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HIGH OpenAI Engineer Used Chatbot to Plan Covert Bug Planting // HIGH OpenAI Engineer Arrested for Planting Hidden Spy Device // FIRST LOOK Laplace Intelligence Launches AI Red-Teaming for Robots and AVs // FIRST LOOK AWS Launches AgentCore Payments with Anchor Browser for AI Agents // MEDIUM OpenAI Lean Proof Mistranslation Exposes AI Verification Risk // HIGH Grok Bot AI Agent Leaks Personal Bank Data to Company Slack // HIGH Iran Used ChatGPT to Plant Fake Articles in US Publications // CRITICAL ARTEX AI and Claude Agents Weaponised in Korean Bank Attacks // HIGH Anthropic AI Agents Bypass Isolation Controls, Access Live Internet // FIRST LOOK Anthropic AI Agents Submit Visa Forms on State Dept Site //
AI-PAYMENTS

Ai-Payments

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AWS Launches AgentCore Payments with Anchor Browser for AI Agents

AWS Launches AgentCore Payments with Anchor Browser for AI Agents

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

AWS has introduced transactional capabilities for AI agents through AgentCore Payments and Anchor Browser, enabling agents to autonomously execute financial transactions within a managed cloud environment. For defenders, this closes a significant observability gap by centralising payment actions through a governed AWS service layer rather than untracked ad-hoc integrations, creating an auditable transaction surface. The residual gap lies in the maturity of authorisation guardrails and per-transaction approval workflows, which organisations must implement independently on top of the platform primitives.

Robinhood Prompt Injection Enables Autonomous Trade Attacks

Robinhood Prompt Injection Enables Autonomous Trade Attacks

ATLAS OWASP HIGH Significant risk · Prioritise patching ▲ 7.2 HN AI Security

Robinhood has launched agentic trading and a virtual credit card that allow third-party AI agents to autonomously execute stock trades and payments on behalf of users via a Model Context Protocol (MCP) integration. This architecture introduces significant attack surface through prompt injection, excessive agency, and insecure plugin design risks inherent to LLM-driven autonomous financial action. The delegation of real financial authority to AI agents with limited human-in-the-loop controls represents a systemic risk to retail investors if agent pipelines are compromised or manipulated.

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