LIVE FEED
FIRST LOOK Microsoft Copilot Gains Local File Access via Hybrid Intelligence // FIRST LOOK AWS Adds Native Access Controls for RAG via Amazon Quick and Bedrock // HIGH DPRK npm Supply Chain Worm Uses Web3 C2 to Steal Cloud Keys // FIRST LOOK Rein Security Launches $25M Runtime Guard for AI Agents // HIGH APT Uses AI-Generated Lures in Google AitM Phishing on Taiwan // CRITICAL Tensorlake npm Package Hijacked by Shai-Hulud Worm // FIRST LOOK Meta Launches Open Standard to Authenticate AI Agents on the Web // FIRST LOOK Anthropic Launches 3-Tier Cyber Verification Program for AI Access // FIRST LOOK CrowdStrike Maps LLM Safety Classifier Evasion for Defenders // HIGH OpenAI Adds Training Monitors After Medicare Data Breach //
COMPLIANCE

Compliance

3 reports
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SOC 2 Framework Adapts to Cover AI Agent Identity Controls

SOC 2 Framework Adapts to Cover AI Agent Identity Controls

FIRST LOOK ATLAS OWASP MEDIUM Moderate risk · Monitor closely ▲ 7.2 BleepingComputer

A sponsored analysis by Token Security argues that SOC 2's Trust Services Criteria are hollowing out under AI agent adoption, as the framework's core assumptions about account ownership, log attribution, and access approval no longer hold when agents act autonomously under human identities. The piece closes a conceptual gap by surfacing exactly which SOC 2 controls (CC6.1–CC6.3) are most exposed, giving compliance and security teams a concrete starting point for remediation and audit scope expansion. Realising the full benefit requires auditors, certification bodies, and organisations to reach consensus on treating AI agents as a distinct identity class — maturity that does not yet exist uniformly across the industry.

AWS Brings Model-Agnostic PII Detection to LLM Pipelines

AWS Brings Model-Agnostic PII Detection to LLM Pipelines

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

AWS has published guidance and tooling for model-agnostic PII detection using large language models, enabling organisations to identify sensitive data exposure across diverse LLM deployments regardless of the underlying model provider. This closes a meaningful gap for defenders who previously lacked a flexible, provider-neutral mechanism for detecting PII leakage in LLM inputs and outputs at scale. Realising the full benefit requires integration maturity, consistent labelling policy, and operational commitment to monitoring LLM data flows in production.

The Security Analyst's Claude Code Playbook

The Security Analyst's Claude Code Playbook

DEEP SIGNAL

A practitioner's guide to deploying Claude Code in security operations — threat intelligence automation, compliance gap analysis, token management, and enterprise hardening.

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