The rise of AI has had a seismic impact on the digital threat landscape—but its implications for data storage and retention are often overlooked.
Shadow AI is the new “known unknown,” and it lives inside every modern enterprise. Legacy cyber products won't secure AI; only AI built to govern AI can.
Though it is not yet a matter of official policy, inside sources indicate CISA is weighing a three-day deadline for fixing critical vulnerabilities in federal government systems that have been observed being exploited elsewhere.
Most of the conversation around AI in cybersecurity focuses on how attacks are getting faster and more sophisticated. That is true, but it misses a more immediate issue. Many security teams are still operating in ways that assume a much slower threat environment.
As data is continuously collected and acted upon, transparency becomes the mechanism through which organizations demonstrate responsible stewardship. In a world where technology acts on behalf of the consumer, trust becomes the ultimate differentiator.
A new vulnerability chain discovered by Oasis Security can compromise the Claude AI chatbot and does not require the target to have the app installed or even have an account with the service. The attack chain instead begins with a malicious webpage doctored up to place highly in search results for Claude, which passes the user to a pre-filled chat URL that exploits other vulnerabilities in the AI agent.
Wall Street is now demanding evidence of product uptake and pathways to profitability—and Microsoft is stumbling. The company’s latest earnings report led to a large drop in share prices, as investors and analysts raised concerns about its massive spending on AI infrastructure without the kinds of tangible returns that a really valuable product should demonstrate.
As we enter 2026, AI-native automation is fundamentally reshaping telemetry pipeline management. As a result, around 80% of configuration tasks currently hand-built by Observability/Security teams will be automated, transforming the roles of those teams from builders to strategic drivers.
For fraud and AML leaders, the solution isn’t choosing between technology and people, but rather empowering teams with the right technology. AI agents are the key to this transformation with the ability to supercharge fraud and AML teams across end-to-end workflows with human-in-the-loop control.
As AI continues to accelerate how quickly attacks can change, defenses built on static assumptions will continue to fall behind. Detecting intent does not eliminate that challenge, but it offers a way to keep pace by focusing on the one thing attackers cannot easily randomize. The path they have to take.
