.

Agentic AI: Reset, Business Use Cases, Tools & Lessons

🤖 Agentic AI burst into prominence with promises of streamlining operations and accelerating productivity. This Special Report assesses what's practical versus hype, examining the current state of agentic AI, the primary deployment challenges organizations face, and practical lessons from real-world success stories. It highlights business processes suited to agentic agents, criteria for evaluating development tools, and how LinkedIn built a platform. The report also outlines near-term expectations and adoption risks.

Aembit Launches IAM for Agentic AI with Blended Identity

🔐 Aembit today announced Aembit Identity and Access Management (IAM) for Agentic AI, introducing Blended Identity and the MCP Identity Gateway to assign cryptographically verified identities and ephemeral credentials to AI agents. The solution extends the Aembit Workload IAM Platform to enforce runtime policies, apply least-privilege access, and maintain centralized audit trails for agent and human actions. Designed for cloud, on‑premises, and SaaS environments, it records every access decision and preserves attribution across autonomous and human-driven workflows.

AI-Powered Bug Hunting Disrupts Bounty Programs and Triage

🔍 AI-powered tools and large language models are speeding up vulnerability discovery, enabling so-called "bionic hackers" to automate reconnaissance, reverse engineering, and large-scale scanning. Platforms such as HackerOne report sharp increases in valid AI-related reports and payouts, but many submissions are low-quality noise that burdens maintainers. Experts recommend treating AI as a research assistant, strengthening triage, and preserving human judgment to filter false positives and duplicates.

Model Context Protocol Proxy for AWS now generally available

🔒 The Model Context Protocol (MCP) Proxy for AWS is now generally available, offering a client-side proxy that lets MCP clients connect to remote, AWS-hosted MCP servers using AWS SigV4 authentication. It supports agentic development tools such as Amazon Q Developer CLI, Kiro, Cursor, and agent frameworks like Strands Agents, and interoperates with MCP servers built on Amazon Bedrock AgentCore Gateway or Runtime. The open-source Proxy includes safety controls (read-only mode), configurable retry logic, and logging for troubleshooting, and can be installed from source, via Python package managers, or as a container to integrate with existing MCP-supported tools.

Agent Registry for Discovering and Verifying Signed Bots

🔐 This post proposes a lightweight, crowd-curated registry for bots and agents to simplify discovery of public keys used for cryptographic Web Bot Auth signatures. It describes a simple list format of URLs that point to signature-agent cards—extended JWKS entries containing operator metadata and keys—and shows how registries enable origins and CDNs to validate agent signatures at scale. Examples and a demo integration illustrate practical adoption.

GitHub Universe 2025: Agents, AI, and Developer Tools

🚀 At GitHub Universe 2025, Microsoft and GitHub presented a vision for agentic development that lets developers see, steer, and build across autonomous agents. The event introduced platform capabilities like Agent HQ, a prompt-first AI Toolkit for VS Code, and the GA release of Azure MCP Server. Announcements focused on enterprise-grade security, standards-based integration, and faster, more intuitive agent creation and governance.

Rethinking Identity Security for Autonomous AI Agents

🔐 Autonomous AI agents are creating a new class of non-human identities that traditional, human-centric security models struggle to govern. These agents can persist beyond intended lifecycles, hold excessive permissions, and perform actions across systems without clear ownership, increasing risks like privilege escalation and large-scale data exfiltration. Security teams must adopt identity-first controls—unique managed identities, strict scoping, lifecycle management, and continuous auditing—to regain visibility and enforce least privilege.

Anonymous Credentials for Privacy-preserving Rate Limiting

🔐 Cloudflare presents a privacy-first approach to rate-limiting AI agents using anonymous credentials. The post explains how schemes such as ARC and ACT extend the Privacy Pass model by enabling late origin-binding, multi-show tokens, and stateful counters so origins can enforce limits or revoke abusive actors without identifying users. It outlines the cryptographic building blocks—algebraic MACs and zero-knowledge proofs—compares performance against Blind RSA and VOPRF, and demonstrates an MCP-integrated demo showing issuance and redemption flows for agent tooling.

AWS releases AI agent context pack for Greengrass developers

🤖 AWS announced an open-source AI agent context package for AWS IoT Greengrass that provides ready-to-use instructions, examples, and templates to accelerate edge device application development. The package is published on GitHub under the Creative Commons Attribution Share Alike 4.0 license and is designed to integrate with generative AI tools such as Amazon Q. Developers can clone the repository to jumpstart creation, testing, and fleet-wide deployment workflows across supported Regions.