Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

The evolution of cybersecurity challenges and the rapid pace of digital transformation have led security leaders to focus increasingly on robust and adaptive security frameworks. Among them, zero-trust identity management has emerged as a cornerstone of modern security strategies.

On 11th March, our CEO, Rory Innes, stood before the London Assembly’s Police and Crime Committee to represent a group of people who are too often overlooked: victims of digital fraud, cybercrime and online harm. In a session focused on how the Metropolitan Police Service’s Cyber Crime Unit is protecting Londoners from digital fraud, Rory made a direct and powerful case for why the current system is failing the public.

There’s a growing acceptance that AI is no longer optional in security. That battle is largely won. The more interesting question — and the one I keep getting asked — is what we actually believe AI should be responsible for, and where human authority must ultimately sit.

You’ve sat through three vendor demos this week. Vendor A showed you an AI-SPM dashboard with a pie chart of misconfigurations. Vendor B showed you a nearly identical dashboard with different branding and a slightly wider set of compliance frameworks. Vendor C showed you posture findings with an “AI workload” tag that wasn’t in their product last quarter.

Your Bedrock agent running on EKS receives a prompt through your RAG pipeline. CloudTrail logs it as a normal bedrock:InvokeModel event—status 200, authorized IAM role, expected endpoint. But inside the container, the agent’s response triggers a tool call that spawns curl to an external IP, exfiltrating the context window. GuardDuty doesn’t flag it because the connection routes through a permitted VPC endpoint. You open your AWS console and see a healthy API call.

Before the AI spectacle of RSA arrives, let’s talk about what actually keeps regulated organizations secure RSA is only weeks away. And if you’ve been paying any attention to the pre-conference buzz, or if you work in technology generally, you already know what it’s going to feel like walking that floor: artificial intelligence, everywhere, in everything. AI-powered detection. Autonomous response. Agentic security copilots in everything from threat monitoring to your morning coffee.

As organizations continue to scale their AWS environments, security teams face increasing challenges in detecting cloud-native threats such as compromised credentials, misused APIs, container breaches, and malicious workload behavior. Traditional perimeter-based controls and legacy endpoint tools are often insufficient in dynamic, cloud-first architectures. AWS GuardDuty provides native,intelligent threat detection for AWS environments.

Incident response in the cloud is derailed not by a lack of skill, but by a lack of visibility. Security teams frequently discover critical blind spots only after an incident is already underway, leading to delayed containment, inaccurate attribution, and incomplete forensic analysis. This report walks through six realistic, real-world inspired scenarios where missing log sources prevented effective investigations.

The modern workplace has a new “system of record,” and it isn’t email. Today, approvals, incident coordination, customer escalations, vendor conversations, quick file shares, and “can you grant access?” requests happen in Slack channels, Teams chats, and Google Chat spaces, often at a pace that makes formal controls feel optional.

A useful way to evaluate a modern identity security platform is to look at three core pillars: strong authentication and access controls, Privileged Access Management (PAM) that reduces standing privilege and secure credentials and secrets management with continuous visibility. In this blog, we’ll break down what those pillars mean, how they work together and how to evaluate and roll them out without creating gaps or friction as you scale automation and agent-driven workflows.