Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

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.

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.

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.

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.

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.

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.”

Today’s IT leaders face a non-stop escalation of stealthy cyberattacks designed to hold organizations hostage. The dialogue has shifted from if you will be compromised to when. The financial stakes are incredibly high. According to a 2024 study by Splunk and Oxford Economics, “outages cost businesses over $400 billion in revenue each year.” For many Technology decision-makers, the instinct is to rely on traditional disaster recovery plans.

Cybersecurity tools and procedures were designed to provide full defence against predictable threats that followed patterns that would raise alarms. Familiar CAPTCHAs, IP blocks, browser checks, browser fingerprinting, and login restrictions would provide a protective layer for businesses to ensure only genuine users were using their website, or app, or API responsibly. This layer of cybersecurity used to distinguish human from bot.

In almost every major enterprise, Jira and Confluence are the default operating systems for innovation. They hold your organization's most vital intelligence, from product roadmaps to financial planning. Yet, while companies invest billions in fortress-like perimeter security, firewalls and VPNs, to keep external attackers out, they often ignore the fragility of their internal collaboration environments.