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FIRST LOOK Anthropic and OpenAI Open Doors to Embedded Safety Evaluators // HIGH OpenAI Reports Six Cases of Unsafe AI Model Behavior // HIGH BragJack Attack Hijacks Browser AI Agents to Steal Data // CRITICAL Agentic AI Causes First Autonomous Data Breach in Spain // MEDIUM Autonomous AI Agents Abuse Internet Access and Email Systems // FIRST LOOK Anthropic Co-Founder Calls for Mandatory AI Kill Switch Oversight // HIGH CVE-2026-39987: Marimo RCE Exploited to Breach SSH Bastion // HIGH PhantomRaven: LLM-Generated Info Stealer Built for Bug Bounty // FIRST LOOK AIUC Launches AIUC-1 Agent Certification Standard for Enterprises // CRITICAL Anthropic Exposes 200M-Exchange Model Distillation Attacks //
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AWS Launches SageMaker AI and Bedrock AgentCore Workflow Integration

AWS Launches SageMaker AI and Bedrock AgentCore Workflow Integration

FIRST LOOK ATLAS OWASP MEDIUM Moderate risk · Monitor closely ▲ 5.5 AWS Machine Learning Blog

AWS has published guidance and tooling for building agentic workflows that bridge SageMaker AI and Bedrock AgentCore, offering a unified platform for constructing, connecting, and optimising AI agents at scale. For defenders, this represents a consolidation of agentic infrastructure under a managed cloud environment where IAM, logging, and network controls can be applied consistently — reducing the sprawl of unmanaged agent deployments. Residual gaps remain around how mature an organisation's governance framework must be before the observability and access-control benefits are fully realised in production agentic systems.

AWS SageMaker Ships 100+ Inference Metrics to CloudWatch

AWS SageMaker Ships 100+ Inference Metrics to CloudWatch

FIRST LOOK ATLAS OWASP MEDIUM Moderate risk · Monitor closely ▲ 6.2 AWS Machine Learning Blog

AWS has released a deep observability layer for SageMaker AI inference endpoints, emitting over 100 metrics covering GPU health, KV cache pressure, token-level latency, and traffic distribution into a native CloudWatch Insights dashboard with PromQL-compatible export. For defenders, this centralised telemetry surface introduces new reconnaissance and exfiltration vectors: an adversary with read access to CloudWatch or connected third-party tools (Grafana, Datadog) can infer model architecture, request patterns, and capacity limits without touching the model itself. The richness of these signals also raises insider-threat risk, as operational staff now have granular visibility into inference behaviour that can be leveraged to reverse-engineer model characteristics or plan targeted denial-of-service campaigns.

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