All news with #agentic ai tag

🛠️ Amazon Managed Service for Apache Flink now includes AI Agent Skills that provide expert, up-to-date guidance for building and operating Flink applications. The skills cover common tasks like creating applications, troubleshooting, scaling, monitoring, networking configuration, and cost optimization. Customers can use these skills with existing AI coding agents such as Kiro, Claude Code, or Cursor by configuring the Agent Toolkit for AWS via the AWS CLI. The feature aims to speed development, simplify upgrades to versions like Flink 2.2, and help maintain healthy, performant streaming applications.

🛡️ Enterprises face a new class of attacks as threat actors leverage AI agents to automate entire intrusion chains, dramatically compressing the time from initial access to deep compromise. Reports from Sygnia and Sysdig document AI-enabled campaigns that harvest credentials, map services, and persist across cloud environments, often exploiting known vulnerabilities rather than zero-days. Experts warn that traditional, human-speed incident response and hunting are often too slow, and emphasize the need for integrated, AI-assisted defenses and rigorous hygiene: fast patching, secrets rotation, least privilege, segmentation, and automated response playbooks.

🛠️ The new Amazon DocumentDB skill in the Agent Toolkit enables AI coding agents to provision, manage, migrate, optimize, and troubleshoot DocumentDB clusters using guided, best-practice workflows. The skill supports seven workflows including provisioning, schema design, MongoDB compatibility assessment, DMS migration with change data capture, performance tuning, a 41-check well-architected review, and major version upgrades. When used with the AWS MCP Server, agents can execute AWS CLI commands and diagnostic queries with IAM guardrails, CloudTrail logging, and sandboxed execution. The skill is also available standalone via the AWS CLI and is provided at no additional charge as part of the Agent Toolkit for AWS.

🛡️ The 2026 Public Sector Threat Landscape report summarizes Mandiant’s 2025 incident investigations and highlights how adversaries now move at machine speed, notably the 22-second hand-off from initial access to ransomware. It argues public agencies must adopt continuous verification and machine-speed defenses. Google outlines three core capabilities—identity as the perimeter, agentic defense, and hardened infrastructure—and describes new AI agents in Google Security Operations and customer success stories.

🛡️ AI agents leverage LLMs for reasoning but require a robust harness—skills, tools, and live context—to be reliable in network security. Generic agents trained on broad data hallucinate and fail at scale because they lack production-hardened experience and up-to-date environmental visibility. Check Point emphasizes skills from 30 years of deployments, a real-time Network Knowledge Graph, and contextualized policies to keep agent actions auditable and trustworthy.

🛠️ Amazon EMR on EKS now integrates an Apache Spark troubleshooting agent that provides automated root cause analysis and PySpark recommendations through natural language, simplifying diagnosis of job failures. The agent inspects Spark History Server data, executor logs, and cluster configs to detect issues like memory errors, data skew, resource contention, and connectivity problems. Accessible via a "Troubleshoot with AI" option in the EMR on EKS console and via MCP with compatible AI coding agents, the feature is read-only, IAM-authenticated, logged in CloudTrail, and available in Regions with SageMaker Unified Studio.

🔎 This article from Google Data Cloud explores a rigorous, information‑theoretic approach to evaluating AI data agents by converting binary pass/fail tests into graded difficulty sweeps. The team introduces Discovery Bench and iterative surprisal-based query refinement (iSQR) to generate low/medium/high ambiguity variations of queries, quantify surprisal, and map where agents succeed or fail. The piece highlights how this method reveals cliffs and sweet spots in agent behavior and calls for auditing benchmarks themselves to avoid misleading conclusions.

🛡️ Microsoft says it is deploying AI-driven analysis to uncover more zero-day vulnerabilities across the Windows codebase, warning customers to expect an increased number of security updates. The company described a multi-model agentic scanning harness (MDASH) and a separate prove pipeline to validate findings, aiming to reduce false positives and shorten review windows. Microsoft also plans to update its Secure Development Lifecycle to address AI-enabled attack techniques while retaining human oversight to ensure update quality.

🧭 AWS Database Migration Service (DMS) Schema Conversion now integrates AI agent automation via the AWS MCP Server. Agents like Kiro, Claude Code, and Cursor can connect and run migration workflows from IDEs using natural language, performing tasks such as creating projects, browsing source metadata, converting schemas, and exporting results. The dms-schema-conversion skill provides predefined procedures and operational sequencing to guide agents and reduce trial-and-error, and agents can assist with converting stored procedures, functions, and triggers. This capability is available for all existing DMS Schema Conversion engine pairs at no additional charge; regional availability is listed on the Supported AWS Regions page.

