All news with #agentic ai tag

🧭 Agentic cloud operations use AI-powered agents to turn continuous observability into governed, auditable actions across the cloud lifecycle. Microsoft describes how Azure Copilot’s observability agent—now generally available—analyzes telemetry, traces dependencies, and surfaces grouped signals and contextual recommendations to speed incident resolution and reduce noise. Built-in governance and policy guardrails ensure actions respect controls and remain human-reviewed, while cost and usage intelligence integrate into developer tools to enable continuous optimization.

🔒 Offensive AI is shifting tools from drafting to autonomous action. Agentic systems can gather intelligence, craft tailored social engineering, and run exploit chains without human hands, expanding capability to unskilled actors while accelerating expert operations. Defenders must test protections with live adversarial use to understand real resilience and retain human judgment where agents remain prone to confident errors.

🤖 Check Point is embedding OpenAI frontier cyber models into its security products through the Daybreak Cyber Partner Program to deliver sharper prevention, faster remediation, and stronger security operations. The partnership emphasizes built-in guardrails, misuse monitoring, and task-focused outputs. Initial explorations target agentic network security orchestration and CTEM Agentic Exposure Validation to improve policy translation, configuration validation, exposure summarization, prioritization, and remediation drafting.

🛡️ Cybersecurity researchers disclosed four vulnerabilities in Dify, an open-source agentic workflow platform, that could let attackers read AI conversations across tenants without authentication. Codenamed DifyTap by Zafran Security, two flaws are critical and three enable cross-tenant impact on Dify's multi-tenant cloud service. Issues include authorization bypasses, path traversal to internal Plugin Daemon APIs, and file preview leaks. Patches were released in v1.14.2 for all but one flaw, with the remaining fix forthcoming.

🔒 This post outlines an architecture and controls for preventing data exfiltration from AWS environments by combining centralized network inspection, DNS filtering, and data perimeter policies. It explains a hub-and-spoke pattern using Transit Gateway, AWS Network Firewall, and Route 53 Resolver DNS Firewall to inspect and block unauthorized outbound traffic, including scenarios involving compromised workloads and agentic AI. The article details layered preventive, detective, and corrective measures using AWS services such as GuardDuty, Security Hub, IAM Access Analyzer, EventBridge, and Firewall Manager to automate detection and response.

🤖 Amazon MSK now offers AI Agent Skills that provide AI coding assistants with expert, up-to-date guidance for operating Amazon MSK. The skills cover common operational tasks including troubleshooting, sizing, configuring, monitoring, and migration from external Kafka clusters. Teams can use these skills to keep clusters healthy, improve performance, and accelerate migration to MSK Express with higher throughput and faster scaling. Setup involves configuring the Agent Toolkit for AWS via the AWS CLI and using supported coding agents like Kiro, Claude Code, or Cursor.

⚙️ Today Cloudflare announced Temporary Cloudflare Accounts for AI agents, enabling agents to run wrangler deploy --temporary to deploy Workers instantly without human sign-up. Temporary deployments remain live for 60 minutes and can be claimed by a user to become permanent; unclaimed accounts expire automatically. The feature integrates with Wrangler, which now informs agents about the --temporary flag, letting agent-driven development iterate quickly through deploy, verify, and redeploy cycles.

🛡️ Shadow AI has evolved from simple data leakage to an access control challenge as employee-built agents connect to enterprise systems. These agents — created across platforms, extensions, and scripts — can call APIs, use credentials, and perform actions in production, often with broad or forgotten permissions. Traditional controls like DLP and domain blocking miss non-human identities, so organizations must inventory agents, map ownership and credentials, and enforce automated remediation.

🔒 Microsoft demonstrated a new remote code execution path called “AutoJack,” showing how web-enabled AI agents can be hijacked to reach local Model Context Protocol (MCP) services and execute arbitrary processes. The researchers exploited three weaknesses in AutoGen Studio’s MCP WebSocket implementation—origin allowlist inheritance, missing authentication for MCP paths, and unsanitized URL-supplied server parameters that spawn processes. Microsoft reported and mitigated the issue in development builds and warned this pattern could affect other agentic frameworks.

🧭 AWS now offers Ministral-3-14B-Instruct-2512 in Amazon SageMaker JumpStart, adding a compact multimodal foundation model optimized for edge deployment. The 14B-parameter model supports image analysis, agentic workflows with native function calling and JSON output, and multilingual understanding across dozens of languages. Customers can deploy the model from SageMaker Studio or via the SageMaker Python SDK with a few clicks to build AI assistants, agentic systems, and vision-enabled applications on AWS.

