All news with #agentic ai tag

⚠️ Notion 3.0 introduces AI agents that, the author argues, create a dangerous attack surface. The vulnerability exploits Simon Willson’s lethal trifecta—access to private data, exposure to untrusted content, and the ability to communicate externally—by hiding executable instructions in a white-on-white PDF that instructs the model to collect and exfiltrate client data via a constructed URL. The post warns that current agentic systems cannot reliably distinguish trusted commands from malicious inputs and urges caution before deployment.

🔐 Agent Payment Protocol (AP2) is an open trust layer that enables AI shopping agents to complete purchases without ever handling raw payment credentials. AP2 enforces a role-based separation—shopping agent, merchant endpoint, credential provider, and payment processor—and relies on verifiable credentials to produce cryptographic proof of intent and approval. It defines three mandate types (Cart, Intent, Payment) to support both human-present and human-not-present flows. Developers can adopt AP2 as an extension to A2A and MCP to reduce PCI scope and improve accountability.

⚠️ Many organizations are moving too quickly into agentic AI and risk major security failures unless boards embed governance and security from day one. The article argues that the shift from AI giving answers to AI taking actions changes the control surface to identity, privilege and oversight, and that most programs lack cross‑functional accountability. It recommends forming an Agentic Governance Council, defining measurable objectives and building zero trust guardrails, and highlights Prisma AIRS as a platform approach to restore visibility and control.

🛡️ Agentic AI is moving from lab experiments into real-world SOC deployments, where autonomous agents triage alerts, correlate signals across tools, enrich context, and in some cases enact first-line containment. Early adopters report fewer mundane tasks for analysts, faster initial response, and reduced alert fatigue, while noting limits around noisy data, false positives, and opaque reasoning. Most teams begin with bolt-on integrations into existing SIEM/SOAR pipelines to minimize disruption, treating standalone orchestration as a second-phase maturity step.

🚀 Beginning today, Amazon Bedrock is available in the Israel (Tel Aviv) region, enabling customers to build and scale generative AI applications with local infrastructure. The managed service connects organizations to a variety of foundation models (FMs) and provides tools to deploy and operate agents, reducing time-to-production. Local availability can lower latency, support regional compliance needs, and help move projects from experimentation to real-world deployment.

🔐 At Fal.Con 2025, CrowdStrike CEO George Kurtz outlined a shift from reactive SOCs to an agentic model where intelligent agents reason, decide, act, and learn across domains. CrowdStrike introduced seven AI agents within its Charlotte framework for exposure prioritization, malware analysis, hunting, search, correlation rules, data transformation and workflow generation, and is enabling customers to build custom agents. The company highlights a proprietary "data moat" of trillions of telemetry events and annotated MDR threat data as the foundation for training agents, and announced the acquisition of Pangea to protect AI agents and launch AIDR (AI Detection and Response). The vision places humans as orchestrators overseeing fleets of agents, accelerating detection and response while preserving accountability.

⚠️ Salesforce has released patches for a critical prompt-injection vulnerability dubbed ForcedLeak that could allow exfiltration of CRM data from Agentforce. Discovered and reported by Noma Security on July 28, 2025 and assigned a CVSS score of 9.4, the flaw affects instances using Web-to-Lead when input validation and URL controls are lax. Researchers demonstrated a five-step chain that coerces the Description field into executing hidden instructions, queries sensitive lead records, and transmits the results to an attacker-controlled, formerly allowlisted domain. Salesforce has re-secured the expired domain and implemented a Trusted URL allowlist to block untrusted outbound requests and mitigate similar prompt-injection vectors.

🧪 OpenAI is internally testing a new AI agent, GPT-Alpha, built on a special GPT-5 variant and briefly exposed to users in an accidental push. A screenshot shared on X showed an 'Agent with Truncation' listing under Alpha Models, and the agent's system prompt outlines capabilities to browse the web, generate and edit images, write, run, and debug code, and create or edit documents, spreadsheets, and slides. OpenAI says the agent uses GPT-5 for advanced reasoning and tool use and may initially be offered as a paid feature due to increased compute demands.

🧭 Google outlines an AI-native stack to transform data scientists into agentic architects, unifying development, real-time data access, and production-grade agent deployment. Enhancements to Colab Enterprise notebooks add native SQL cells, editable visualizations, and an interactive Data Science Agent that can orchestrate BigQuery ML, DataFrames, and Spark workflows. The Lightning Engine is now generally available to accelerate Spark, while previews for stateful BigQuery continuous queries and autonomous embedding generation bring real-time streaming and vector search into analytics. A 'Build-Deploy-Connect' toolkit, including the Agent Development Kit, MCP Toolbox, and Gemini CLI extensions, helps move notebook prototypes into secure, scalable agent fleets.

🔧This wrap-up of the Agent Factory series lays out a repeatable blueprint for designing and deploying enterprise-grade AI agents and introduces the agentic web stack. It catalogs eight essential components—communication protocols, discovery, identity and trust, tool invocation, orchestration, telemetry, memory, and governance—and positions Azure AI Foundry as an implementation. The post stresses open standards such as MCP and A2A, emphasizes interoperability across organizations, and highlights observability and governance as core operational requirements.

