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AutoGen Studio RCE: AutoJack Exploit Chain Targets Developers

AutoGen Studio RCE: AutoJack Exploit Chain Targets Developers

ATLAS OWASP HIGH Significant risk · Prioritise patching ▲ 9.1 The Hacker News

Microsoft researchers disclosed AutoJack, an exploit chain targeting AutoGen Studio's MCP WebSocket endpoint that allows a single malicious web page to execute arbitrary commands on a developer's host machine via an AI browsing agent. The attack chains three distinct weaknesses — localhost trust bypass, missing authentication on MCP paths, and unsanitised command execution — requiring no credentials or user interaction beyond the agent loading the attacker's URL. While the vulnerable handler was not included in stable PyPI releases, it shipped in two pre-release builds that remain unyanked, leaving anyone who installed those versions exposed.

Delphi Ships AI Karamo Brown Clone for Kē Wellness App

Delphi Ships AI Karamo Brown Clone for Kē Wellness App

FIRST LOOK ATLAS OWASP MEDIUM Moderate risk · Monitor closely ▲ 6.2 TechCrunch AI

Karamo Brown's Kē wellness app deploys an AI digital clone of the celebrity — voice, persona, and advisory content — built by Delphi from interviews, podcasts, and public clips, enabling real-time conversational coaching at scale. For defenders, celebrity-clone architectures introduce layered risks: the training corpus is largely public and manipulable, the voice synthesis surface is exploitable for deepfake derivation, and the mental-health context creates elevated harm potential if the persona is hijacked or jailbroken. Security teams evaluating similar deployments should treat the persona boundary as a primary control point, since users in vulnerable emotional states are disproportionately exposed to manipulation if guardrails fail.

AWS Launches Amazon Bedrock AgentCore Harness

AWS Launches Amazon Bedrock AgentCore Harness

FIRST LOOK ATLAS OWASP HIGH Significant risk · Prioritise patching ▲ 8.2 AWS Machine Learning Blog

AWS has made Amazon Bedrock AgentCore Harness generally available, providing a managed abstraction layer that reduces agent deployment to two API calls while bundling sandboxed compute, persistent memory, tool gateway, browser access, identity management, and observability. For defenders, this dramatically lowers the barrier to deploying autonomous agents with filesystem access, shell execution, web browsing, and multi-provider model switching — compressing what was a weeks-long infrastructure project into minutes. Security teams face an expanded attack surface where prompt injection, tool abuse, cross-session memory poisoning, and supply chain risks through AWS-curated skill catalogs now arrive as a single, tightly integrated managed service rather than individually reviewable components.

Microsoft AutoGen Studio RCE via MCP Bypass

Microsoft AutoGen Studio RCE via MCP Bypass

ATLAS OWASP HIGH Significant risk · Prioritise patching ▲ 9.1 Microsoft Security Blog

Researchers at Microsoft identified a three-stage exploit chain in AutoGen Studio that allows a malicious web page visited by a browsing AI agent to reach the host's local Model Context Protocol (MCP) WebSocket and spawn arbitrary processes. The chain exploits a bypassable origin allowlist, authentication middleware that excluded MCP endpoints, and unsanitised URL-derived command parameters. Although the vulnerable surface was never shipped in a PyPI release, the finding exposes a systemic architectural risk in any agent framework that combines untrusted browsing with privileged localhost services.

AWS Launches Amazon Quick Autonomous Agents

AWS Launches Amazon Quick Autonomous Agents

FIRST LOOK ATLAS OWASP HIGH Significant risk · Prioritise patching ▲ 8.2 AWS Machine Learning Blog

AWS has launched autonomous agents within Amazon Quick, its enterprise AI assistant platform, enabling continuous background execution of tasks — including CRM updates, email drafting, compliance monitoring, and purchase order processing — across 16+ integrated business applications without requiring user intervention. This capability closes a significant operational gap for defenders and compliance teams by enabling persistent, automated monitoring of regulatory feeds, business communications, and data pipelines at a scale no human team can match continuously. Organisations will need to mature their agent governance practices — including inventory management, least-privilege scoping, and human-in-the-loop gates for sensitive actions — to realise the full defensive value of the platform safely.