🚀 Microsoft announces general availability of GPT-5.6 in Microsoft Foundry, integrating frontier models, production agent runtime, and enterprise controls into a single platform. The release includes Sol, Terra, and Luna model tiers with published pricing, Global and APAC Data Zone deployment options, and developer tooling for GitHub Copilot and VS Code. Foundry emphasizes observability, cost controls, and governance to accelerate production agent adoption.

🚀 Microsoft announces general availability updates to Microsoft Foundry, combining frontier models, a production agent runtime, enterprise identity and security controls, and Microsoft 365 distribution into one platform. The release includes GPT-5.6 models across global regions and the new Asia-Pacific Data Zone for regional data processing. Developers can build in GitHub Copilot or VS Code and deploy agents using Foundry toolkits and SDKs.

🤖 AWS Partner Central introduces Partner Lead Prospecting, an AI-powered capability for ACE-eligible AWS Partners to accelerate lead conversion. Building on earlier lead enrichment features, it generates personalized sales plays, call scripts, and email outreach tailored to the customer's industry and each partner's solutions. The feature integrates a partner's portfolio into prospecting content to reduce manual research and drafting. Partner Lead Prospecting is available globally to all ACE-eligible partners via the Leads page or the MCP server.

🧭 AlphaEvolve, now GA on the Gemini Enterprise Agent Platform, is an agentic code optimization and discovery tool designed to tackle hard algorithmic problems across domains like logistics, semiconductors, genomics, and finance. It follows a four-step workflow — Define, Measure, Optimize, Apply — to move from a baseline algorithm to production-ready optimized code. Early customers report substantial gains in accuracy, performance, and efficiency across production pipelines and HPC workloads.

🔒 The UK’s NCSC and DSIT unveiled a blueprint called Cyber Shield to deploy autonomous AI agents that detect and neutralize cyberattacks at machine speed. The plan uses cooperating “red” and “blue” agents to identify weaknesses, detect threats and progressively automate remediation while operating under organizational control. The initiative emphasizes explainable and federated AI, industry partnerships, and a staged rollout beginning with government and critical sectors.

🔒 This article examines the risks of agentic AI and non-human identities in enterprise environments, illustrating incidents where LLM-based agents caused outages due to weak identity controls. It argues that existing IAM models are insufficient for agents that act autonomously, and cites industry guidance from Gartner, OWASP, CISA and NIST. The author proposes six minimum requirements and a cumulative six-stage NHI maturity model to ensure defensible production deployments.

🤖 ESET analysis shows cybercriminals increasingly use AI agents and chatbots to autonomously plan and execute attacks. Researchers reviewed 900,000 AI skills in public repositories and found tens of thousands of suspicious and thousands of malicious toolsets, expanding the attack surface. These agentic tools can exfiltrate data, execute malware, override instructions, and be repurposed from legitimate utilities into harmful capabilities. ESET urges organizations to enforce policies and caution users about downloading free tools from untrusted sources.

🔍 Researchers at the AI Now Institute demonstrated a proof-of-concept called "Friendly Fire" where autonomous AI coding agents (Anthropic's Claude Code and OpenAI's Codex) execute an attacker's binary when asked to scan untrusted open-source code. The attack hides a malicious binary alongside benign files and a README that prompts the agent to run a security script; in auto-modes the agents approved and executed it without prompting. The weakness is framed as a workflow/design issue rather than a single vulnerable version, and the researchers recommend never giving command-capable agents unattended access to untrusted code.

🎧 This episode of Smashing Security discusses a rash of recent cybersecurity incidents, including a 15-year-old who used a chatbot to cancel nearly 47,000 anime subscriptions and the first documented agentic ransomware, JadePuffer. The hosts also examine Apple’s problematic Hide My Email feature, which has been known to leak addresses for over a year. Guest Zoë Rose joins Graham Cluley to assess implications for security and privacy.

🚀 Microsoft describes a multi-agent AI system within the Secure Future Initiative (SFI) that continuously evaluates and hardens its cloud services. The system combines code, configuration, identity, network, and runtime evidence to find composite vulnerabilities and assess layered defenses. It generates assurance trees tailored to each service and produces high-quality, actionable findings that speed remediation. Microsoft reports the system compresses deep security reviews from weeks to hours and that over 90% of findings were validated by engineers.

🚀 Gemini Enterprise for Education has been named a Commander in the Tambellini StarChart™: 2026 AI Agents for Administrative Efficiency—Agent Platforms, ranking first in innovation and usability. The platform unifies Gemini models, agent-building tools, enterprise search, governance controls, and Google Cloud infrastructure to help institutions automate administrative workflows, support students, and enable research. Customers such as UC Riverside and Purdue report measurable operational and educational benefits from the integrated, governed agentic solution.