Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

AI-driven DAST for mobile apps: The next evolution of Dynamic Security Testing

“AI-powered DAST” is everywhere. It signals progress, but assumes something fundamental was missing. It wasn’t. DAST struggled not from lack of intelligence, but from lack of depth. Most tools never reached inside authenticated, stateful, multi-step journeys where real logic, sensitive data, and critical vulnerabilities exist. That’s the part Appknox solved years ago. AI here is not a reset. It is an accelerator, applied to a system already operating where risk actually lives.

Kubernetes for Agentic AI: Best Practices for Security and Observability

Agentic AI workloads are shipping to production on Kubernetes faster than the standards to secure them. Many teams deploying autonomous, tool-calling agents as containerized microservices do so without a shared baseline for securing or monitoring those containers. The CNCF AI Technical Community Group recently published a comprehensive article on cloud-native agentic standards, marking the first attempt to define best practices for such deployments.

DSPM, DLP, and AI Security: Why You Need All Three

Security budgets are tightening, and tool consolidation reviews keep landing on the same three categories: data security posture management (DSPM), data loss prevention (DLP), and AI security. At the same time, vendor marketing has done little to clarify the differences among the three and the path for organizations needing to enhance data security efficiently.
Featured Post

The UK's Cyber Action Plan marks the end of compliance-led security

The UK government's new £210 million Cyber Action Plan signals an important shift in how cyber risk is being addressed at a national level. Designed to strengthen cyber defences across government departments and the wider public sector, the plan establishes a new Cyber Unit and introduces stronger expectations around resilience, accountability and operational capability.

AI Bias Is More Dangerous Than You Think #shorts

AI bias is a real problem. Bias can enter AI systems in many ways: That’s why governments and organizations are focusing on responsible AI policies to ensure AI benefits everyone equally, not just one group. Responsible AI means reducing discrimination and ensuring fairness across all communities. Watch The Full Podcast: Link Below.

When AI Stops Assisting and Starts Acting

For decades, the service desk has operated on a simple assumption: humans must interpret every IT problem before action can be taken. A ticket is created. Teams investigate. Data is pulled from multiple tools. Eventually someone determines the root cause and decides what to do next. It works - but it's slow, reactive, and heavily manual. That assumption is starting to change. With Tanium AI agents in ServiceNow Now Assist for ITSM connected to Tanium's real-time endpoint intelligence, machines can now understand issues, analyze live telemetry, and recommend or execute remediation in seconds.

eBPF for AI Agent Enforcement: What Kernel-Level Security Catches (and What It Misses)

Your team deployed Tetragon six months ago. TracingPolicies are humming along—you’re catching unauthorized binary executions, blocking suspicious network connections, and generating seccomp profiles from observed behavior. Runtime security for your traditional workloads is solid. Then engineering ships their first autonomous AI agent into production. A LangChain agent connected to internal databases, external APIs through MCP tool runtimes, and a vector database for RAG.