All news with #agentic ai tag

🚀 Cloudflare and Anthropic have integrated Claude Managed Agents with Cloudflare Sandboxes, allowing teams to run the Claude agent loop on Anthropic while Cloudflare executes code, secures connections, and provides detailed observability. A default deployment template offers enhanced security through customizable outbound proxies, sandbox metrics and logs, SSH access, and configurable sandbox images. You can choose traditional microVMs or lightweight V8 isolates to optimize for performance and cost, and use Cloudflare Mesh or Workers VPC to connect agents to private services without exposing them to the Internet.

📈 Digital.ai's 2026 Application Security Threat Report found that 87% of monitored customer-facing apps were attacked in 2026, up sharply from 55% in 2022. The firm says agentic AI has lowered the skill and time required for threat actors to inspect code, generate exploits and adapt malware. Financial services, automotive and medical device apps were most targeted, and iOS attacks have nearly closed the gap with Android.

🔒 This article outlines five architectural patterns for exposing enterprise data to autonomous systems on Google Cloud, using BigQuery examples and mocked CRM data as pedagogical blueprints. It contrasts deterministic, developer-authored SQL APIs with agentic approaches that use LLMs, platform-native reasoning like the Conversational Analytics API, and the vendor-neutral Model Context Protocol (MCP). It highlights trade-offs in trust, complexity, cost, latency, and maintenance.

🚀 Google Cloud announced streaming AI enhancements to its Agentic Data Cloud at Next ‘26, unifying Pub/Sub, Dataflow, BigQuery, Bigtable and Managed Service for Kafka to deliver real-time context and low-latency inference. These additions include Pub/Sub AI inference, BigQuery continuous queries for stateful stream processing, Pub/Sub→Bigtable subscriptions, and unified embedding sinks for immediate semantic search and agent memory. The platform also supports MCP and ADK integrations so agents can manage resources and run inside Dataflow pipelines, reducing context lag for use cases like fraud detection and autonomous supply chain actions.

🔒 The UK’s National Cyber Security Centre (NCSC) has published new guidance for organisations considering the adoption of agentic AI, summarising a wider report produced with Five Eyes partners. It flags the heightened risk from agent autonomy and complexity, including excessive access, unpredictable behaviour and actions that can outpace human review. The NCSC advises incremental deployment with tightly bounded pilots, clear ownership, ongoing monitoring and meaningful human oversight, and points organisations to industry best practice such as ETSI EN 304 223.

🤖 The Gemini Live Agent Challenge drew 11,878 participants and 1,536 submissions from 151 countries, inviting developers to build next-generation multimodal AI agents with the Gemini Live API, the Agent Development Kit (ADK), and Google Cloud infrastructure. Entries competed across three categories — Live Agent, Creative Storyteller, and UI Navigator — producing winners like ORION, drone-copilot, and Sankofa. Two category winners presented their projects at Google Cloud Next 2026 and shared insights on stage and in interviews. The post lists all winners and highlights routes for developers to continue building, including GEAR and weekly livestreams.

🔒 The article argues that security must move beyond detection and focus on compressing the OODA loop—observe, orient, decide and act—so defenses can outrun attackers. It notes that detection improvements have reached diminishing returns while investigation and remediation remain time-bound bottlenecks. By embedding contextual investigation into systems and deploying agent-based remediation, teams can make faster, more consistent decisions. As AI-driven interactions accelerate threat timelines, continuous validation and automated response become essential.

🛡️ Microsoft Security explains how rising agentic autonomy reorients security from models to how agents are assembled, constrained, and governed inside applications. The post identifies amplified risks—agent hijacking, intent breaking, data leakage, supply chain compromise—and shows why the application layer is decisive because builders fully control permissions, tool access, and failure handling. It recommends concrete design patterns: agents as microservices, least permissions, deterministic human-in-the-loop, and distinct agent identity to limit blast radius and preserve auditability.

🛠️ The AWS Transform agentic AI assistant is integrated into the AWS Toolkit for Visual Studio, giving .NET developers an in‑IDE, conversational workflow to assess, plan, and execute application modernization. It provides visibility, checkpointing, interactive diffs, automatic build-fix attempts, detailed worklogs, and downloadable HTML reports while preserving context between the web console and Visual Studio. Agents are also accessible via Kiro and other AI coding environments and are available in multiple AWS Regions.

🔒 Semperis finds that 93% of global organizations use or plan to use AI agents for security tasks such as password resets and VPN access, while 92% report AI on endpoints with SSH and encryption key access. The survey of 1,100 organizations warns of over‑permissioned and abandoned 'zombie' non‑human identities that increase hijack risk. Semperis recommends treating agents as NHIs, enforcing least‑privilege, and improving observability and recovery readiness.

