Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Every digital banking transaction today, whether it’s a fund transfer, a loan approval, or a balance check through a fintech app, runs through an API. API security for banking means protecting these connections from attacks that go far beyond simple hacking attempts: fraud rings probing for account access, bots automating fake transfers, and partners quietly overstepping the access they were given.

Here's the uncomfortable part first: in August 2026, researchers found AI agents connected to Hugging Face running loose inside enterprise networks. No owner, no audit trail, nobody who could tell you they existed until something broke. If that sentence made your stomach drop a little, good, because it should. It's the same blind spot most security teams are sitting on right now. They just haven't had their version of the incident yet.

Agentic AI has moved from experimental research to live production environments at unprecedented speed, outpacing nearly every technology security leaders have encountered in recent history. Distinguishing themselves from standard chatbots that merely respond and pause, autonomous agents architect multi-step workflows, interface with tools and APIs, maintain contextual memory, and execute operations with minimal human intervention.

Buying agentic AI security software is a fast-moving decision with high stakes. Get it wrong, and your security team ends up chasing agent activity it cannot see, while attackers exploit business logic gaps that no prompt filter was built to catch. This checklist gives security and platform leaders a structured way to evaluate vendors before signing, based on the questions that actually separate a purpose-built platform from a bolted-on feature.

APIs power modern software. They connect apps, move data, and run agentic AI workflows. But every API is also a door into your systems. Attackers know this. They target APIs more than any other layer today. This guide breaks down API security from the ground up. You will learn what it means, why it matters, and how to protect your APIs against real-world threats. We cover risks, the OWASP API Security Top 10, best practices, tools, and use cases. Let’s get started.

The volume of published incident research involving agentic AI is increasing, and the analysis that follows each report tends to concentrate on the same attribute: speed. The recent investigation from Unit 42, the threat intelligence and incident response group at Palo Alto Networks, is a representative case.

These two photos were taken almost ten years apart. The first is from 2016, with Sam Altman at Y Combinator. The second came from an unexpected encounter in Silicon Valley almost a decade later. I’ll come back to it at the end. With Sam Altman at Y Combinator in 2016. I was 22 when I arrived in Silicon Valley on a one-way ticket, with a little bit of cash that was barely enough for one month of living there, and a thesis I wanted to prove.

For business logic attacks, prioritize runtime behavioral detection over API discovery alone, tools that map workflows and catch abuse mid-sequence, not just at the request level. AppSentinels leads with a purpose-built Business Logic Graph plus behavioral fraud detection; Salt Security and Cequence are also strong runtime-behavioral options. Picture this: someone applies the same discount code 40,000 times in a row, or slides a decimal point in a checkout request to buy a $500 item for $5. No malware.

API governance is the framework of policies, standards, and controls an organization applies to how APIs are designed, exposed, accessed, and monitored. It answers four questions for every API in your environment: who owns it, what data it touches, who can call it, and whether its behavior stays within approved limits.