Organizations are rapidly adopting AI assistants, copilots, and agentic AI tools to improve productivity, automate workflows, summarize information, and interact with enterprise applications. These tools are powerful because they can access emails, calendars, documents, browsers, internal systems, APIs, and business data. That same power introduces a new risk: Promptware. Promptware is a form of prompt-driven malicious behaviour where an attacker uses text, documents, emails,

AI is changing how security teams think about threat modeling. Traditionally, threat modeling has depended heavily on manual review: architects document systems, security teams inspect data flows, reviewers identify risks, and risk owners decide what must be remediated or accepted. That work is valuable, but it can be slow, inconsistent, and difficult to scale across many applications, cloud environments, APIs, data flows, and third-party integrations. NorthernCiX has put for

AI is quickly moving from experimentation into core risk and security workflows. One area where this is especially powerful is threat modeling. An AI-assisted threat modeling platform can accelerate architecture review, identify potential threats, map evidence to risks, suggest controls, and support risk decisions. But this also creates a governance challenge: what happens when AI starts influencing how risks are identified, assessed, scored, and accepted? This is where the t