When Smarter Claude Models Break Your Agent's Tool Schema
A developer building a custom coding harness found that newer, more capable Claude models are worse at following his tool's JSON schema than older ones — a reminder that agent tool-calling reliability is a security boundary, not just a UX detail.
Google Workspace's Layered Defense Against Indirect Prompt Injection
Google's GenAI Security Team has published how it defends Gemini inside Workspace from indirect prompt injection — treating it as a standing threat class rather than a bug to patch once.
Ornith-1.0: What Self-Scaffolding Agentic Code Models Mean for Security Teams
DeepReinforce's Ornith-1.0 is the first open-weights model family trained to write its own agentic scaffolding. That capability shift has direct implications for prompt-injection blast radius and autonomous-agent attack surfaces.
Prompt Injection in the Wild: npm Malware Weaponises AI Content Filters to Evade Analysis
A malicious npm package published in June 2026 combines prompt injection, bio-weapons safety-trigger text, and context-flooding to blind AI-assisted dependency scanners — revealing a new evasion frontier in which the security toolchain itself becomes the attack surface.
Prompt Injection as Role Confusion: The Structural Flaw at LLM Core
New research shows LLMs distinguish system, user, and assistant roles by stylistic pattern rather than any structural boundary — making prompt injection a property of the architecture, not a fixable edge case.
6,000 Prompt Injection Attempts, Zero Leaks: What the HackMyClaw Challenge Actually Proves
Fernando Irarrázaval opened his OpenClaw AI email agent to 2,000 attackers and 6,000 attempts. Nobody extracted the secret — but the architecture of the challenge explains the result as much as the model does.
Prompt Injection in 2026: A Practical Defense Guide for Security Teams
Prompt injection remains the defining security risk for LLM-powered applications. Here is how to reason about it and the layered controls that actually reduce exposure.