Measures to prevent AI information leaks boil down to two main axes: do not give it away carelessly, and do not entrust it ...
AI agents are exposing gaps between identity and authority, pushing GLEIF, FIDO, iProov and others to build verifiable trust ...
AI-assisted development is increasing both the volume and velocity of code, while code verification capacity struggles to keep pace. Static analysis, software composition analysis, and infrastructure ...
AI agents cannot see the outside worldHaving AI agents write code, fix documentation, or manage tasks has already become ...
Visa's own research found only 23% of US consumers trust generative AI to handle a payment independently, even though most of ...
Overview: AI agents require infrastructure beyond traditional model APIs and chatbot frameworks.Identity, sandboxing, ...
UNDERSTAND: Measure runtime activity against the agent’s stated purpose and sanctioned scope. Orchid attaches AI readiness tags to applications, accounts, and access paths, surfacing identity hygiene ...
A newly released a proof-of-concept (PoC) for an alleged zero-day vulnerability in Muse, an AI assistant application.
Stronger monitoring, shorter-lived tokens, and tighter controls over how tokens are used after authentication are needed as ...
Banks must develop a "know your agent" framework for AI involvement in financial transactions, covering identity, ...
Readiness tagging, always-on observability, and orchestrated shutdowns at the application layer give enterprises a way to expand AI agent programs while keeping authority in check.
Explore the challenges posed by the proposed Unified Agent Protocol (UAP) for UPI payments, including fraud risks and authentication complexities for banks in India.
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