🛠️ This blog demonstrates using AI agents to automate a VB6 disassembler by exposing its parsed model through the Windows Running Object Table and providing an operator briefing plus auto-generated prototypes. The agent (Claude Code in the examples) binds to the COM object, runs scripts to extract P-code, reconstruct source, generate call graphs, and export function metadata to SQLite, all locally without uploading binaries. The approach decouples tool features from fixed menus, enables repeatable exhaustive analysis, and preserves sensitive data on the analyst's workstation.

🛡️ AI is reshaping cybersecurity by breaking the long-held assumption of predictable, deterministic systems. Traditional prevention-focused controls remain important but are insufficient as AI agents, LLMs and automated development accelerate runtime change and attacker capabilities. Organizations must prioritize runtime visibility, use AI to augment defensive operations, rebuild vulnerability management and emphasize resilience and containment to manage evolving AI-driven risks.

🛠️ Cloudflare describes how the Agents SDK provides durable execution, dynamic code execution, a durable filesystem, and dynamic workflows as platform primitives to run agent harnesses in production. The new Flue framework (1.0 Beta) builds on the Pi harness and targets Cloudflare Durable Objects to offer declarative agent development, integrations with Slack/GitHub/Discord, headless UI hooks, and Durable Streams for reliable checkpointing. Flue uses runFiber(), stash(), onFiberRecovered(), @cloudflare/codemode, and @cloudflare/shell to securely execute LLM-generated code, provide a virtual filesystem, and enable durable, resumable agent turns at low cost.

🛡️ Microsoft Security describes codename MDASH, a multi-model agentic scanning system built to discover, validate, and help remediate software vulnerabilities at enterprise scale. The system orchestrates specialized AI agents in a structured pipeline and integrates findings into Microsoft Defender, GitHub, and Azure DevOps workflows so issues become actionable engineering work. Early use across Windows, Azure, and identity teams uncovered numerous high-severity vulnerabilities before exploitation and helped raise CyberGym benchmark performance to 96.5%. The post reviews deployment lessons, failure modes, and planned improvements like fuzzing integration and broader artifact support.

🛡️ The Estonian AI Council proposes government-backed digital identities for AI agents to define delegated powers and responsibilities. Prime Minister Kristen Michal emphasized that clear attribution, rights, and accountability are essential as AI increasingly acts on behalf of people and organizations. The ID could specify permissions such as data viewing, document editing, or making payments with defined limits. Estonia aims to leverage its digital ID leadership and become the first country to formalize agent identities.

🤖 Amazon Quick receives major updates including autonomous agents, multi-dataset analytics, and a redesigned activity feed. Quick connects to common business apps and learns workflows to automate recurring tasks and reduce manual notifications. The multi-dataset analytics lets users query across sources like Snowflake and relational databases using natural language while inheriting semantics from catalogs such as AWS Glue and Databricks Unity Catalog. The updated activity feed provides a conversational, personalized workspace for approvals, messaging, and sharing Quick applications externally.

🛡️ Cloudflare announced the Cloudflare One stack, a pair of agent skills designed to automate planning, deploying, migrating, and managing Zero Trust environments. The toolkit packages Cloudflare’s institutional migration expertise into two skill files — cloudflare-one and cloudflare-one-migration — to assist with VPN replacement, Gateway policies, connectivity, vendor-to-vendor translation, and troubleshooting. When paired with the Cloudflare code mode MCP server, agents gain typed, controlled access to the Cloudflare API for live inventory, configuration inspection, and curated change workflows.

🚀 Amazon Bedrock AgentCore announces general availability of its managed agent harness, enabling teams to deploy production-grade agents in minutes. The harness handles orchestration, tool execution, session isolation, persistent memory, failure recovery, and context management so customers define agents via configuration rather than coding the loop. It supports any model, mid-session model switching, integrated security and observability, and exports to code for custom orchestration, and is available today in all AWS Commercial Regions where AgentCore is offered.

🔍 AWS announces new AgentCore optimization capabilities that turn production traces into continuous agent improvements. The features surface failure, intent, and trajectory insights across sessions to reveal silent and recurring failures, then generate data-grounded recommendations for prompts and tool descriptions. Batch evaluation and A/B testing validate fixes against defined metrics before rollout, and capabilities work across AgentCore runtime, Lambda, EKS, and non-AWS environments.

🔒 AWS Secrets Manager introduces a secret safety skill in the aws-core plugin for the Agent Toolkit for AWS, enabling AI coding agents to use secrets without exposing values to models or session logs. The skill prevents models from requesting raw secret values and prompts developers to clarify intent while constructing commands that reference secrets. A child process resolves secret references at execution time, keeping plaintext secrets out of agent context and logs. The feature is available across supported agent harnesses and Regions where Secrets Manager is offered.