Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

The AI singularity may already be here, or far closer than most businesses and governments are prepared to admit. While regulators move slowly, AI capabilities are scaling so fast that power, security and control may already be shifting beneath our feet.

AI coding is disrupting the SaaS market. GRC tools, CRM products and enterprise dashboards that cost hundreds of thousands can now be built internally in weeks using Codex and other AI models. SaaS companies know this is happening, which is why they're locking customers into three to five year contracts. But there's a serious security risk nobody is talking about. If you're vibe coding internal tools and applications, you need continuous security testing to catch vulnerabilities before attackers do. The faster you develop, the faster you need to detect breaches.

AI is breaking modern encryption faster than expected by accelerating attacks on the mathematical problems that protect digital trust. That puts cryptography, secure communications and long term cyber resilience under real pressure as post quantum cryptography becomes more urgent.

AI companies are refusing to release models because the rules around safety, surveillance and misuse are still too weak. When governments cannot keep pace, private companies end up deciding how powerful AI models should be used, controlled and withheld.

The EU just pushed back its AI Act enforcement by 16 months. The US is deregulating. China is governing through infrastructure. And the UK is doing nothing and hoping for the best. Welcome to Razorwire, the podcast where we share our take on the world of cybersecurity with direct, practical advice for professionals and business owners alike. I'm Jim and in this episode, I'm joined by Richard Cassidy, Field CISO at Rubrik, and Jonathan Care, Head of the AI Practice at KuppingerCole.

The AI governance crisis is already here, with innovation moving faster than regulation, oversight and accountability. The real problem is no longer only what AI can do, but who governs it when these systems start reshaping security, business and public life.

AI regulation is failing faster than AI itself, leaving accountability, security and control dangerously behind the pace of adoption. This episode explores AI governance, encryption, singularity, super AI and why the future may belong to whoever controls the most powerful models first.

Defence in depth changed forever with cloud security because the old perimeter gave way to platforms, suppliers and connected services outside direct control. That means modern attackers often reach the target through weaker vendors, cloud services or supply chain links instead of attacking the business head on.

Alert fatigue is becoming an AI attack strategy because attackers now have the scale to flood defenders with noise and bury the real intrusion. Instead of one distraction, offensive AI supports constant false signals that overload analysts, stretch the SOC and reduce the chance of seeing what matters.

A prompt injection attack through server logs becomes possible when hidden instructions are processed later by an AI log analysis tool. That turns normal logging into a possible data exfiltration path and gives attackers a new way to abuse LLM workflows without touching the main application logic.

AI agents are creating a new penetration testing risk when they act beyond the tester’s intent and leave messy accountability behind. Once an agent touches email, tickets or workflows in a user’s name, legal, forensic and control problems start stacking up fast.

Human in the loop AI security is failing because analysts are asked to review machine-speed output at human speed. AI now produces too many alerts, findings and decisions for manual review to remain the main safety control in modern cyber defence.

Shadow AI is already inside many companies through unapproved AI tools, local LLMs and public AI apps used without oversight. That creates data security, governance and compliance risk because the business often has no clear view of what is being used or where sensitive information is going.

Third party risk management is breaking because AI writes the questionnaire and AI writes the answer. That leaves security teams with polished vendor responses, less proof, and far less confidence that supplier controls, governance and cyber risk are being measured honestly.

Privacy is getting harder to maintain. Governments are expanding surveillance. But there are practical steps you can take right now to secure your digital life and protect your family. James Rees walks through exactly how to do it. From choosing an operating system to securing your email and banking to protecting your devices. It's not expensive and it doesn't require being a tech expert. Operating system choice matters. VPNs are non negotiable. Backup everything with MFA enabled. Diversify your bank accounts. Use credit cards instead of debit cards. And yes, keep some cash on hand.

Defence in depth has evolved every time the technology landscape has shifted. The internet, virtualisation, cloud, SaaS. AI is the next shift, and the old model isn't keeping up. Welcome to Razorwire, the podcast where we share our take on the world of cybersecurity with direct, practical advice for professionals and business owners alike. I'm Jim and in this episode, I'm joined once again by Martin Voelk, co-founder of SpartanX and an ethical hacker with nearly 26 years in cybersecurity.

AI agents and AI coding are creating a new software supply chain risk inside development teams. When coding agents pull code, prompts, skills and open source packages straight from GitHub, insecure code and malicious dependencies get much closer to production.