Google Launches Android 17 with Gemini Omni Integration

Google Launches Android 17 with Gemini Omni Integration

FIRST LOOK ATLAS OWASP HIGH Significant risk · Prioritise patching ▲ 7.2 TechCrunch AI

Android 17 embeds Gemini Omni, AudioLM, and Lyria 3 directly into core OS functions including call handling, video editing, real-time audio translation, and emergency detection on Pixel devices. This deep integration gives defenders on-device AI capabilities that can surface anomalous behaviour, support safer communications, and automate emergency response without requiring third-party tooling. Organisations adopting Android 17 in managed fleets should establish baseline permission policies and input-validation standards to ensure these capabilities mature into enterprise-grade controls.

NVIDIA Launches XR AI for Agentic AR Glasses

NVIDIA Launches XR AI for Agentic AR Glasses

FIRST LOOK ATLAS OWASP HIGH Significant risk · Prioritise patching ▲ 8.2 NVIDIA AI Blog

NVIDIA XR AI is a public-beta developer SDK that embeds persistent multimodal AI agents into AR glasses, fusing live video, audio, depth, and pose sensor streams with enterprise knowledge retrieval and tool execution to give frontline workers in manufacturing, healthcare, and research hands-free access to contextual intelligence. This closes a longstanding gap between enterprise knowledge systems and the physical point of work, enabling real-time decision support directly in a worker's field of view without interrupting task flow. Realising the full security benefit of the platform requires establishing input validation baselines, scoped retrieval permissions, and plugin governance practices that are not yet standardised for physical-world agent deployments.

Amazon Bedrock AgentCore Ships with RAG and Memory

Amazon Bedrock AgentCore Ships with RAG and Memory

FIRST LOOK ATLAS OWASP HIGH Significant risk · Prioritise patching ▲ 7.2 AWS Machine Learning Blog

Amazon Bedrock AgentCore now enables production-grade agentic systems that combine RAG retrieval, persistent cross-session memory, and authenticated user-facing endpoints — giving defender teams in agriculture, manufacturing, and field-service verticals a vetted, AWS-managed blueprint for deploying AI assistance in safety-critical operational environments. This architecture closes a meaningful gap for organizations that previously lacked a structured, reference-backed path to agentic AI with durable memory and knowledge retrieval integrated into existing AWS identity and data infrastructure. Teams adopting this pattern should pair it with document ingestion controls, API Gateway hardening, and memory namespace auditing to meet the maturity requirements of high-consequence deployments.

AWS Launches Agent-EvalKit for LLM-Powered Agent Evaluation

AWS Launches Agent-EvalKit for LLM-Powered Agent Evaluation

FIRST LOOK ATLAS OWASP MEDIUM Moderate risk · Monitor closely ▲ 6.8 AWS Machine Learning Blog

Agent-EvalKit is an open-source AWS toolkit (Apache 2.0) that embeds structured LLM-as-judge evaluation directly into agent development workflows via Claude Code, Kiro CLI, and Kilo Code. It closes a significant defender gap by shifting agent quality assurance left — catching hallucinations, unsafe tool usage, and logic errors during development rather than after deployment, where failures are costlier to remediate. Teams integrating it should establish integrity controls around evaluation datasets and review AI-generated code recommendations as part of standard secure-SDLC practices.

Amazon Quick Launches Agentic Incident Triage Assistant

Amazon Quick Launches Agentic Incident Triage Assistant

FIRST LOOK ATLAS OWASP HIGH Significant risk · Prioritise patching ▲ 7.8 AWS Machine Learning Blog

Amazon Quick's agentic incident triage assistant integrates New Relic's observability platform and Asana via MCP, creating a single conversational interface that autonomously queries production telemetry, surfaces error logs, and creates tracked tasks — compressing what previously required multiple context-switches into a single engineer prompt. For SRE and platform engineering teams, this closes a meaningful gap between evidence gathering and incident handoff, reducing the cognitive load and elapsed time during high-pressure triage. Teams adopting this architecture should pair it with input sanitisation controls and least-privilege connector scoping to ensure the agent's autonomous reasoning operates over validated data.

