Security Boulevard

Automated Threat Detection for Quantum-Enabled Adversarial Attacks on AI Context

Learn how to protect Model Context Protocol (MCP) from quantum-enabled adversarial attacks using automated threat detection and post-quantum security.
VentureBeat

Adversarial attacks in machine learning: What they are and how to stop them

Adversarial machine learning, a technique that attempts to fool models with deceptive data, is a growing threat in the AI and machine learning research community. The most common reason is to cause a ...
Infosecurity Magazine

Researchers Discover Major Security Gaps in LLM Guardrails

Palo Alto Networks’ Unit 42 has developed a successful attack to bypass safety guardrails in popular generative AI tools ...
PCQuest on MSN

Hidden text in PDFs may be fooling AI paper reviewers

What if a weak research paper did not need better ideas, better data, or better science: just a hidden line of text to fool an AI reviewer? That is the unsettling question behind a new ...
Morningstar

Radiant Logic Launches “Through the Eyes of the Adversary” Webinar Series Exploring Identity as the Primary Attack Surface

Radiant Logic, the pioneer of Identity Data Fabric and leader in Identity Security Posture Management (ISPM), today announced the launch of a three-part webinar series, Through the Eyes of the ...