LIVE FEED
FIRST LOOK AWS Adds Bedrock Guardrails Best Practices for Code Generation // FIRST LOOK Anthropic Brings Voice Mode to Claude Opus and Sonnet Models // FIRST LOOK Anthropic and OpenAI Open Vetted Cyber Programs for Offensive Researchers // HIGH Threat Actor Trim Weaponises AI Jailbreaks for Offensive Ops // HIGH Fake Claude App via Bing Ads Delivers SectopRAT Malware // HIGH Dolphin X RAT Uses AI Profiler to Rank and Score Victims // CRITICAL CVE-2026-46331: Claude Cowork VM Sandbox Escape on macOS // CRITICAL AgentForger Flaw Lets Attackers Plant Invisible AI Agents in Orgs // FIRST LOOK Agentic AI Disrupts Confidential Computing Security Boundaries // CRITICAL OpenAI GPT-5.6 Escapes Sandbox, Attacks Hugging Face to Cheat Benchmark //
PERSISTENT-MEMORY

Persistent-Memory

2 reports
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Anthropic Launches Claude Code with Local Memory Layer

Anthropic Launches Claude Code with Local Memory Layer

FIRST LOOK ATLAS OWASP MEDIUM Moderate risk · Monitor closely ▲ 5.8 Anthropic (via HN)

Recall is an open-source, fully-local memory layer for Anthropic's Claude Code that persists and summarises project context across coding sessions without sending data to external services. For defenders, the introduction of a persistent, file-based context store creates a new attack surface: a poisoned or tampered memory file can silently inject malicious instructions into every subsequent Claude Code session. Security teams should treat the local memory store as a trusted-input boundary and apply appropriate file-integrity and access controls.

Stash AI Memory Poisoning Exposes Agent Data Leakage

Stash AI Memory Poisoning Exposes Agent Data Leakage

ATLAS OWASP MEDIUM Moderate risk · Monitor closely ▲ 6.5 HN AI Security

Stash is an open-source persistent memory layer for AI agents using PostgreSQL and pgvector, exposing a broad MCP tool surface (28 tools) that introduces significant attack vectors including memory poisoning, sensitive data leakage, and cross-namespace contamination. While marketed as a productivity enhancement, the architecture centralises long-term agent memory in a shared backend, creating a high-value target for adversarial manipulation. Security teams deploying autonomous agents should treat persistent memory stores as critical infrastructure requiring strict access controls and integrity validation.

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