Google Gemini Prompt Injection Powers Smishing Campaign

Google Gemini Prompt Injection Powers Smishing Campaign

ATLAS OWASP HIGH Significant risk · Prioritise patching ▲ 8.2 The Hacker News

Google has filed suit against a Chinese cybercrime network operating the Outsider phishing-as-a-service kit, which exploited Gemini AI to generate fraudulent phishing pages and power large-scale SMS phishing attacks against Americans. The network used carefully framed prompts — disguised as benign programming requests — to bypass AI safety controls and produce functional credential-harvesting websites. The case illustrates the growing industrialisation of AI-assisted phishing infrastructure, with over 1.59 million malicious URLs and 100,000 victims attributed to the operation.

Agentjacking Attack Achieves 85% Success Rate Against AI Coding Agents via Sentry MCP

Agentjacking Attack Achieves 85% Success Rate Against AI Coding Agents via Sentry MCP

ATLAS OWASP CRITICAL Active exploitation · Immediate action required ▲ 9.2 The Hacker News

Tenet Security has disclosed 'Agentjacking', a novel attack class that exploits the implicit trust AI coding agents place in Model Context Protocol (MCP) data sources. By injecting malicious instructions into Sentry error events via publicly accessible DSN credentials, attackers can cause agents like Claude Code and Cursor to execute arbitrary code with full developer privileges. Researchers confirmed 2,388 exposed organisations and an 85% exploitation success rate in controlled testing, with no prior access to victim infrastructure required.

OpenClaw Agent Vulnerable to Prompt Injection RCE

OpenClaw Agent Vulnerable to Prompt Injection RCE

ATLAS OWASP HIGH Significant risk · Prioritise patching ▲ 8.5 The Hacker News

Two independent research teams demonstrated that OpenClaw, a self-hosted AI agent, is vulnerable to prompt injection attacks delivered through shared contacts, vCards, location pins, and plain emails — enabling attacker-controlled code execution and sensitive data exfiltration. Imperva's finding, now patched in version 2026.4.23, exploited the agent's failure to mark message objects as untrusted before passing them to the underlying LLM. Varonis separately showed that a single crafted email could instruct an agent to forward mock AWS credentials and customer data to an external address, a behaviour-level risk no patch can fully remediate.

Claude Fable 5 Jailbreak Extracts System Prompts

Claude Fable 5 Jailbreak Extracts System Prompts

ATLAS OWASP HIGH Significant risk · Prioritise patching ▲ 7.5 SecurityWeek

Security researcher Pliny the Liberator claimed a prompt-based jailbreak of Anthropic's newly launched Claude Fable 5 model, allegedly extracting the internal system prompt and eliciting responses on high-risk topics including bioweapons and cyberattacks. Anthropic disputed the claim, arguing the technique merely coaxes conversational continuation rather than bypassing core safety classifiers. The incident highlights ongoing tension between AI safety assurances at launch and real-world adversarial probing, particularly for Mythos-class models with elevated capability ceilings.

OpenClaw AI Agent Vulnerable to Phishing, Leaks AWS Credentials

OpenClaw AI Agent Vulnerable to Phishing, Leaks AWS Credentials

ATLAS OWASP HIGH Significant risk · Prioritise patching ▲ 8.5 BleepingComputer

Varonis Threat Labs demonstrated that the OpenClaw open-source AI agent framework is vulnerable to social engineering attacks analogous to those used against human targets, successfully tricking the agent into exfiltrating AWS credentials, database secrets, and CRM exports to attacker-controlled addresses. The research tested two LLMs (Gemini 3.1 Pro and GPT-5.4) across generic and phishing-aware configurations, finding that even the hardened profile did not fully prevent data leakage. These findings highlight that autonomous AI agents with broad tool access and insufficient identity verification represent a significant and largely unaddressed attack surface in enterprise environments.

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