All news with #agentic ai tag

🔒 Microsoft announced major AI upgrades for Sentinel SIEM and Security Copilot, positioning them as agentic platforms. The update makes Sentinel data lake generally available and introduces public-preview releases of Sentinel graph and the Sentinel Model Context Protocol (MCP) Server so AI agents can access and act on SIEM data. Customers can now build custom agents with natural‑language prompts and discover third‑party agents via a revamped store. Microsoft positions agents to automate investigation and response but warns of increased noise, false positives and a new attack surface.

🧭 The AWS API MCP Server v1.0.0 enables foundation models to interact with AWS APIs via natural language by generating and executing syntactically correct CLI commands. This release reduces startup time and removes local dependencies by converting the suggest_aws_command tool into a remote service, and adds streamable HTTP transport alongside stdio. Security and governance are strengthened with improved secure file system controls, better input validation, configurable denials, and options to require human oversight for mutating actions. Observability is improved through CloudWatch agent log collection, and an experimental get_execution_plan tool (enabled by EXPERIMENTAL_AGENT_SCRIPTS) offers prescriptive workflows; the server is available as a container and open-source on the AWS Labs GitHub repository.

🔎 The AWS Knowledge MCP Server is now generally available, giving AI agents and MCP-compatible clients access to authoritative AWS documentation, blog posts, What's New announcements, and Well-Architected guidance in an LLM-friendly format. The GA release also adds structured knowledge about regional API and CloudFormation resource availability. The server is publicly accessible at no cost and does not require an AWS account, though usage is rate-limited. Configure MCP clients to use the AWS Knowledge MCP Server endpoint to anchor agent responses in trusted AWS context and reduce manual context management.

🤖 The Microsoft Agent Framework is now in public preview inside Azure AI Foundry, offering an open-source SDK and runtime to simplify orchestration of multi-agent systems. Developers can prototype locally and deploy with built-in observability, durability, and compliance while integrating tools via OpenAPI, Agent2Agent (A2A), and the Model Context Protocol (MCP). Microsoft also previews stateful multi-agent workflows and has contributed multi-agent tracing standards to OpenTelemetry. Responsible AI controls and a generally available Voice Live API add governance and real-time voice capabilities for enterprise scenarios.

🔒 CrowdStrike’s Fall 2025 release introduces the Falcon agentic security platform, redefining SOC operations by pairing analysts with AI agents that reason, act, and continuously learn. The release centers on the Enterprise Graph data layer and Charlotte AI AgentWorks for no-code agent creation, plus seven mission-ready agents and Threat AI for autonomous hunting and response. It also expands identity, data protection, patching, and MDR capabilities, integrates Pangea and Onum, and launches AI Detection and Response (AIDR) to secure AI workflows.

🔒 Microsoft announced the general availability of the Sentinel data lake and public previews of Sentinel Graph and the Sentinel Model Context Protocol (MCP) server. The release broadens Sentinel from a traditional SIEM into a unified, agentic security platform designed to ingest and correlate structured and semi-structured signals at scale. It is intended to give AI agents such as Security Copilot and developer tools in VS Code with GitHub Copilot richer contextual access for detection, retroactive hunting, and automated response while integrating with Defender and Purview.

🛡️ Microsoft announced expanded agentic security capabilities in Microsoft Sentinel, including the general availability of the Sentinel data lake and public preview of Sentinel Graph and the Model Context Protocol (MCP) server to enable AI agents to reason over unified security data. Sentinel ingests structured and semi-structured signals, builds vectorized, graph-based context, and integrates with Microsoft Defender and Microsoft Purview. Security Copilot now offers a no-code agent builder and developer workflows via VS Code/GitHub Copilot, while enhanced governance controls (Entra Agent ID, PII guardrails, prompt shields) aim to secure agent lifecycles.

🔍 The Hacker News piece argues that traditional, rule‑driven SOCs produce overwhelming alert noise that prevents timely, accurate incident response. It advocates flipping the model to treat incoming signals as parts of a larger story—normalizing, correlating, and enriching logs across identity, endpoints, cloud workloads, and SIEMs so analysts receive coherent investigations rather than isolated alerts. The contributed article presents Conifers and its CognitiveSOC™ platform as an example of agentic AI that automates multi‑tier investigations, reduces false positives, and shortens MTTR while keeping human judgment central.

🔒 Falcon ASPM provides continuous, code-level visibility to secure generative and agentic AI applications such as Charlotte AI. It detects real-time drift, produces a runtime SBOM, and maps architecture and data flows to flag reachable vulnerabilities, softcoded credentials, and anomalous service behaviors. Contextualized alerts and mitigation guidance help teams prioritize fixes and reduce exploitable risk across complex microservice environments.

🚀 Anthropic’s Claude Sonnet 4.5 is now generally available on Vertex AI, delivering advanced long-horizon autonomy for agents across coding, finance, research, and cybersecurity. The model can operate independently for hours, orchestrating tools and coordinating multiple agents to complete complex, multi-step tasks. Vertex AI provides orchestration, provisioning, security controls, and developer tooling, and includes Claude Code upgrades like a VS Code extension and an improved terminal interface.

🚀 Anthropic’s Claude Sonnet 4.5 is now available through Amazon Bedrock, providing managed API access to the company’s most capable model. The model leads SWE-bench Verified benchmarks with improved instruction following, stronger code-refactoring judgment, and enhanced production-ready code generation. Bedrock adds automated context editing and a memory tool to extend usable context and boost accuracy for long-running agents across global regions.

⚠️ 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.