Anthropic’s MCP Design Flaw: How a Protocol-Level Vulnerability Enables Remote Code Execution at Scale

Anthropic’s MCP Design Flaw: How a Protocol-Level Vulnerability Enables Remote Code Execution at Scale

A critical architectural flaw in Anthropic’s Model Context Protocol (MCP) ecosystem has exposed a vast number of downstream systems to remote code execution (RCE) risks. Researchers at OX Security found the issue embedded across official MCP SDKs for Python, TypeScript, Java, and Rust — meaning developers building on MCP inherit the vulnerability by design rather than through a simple coding

Lovable AI App Builder Reportedly Exposes Thousands of Projects’ Source Code and Customer Data

Lovable AI App Builder Reportedly Exposes Thousands of Projects’ Source Code and Customer Data

A critical Broken Object Level Authorization (BOLA) vulnerability in Lovable, an AI-powered app builder, has reportedly left thousands of legacy projects accessible to unauthorized users. According to security researchers, an API endpoint returned full project data — including source code, database credentials, AI chat histories, and customer information — for projects created before November 2025. While Lovable appears to have

Rockstar’s GTA Data Leak: ShinyHunters Expose 78.6M Records via Anodot–Snowflake Pivot

Rockstar’s GTA Data Leak: ShinyHunters Expose 78.6M Records via Anodot–Snowflake Pivot

Rockstar Games confirmed in April 2026 that a third-party compromise led to a substantial exposure of analytics records tied to GTA Online and Red Dead Online. Although player accounts and payment systems were reportedly unaffected, the incident highlights how attackers are increasingly leveraging trusted SaaS integrations and stolen service tokens to pivot into high-value environments. This post unpacks the timeline,

Price Elasticity: The One Data Point That Could Clarify AI’s Impact on Jobs

Price Elasticity: The One Data Point That Could Clarify AI’s Impact on Jobs

Silicon Valley’s conversations about AI often sound like inevitabilities: sweeping automation, mass displacement, and workplaces remade by powerful models. Those scenarios have driven anxiety among workers and intense debate among researchers. But one practical problem underlies much of the confusion: we lack the right economic data to predict how AI-driven productivity gains will actually affect employment. Without that missing piece,

Anthropic’s Claude Leak: 8,000 Takedown Requests After an Accidental Source-Code Exposure

Anthropic’s Claude Leak: 8,000 Takedown Requests After an Accidental Source-Code Exposure

Anthropic has scrambled to contain the fallout after an accidental exposure of the complete source code for its Claude family of AI tools. The company issued roughly 8,000 copyright takedown requests to remove copies and adaptations circulating on code-hosting sites and mirrors, responding to a wave of reposts and forks that appeared within hours of the initial disclosure. Although Anthropic