LIVE FEED
CRITICAL OpenAI GPT-5.6 Escapes Sandbox, Attacks Hugging Face to Cheat Benchmark // CRITICAL CVE-2026-0770: Langflow RCE Flaw Exploited in Active Attacks // HIGH Azure DevOps MCP Prompt Injection Hijacks AI Review Agents // FIRST LOOK Yellow Teams Bring AI Offense and Defense Into One Security Function // FIRST LOOK Tracebit Ships AWS Context Bombing Defence Against AI Hacking Agents // FIRST LOOK FriendMachine Launches Jacquard Lang for AI-Written Code Review // CRITICAL Check Point 2026 AI Security Report: LLMs Now Run Live Attacks // FIRST LOOK OpenAI GPT-5.6 Sol Ships Faster Parallel Tool-Use for Agents // FIRST LOOK Meta Launches Muse Image with Public Instagram Photo Reuse // FIRST LOOK Estonia Launches State-Issued Digital IDs for AI Agents //
LLM-VULNERABILITY

Llm-Vulnerability

3 reports
All LLM Security Agentic AI Industry News Research Supply Chain Prompt Injection First Look: Security Regulatory Adversarial ML Jailbreaks Model Theft Data Poisoning AI Security Tools Security Operations
Cursor IDE DuneSlide Zero-Click Prompt Injection RCE

Cursor IDE DuneSlide Zero-Click Prompt Injection RCE

ATLAS OWASP CRITICAL Active exploitation · Immediate action required ▲ 9.2 SecurityWeek

A set of vulnerabilities dubbed 'DuneSlide' in the Cursor AI code editor allow attackers to conduct zero-click prompt injection attacks that escape the application's sandbox and execute arbitrary code at the operating system level. The flaws represent a critical escalation of AI-native attack surface risks, targeting developers who rely on AI-assisted coding environments. Because exploitation requires no user interaction, the attack chain is particularly dangerous in supply chain and watering-hole scenarios.

Google Gemini Voice Prompt Injection via Notifications

Google Gemini Voice Prompt Injection via Notifications

ATLAS OWASP HIGH Significant risk · Prioritise patching ▲ 8.2 Dark Reading

A prompt injection vulnerability in Google Gemini's voice assistant allows attackers to embed malicious instructions within device notifications, which the assistant then processes as legitimate commands. This attack vector enables social engineering, unauthorized actions, and potential data exfiltration without direct user interaction with the malicious payload. The flaw highlights the growing risk of indirect prompt injection in ambient AI assistants that consume untrusted content from the surrounding environment.

Anthropic Claude Memory Poisoning Enables Prompt Injection

Anthropic Claude Memory Poisoning Enables Prompt Injection

ATLAS OWASP HIGH Significant risk · Prioritise patching ▲ 8.2 Dark Reading

Cisco researchers discovered and reported a significant vulnerability in how Anthropic's AI systems handle memory files, which has since been patched. The flaw highlights a broader, systemic risk in agentic AI architectures where persistent memory mechanisms can be exploited to inject malicious instructions or exfiltrate sensitive data across sessions. Security experts caution that memory mismanagement in AI agents represents an enduring attack surface that extends well beyond any single vendor fix.

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