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Generative-Ai

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RatHat Android Malware Uses Generative AI to Control Devices

RatHat Android Malware Uses Generative AI to Control Devices

ATLAS OWASP HIGH Significant risk · Prioritise patching ▲ 6.2 The Hacker News

RatHat is a sophisticated Android RAT attributed to China-based threat actors that abuses Android Debug Bridge (ADB) to maintain persistent shell access even after the malware is uninstalled. Notably, the malware integrates a generative AI assistant to parse on-screen accessibility trees and autonomously direct device interactions, representing an emerging class of AI-augmented mobile threats. Its layered anti-analysis techniques and persistence mechanisms make it a significant threat to Android users targeted via smishing and malvertising campaigns.

Meta Faces Lawsuit Over Biometric Data Harvesting for AI Training

Meta Faces Lawsuit Over Biometric Data Harvesting for AI Training

ATLAS OWASP HIGH Significant risk · Prioritise patching ▲ 6.5 Wired Security

A proposed class action alleges Meta illegally extracted biometric data from Facebook and Instagram photos to train AI image-generation models (Emu and Muse Image) and to build its unreleased NameTag facial recognition system for smart glasses. The case highlights systemic risks around unconsented biometric data collection embedded in large-scale AI training pipelines, raising serious privacy and data governance concerns. The lawsuit invokes Illinois and California privacy laws, underscoring the growing regulatory pressure on AI vendors over training data provenance.

Cisco AI Agents Vulnerable to Prompt Injection Honeypots

Cisco AI Agents Vulnerable to Prompt Injection Honeypots

ATLAS OWASP MEDIUM Moderate risk · Monitor closely ▲ 7.2 Cisco Talos

Cisco Talos researcher Martin Lee demonstrates how generative AI can be used to rapidly deploy adaptive honeypot systems that deceive and study AI-driven attack agents. The technique exploits a fundamental weakness in AI agents — their lack of situational awareness — causing them to interact with simulated vulnerable systems as if they were real targets. This defensive approach shifts the paradigm from passive detection to active manipulation, giving defenders new insight into automated threat actor methodologies.

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