🔧 Microsoft outlined a set of agentic AI tools to speed migration and modernization across applications and data. GitHub Copilot now automates Java and .NET upgrades and end-to-end app modernization flows, while Azure Migrate adds AI-driven guidance, connected Copilot workflows, and broader application-awareness. The Azure Accelerate program pairs expert deployment support and funding to reduce friction and help teams move projects faster.

🤖 Amazon Web Services announced the Nova Act extension, embedding the agent development workflow directly into popular IDEs such as Visual Studio Code, Kiro, and Cursor. The extension unifies natural-language script creation, fine-grained scripting controls, and integrated browser testing into a single interface, reducing context switching across tools. Built on the Nova Act SDK (research preview since March 2025), the extension is available today from IDE extension marketplaces and the project’s GitHub repository includes documentation and examples to get started.

⚠️ Agentic AI is proliferating inside enterprises, embedding autonomous agents into development, customer support, process automation, and employee workflows. Security experts warn these systems create substantial visibility and governance gaps: organizations often do not know where agents run, what data they access, or how independent their actions are. Key risks include risky autonomy, uncontrolled data sharing among agents, third-party integration vulnerabilities, and the potential for agents to enable or mimic multi-stage attacks. CISOs should prioritize real-time observability, strict governance, secure-by-design development, and cross-functional coordination to mitigate these threats.

🚀 The Gemini CLI is an open-source, agentic command-line assistant built to reason, select tools, and execute multi-step developer workflows while keeping users informed. In a recent Agent Factory episode, creator Taylor Mullen discussed the project's origin, design philosophy, and roadmap. Demonstrations showed onboarding to codebases, converting research papers into interactive explainers, and creating reusable slash commands. The team emphasizes extensibility, transparency, and community-driven contributions.

🛠️ Vertex AI Agent Builder is a unified platform for building, grounding, and deploying production-grade AI agents, designed to move organizations from prototype to scalable, secure services. It centers development on five pillars: Agent frameworks, Model choice, Tools for taking actions, Scalability and performance, and Built-in trust and security, and supports the Agent Development Kit (ADK) and third-party models including Gemini 2.5 Flash Pro. The platform offers managed runtime features such as sandboxed code execution, Agent-to-Agent collaboration, Bidirectional Streaming, and a streamlined one-line path from ADK prototype to Agent Engine deployment, while enterprise controls like VPC-SC and CMEK address compliance and data protection.

🤖 Mr. Cooper partnered with Google Cloud to develop CIERA, a modular agentic AI framework that assembles specialized agents to support mortgage servicing representatives and customers. The design assigns distinct roles — orchestration, task execution, data retrieval, memory, and evaluation — while keeping humans in the loop for verification and personalization. Built on Vertex AI, CIERA aims to reduce research time, lower average handling time, and preserve trust and compliance in regulated workflows.

🚀 Google Cloud highlights how its differentiated AI tech stack is accelerating startup innovation worldwide, with nine of the top ten AI labs, most AI unicorns, and more than 60% of generative AI startups using its platform. Startups are leveraging Vertex AI, TPUs, multimodal models like Veo 3 and Gemini, plus services such as AI Studio and GKE to build agents, generative media, medical tools, and developer platforms. Programs like the Google for Startups Cloud Program provide credits, mentorship, and engineering support to help founders scale.

🔒 Zscaler's annual ThreatLabz Ransomware Report (April 2024–April 2025) warns of a marked rise in extortion-focused attacks: incidents increased 146% year-over-year while exfiltrated data grew 92%. The vendor attributes this to a strategic shift from pure encryption to data theft and public shaming, with criminals using stolen files as leverage. Researchers also report that generative AI is increasingly incorporated into attackers' playbooks to enable more targeted and efficient campaigns. The U.S. accounted for half of all recorded attacks, Germany saw a nearly 75% rise and is the EU's most affected country, and the most-targeted sectors were manufacturing, technology and healthcare.

🔒 Azure outlines a layered blueprint for building trustworthy, enterprise-grade AI agents. The post emphasizes identity, data protection, built-in controls, continuous evaluation, and monitoring to address risks like data leakage, prompt injection, and agent sprawl. Azure AI Foundry introduces Entra Agent ID, cross-prompt injection classifiers, risk and safety evaluations, and integrations with Microsoft Purview and Defender. Join Microsoft Secure on September 30 to learn about Foundry's newest capabilities.

🧰 MCP Toolbox now includes comprehensive Firestore tools that let AI assistants connect directly to Firestore from environments like Gemini CLI and other MCP-compatible interfaces. Built on the Model Context Protocol, these pre-built tools support document reads, collection queries, targeted updates, and security-rules validation to accelerate debugging, testing, and maintenance for NoSQL applications. Developers can perform complex queries and targeted updates in natural language, validate security rules before deployment, and reduce context switching between consoles and emulators. The release is accompanied by docs, quick start guides, a GitHub repo, and community channels to help teams adopt the features quickly.