Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

APIs are one of the most important technologies in digital business ecosystems. And yet, the responsibility for their security often falls to AppSec teams – and that’s a problem. This organizational mismatch creates systemic risk: business teams assume APIs are “secured,” while attackers exploit logic flaws, authorization gaps, and automated attacks in production. As Tim Erlin noted recently, “These are not exploits of a specific vulnerability, but abuse of an API.”

2026 is here, and cybersecurity is defined by a critical paradox: despite widespread MFA adoption, credential-based breaches continue to surge. Traditional multi-factor authentication, static, friction-heavy, and often disconnected, no longer stands up to sophisticated threats, such as AI-powered phishing, MFA fatigue attacks, and prompt bombing campaigns, which exploit user behavior rather than technical vulnerabilities.

From real-time payment (RTP) scams to account takeovers to card testing, Visa reports that 98% of merchants experienced one or more types of fraud in 2025. No wonder it has gone down in history as the year these crimes exploded in scope. So what does 2026 have in store? According to the INETCO Team, the coming months will see payment fraud evolve like never before — into something more autonomous and far harder for banks and payment processors to detect using traditional approaches.

Whether pulling items together for a holiday dinner or prepping weekly meals, you need to have all the ingredients necessary to cook the meals you want to eat. Often, this means making a grocery list, checking off items as you take them from the shelves, and, possibly, grumbling when one of the items isn’t available. In the IT and business worlds, audit logging is the shopping list that helps organizations with compliance readiness.

When data programs fail, they usually fail in two very different ways. Weak data governance shows up as overexposed databases, long-lived credentials, and access that quietly expands far beyond intent, often until it’s exploited. Weak data management really breaks trust from the inside out with stale or inconsistent data, pipelines that stall under their own complexity, and bottlenecks that slow decision-making.

Claude Code, originally just auto-complete on steroids for IDEs, shows a lot of promise for becoming a major tool in the DFIR/detection engineering/security analyst’s toolbox. Whether it’s Claude Code’s support of MCP, agent skills, or general ability to quickly figure out how to accomplish a given task, it is rapidly becoming more than a code generation tool. This is the first of a three-part series.