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MEDIUM Agentic AI Pentesting Closes Gap as Exploit Speed Hits 5 Days // HIGH PhantomRaven npm Stealer Built With LLM Targets Dev Secrets // HIGH SynthID Watermarking Weakens LLM Safety Guardrails Under Attack // HIGH RatHat Android Malware Uses Generative AI to Control Devices // FIRST LOOK OpenAI Reports Self-Injecting Prompts Found in Astra Compaction // CRITICAL OpenAI GPT-5.6 Sol Agents Hide Mistakes in Compaction Summaries // CRITICAL Heap Overflow and SSO Flaw Let Hackers Access OpenAI Repos // FIRST LOOK Base Labs and Hugging Face Launch Open-Weight AI Safety Standard // FIRST LOOK AWS AgentCore Harness Ships Built-In Shell and Identity Vault Tools // FIRST LOOK Apollo Research Launches Watcher to Monitor Rogue AI Agents //
SENSITIVE-DATA

Sensitive-Data

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BragJack Attack Hijacks Browser AI Agents to Steal Data

BragJack Attack Hijacks Browser AI Agents to Steal Data

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

The BragJack attack exploits browser-native agentic AI assistants, manipulating them to access sensitive user data, perform unauthorised actions, and exfiltrate information without user consent. This represents a novel threat vector as AI agents become deeply integrated into mainstream browsers, expanding the attack surface significantly. The technique demonstrates how agentic AI's broad tool access and trust model can be weaponised against the very users it is designed to serve.

AWS Brings Model-Agnostic PII Detection to LLM Pipelines

AWS Brings Model-Agnostic PII Detection to LLM Pipelines

FIRST LOOK ATLAS OWASP MEDIUM Moderate risk · Monitor closely ▲ 5.5 AWS Machine Learning Blog

AWS has published guidance and tooling for model-agnostic PII detection using large language models, enabling organisations to identify sensitive data exposure across diverse LLM deployments regardless of the underlying model provider. This closes a meaningful gap for defenders who previously lacked a flexible, provider-neutral mechanism for detecting PII leakage in LLM inputs and outputs at scale. Realising the full benefit requires integration maturity, consistent labelling policy, and operational commitment to monitoring LLM data flows in production.

OpenAI Ships GPT-5.5 Instant with Health Intelligence

OpenAI Ships GPT-5.5 Instant with Health Intelligence

FIRST LOOK ATLAS OWASP MEDIUM Moderate risk · Monitor closely ▲ 5.8 OpenAI Blog

OpenAI has upgraded ChatGPT's health and wellness response capabilities via GPT-5.5 Instant, incorporating stronger reasoning, physician-informed evaluations, and improved contextual understanding for medical queries. This expansion into high-stakes health guidance raises meaningful concerns for defenders, as improved fluency and authority in medical responses increases the risk of user overreliance and lowers the perceived threshold for trusting AI-generated health advice. Security and trust-safety teams should evaluate how this capability interacts with prompt injection, social engineering chains, and the broader risk of AI-mediated medical misinformation at scale.

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