🔒 Palo Alto Networks has unveiled Idira, an identity security platform designed to protect human users, machine identities, and autonomous AI agents by applying dynamic privilege controls across all identity types. The platform leverages Palo Alto’s integration of CyberArk and continuously discovers and enriches identities across SaaS, cloud, and developer environments. Idira elevates privileges only when required and revokes them immediately, aiming to close blind spots left by legacy IAM and PAM systems. Analysts say it targets gaps in offerings such as Auth0 and SailPoint but does not eliminate the need for layered security.

🔒 Microsoft released its May Patch Tuesday fixing 120 CVEs, including 17 critical flaws. The update addresses 14 RCEs, two elevation of privilege bugs and one information disclosure issue, with the majority of fixes covering EoP and RCE types. Microsoft credited its WARP team and an agentic AI system, MDASH, with discovering 16 of the issues. Administrators are urged to prioritize high-risk fixes such as CVE-2026-41089.

🔒 Microsoft researchers describe an AI-driven pipeline that translates attacker TTPs into realistic, structured security logs to accelerate detection engineering. The approach uses prompt engineering, collaborative agentic refinement, and data augmentation to generate semantically accurate telemetry (command lines, process ancestry, fields) without exposing sensitive customer data. Evaluation across multiple datasets shows agentic workflows and reasoning models notably improve recall and fidelity compared to prompt-only methods.

🔔At SAP SAPPHIRE, Google Cloud and SAP introduced a Unified Data Foundation to connect SAP business data directly into BigQuery and enable agentic AI workflows. Announcements include BDC Connect for BigQuery GA with zero-copy access, new 48TB X5 memory-optimized instances, a SecNumCloud-qualified Sovereign Cloud with S3NS, and Google SecOps for SAP in preview. The new Cortex Framework preview aims to accelerate building agentic solutions while maintaining enterprise governance and reducing data movement.

🔐 Agentic AI is already operating across enterprises, executing tasks and taking actions often without meaningful security involvement. Security teams must develop hands‑on fluency — build and test agents, understand integrations like the Model Context Protocol, and enforce scoped configurations — because policy alone won't close the gap. The piece distinguishes three agent classes (productivity, MCP‑connected vendor agents, and custom user agents) and emphasizes configuration, access scoping, and training such as SANS SEC545 to reduce exposure.

🔐 At Google Cloud Next, Google outlined a resilient, scalable, and secure foundation to accelerate public sector adoption of the agentic era, highlighting infrastructure, data, and security innovations. Key infrastructure announcements include the AI Hypercomputer with eighth-generation TPUs (TPU 8t for training, TPU 8i for inference) and Virgo Networking, plus Google Distributed Cloud bringing Gemini to where data resides. On data, an AI-native architecture features Knowledge Catalog (FedRAMP High, DoD IL4 & IL5) and a cross-cloud Lakehouse to ground agents in trusted context. Security advances combine Google Threat Intelligence with Wiz, authorize Cloud Armor and Model Armor, and add defensive agents to protect models and sensitive data.

🔒 OTT Cybersecurity LLC — the team behind Lyrie.ai — announced acceptance into Anthropic’s Cyber Verification Program and the public release of the Agent Trust Protocol (ATP). ATP is an open cryptographic standard that enables real-time verification of an AI agent’s identity, authorized scope, attestation status, delegation, and revocation. The protocol is royalty-free, slated for IETF submission, and a reference implementation is published under an MIT license. Lyrie positions itself as the security layer for autonomous AI agents operating on the internet.

🛡️ Traditional purple teaming is failing because human handoffs and siloed toolchains make detection-to-fix cycles far slower than modern attackers. The author documents a collapse in the vulnerability-to-exploit window—from 56 days in 2024 to roughly 10 hours in early 2026 across CISA KEV, VulnCheck KEV, and ExploitDB—and warns that AI-assisted adversaries can act in seconds. Autonomous purple teaming pairs automated penetration testing, Breach and Attack Simulation, and AI-powered mobilization agents to close the loop at machine speed, converting red findings into blue tests and auto-deploying low-risk fixes while keeping every step auditable.

🤖 DXC Technology, Accenture, and other organizations are actively retraining SOC teams to integrate agentic AI by embedding vendor experts and building secure sandboxes. CISOs emphasize top-down leadership, rapid experimentation, and formal learning tracks to shift mindsets and roles. Governance, humans-in-the-loop, and clear escalation and audit paths are required while agents take on L1/L2 tasks.

🔒 Model Context Protocol (MCP), the emerging plugin layer for agentic AI, has become a significant blind spot for security teams, introducing new shadow-AI risks much like shadow IT. CTEM programs can close this gap by extending scoping, discovery, prioritization, validation and mobilization to cover developer workstations, AI toolchains and MCP server configurations. Practical actions include actively enumerating MCP endpoints, scanning agent configuration and markdown context files for hardcoded API keys, and prioritizing exposures by attacker impact to produce actionable remediation tickets for engineering teams.