Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Researchers recently analyzed 18,000 Claude Code configuration files pulled from public GitHub repositories. What they found was straightforward and alarming: developers are already installing mistyped, misconfigured, and near-identical MCP server names — often without realizing it. The human-error condition that makes typosquatting work was already present at scale before any attacker needed to exploit it.

We’ve established the new forensic reality: a massive 72.9% inventory gap exists between the vendors you monitor and those invisible to your security. We have seen the shortcomings of SSO and its inability to holistically monitor all the vendor applications your users engage with, along with a Shadow AI explosion that is compounding both issues. The era of procurement-only discovery is over. To secure the modern cyber workforce, we must pivot from "buying-based" to usage-based discovery.

In February 2026, researchers uncovered something that should give every security leader pause. A malware operation called SmartLoader, previously known for targeting consumers who downloaded pirated software, had completely pivoted its infrastructure. SmartLoaders new target was developers, and its new entry point was a protocol most security teams had never heard of. The payload delivered to victims: every saved browser password, every cloud session token, every SSH key on the machine.

Shadow IT refers to any technology—including hardware, software, cloud services, SaaS applications, or AI tools—used within an organization without the explicit approval of the IT or security department. Shadow IT is rarely malicious. It is usually the result of employees searching for a means of making their workflows more efficient. When sanctioned corporate tools are perceived as too slow, rigid, or complex, users often "self-serve" by adopting unvetted alternatives to meet their deadlines.

The classic tradeoff in cybersecurity has always been simple: more visibility at the cost of speed. But today, that tradeoff is breaking down. As attackers leverage AI to find and exploit vulnerabilities at unprecedented scale, the sheer volume of alerts is burying security teams. The result? An expanding exposure gap. It is taking longer than ever to triage and remediate threats, creating a dangerous window between when a tool pings and when a human in the SOC can actually take action.

There’s no way to stop the clock in cybersecurity for InfoSec teams, but you can find ways to manufacture a better way to spend their time. Tiering does just that, prioritizing your team’s most finite resource. But to start, you need better data, and most importantly, better logic to redefine how you work.

Most organizations need both a cyber-focused TPRM platform and a compliance-focused TPRM platform, but it can be difficult to see where one tool ends and the other begins. If you're currently evaluating TPRM platforms, this guide clarifies the differences between the two.

Cybersecurity doesn’t really have quiet days. Usually, it’s just long stretches of constant noise before realizing you’ve been blindsided. That blindside is a flat list of unprioritized vendors. Without a way to filter what matters when a team needs to mitigate the fallout of a crisis, a vendor inventory like this becomes a compliance-only activity that offers a false sense of security.

The thing about blanket approaches is that they rarely work or scale. The same holds true for third-party cyber risk management. Treating every provider, stakeholder, or partner with the same intensity is neither productive nor cost-effective. While defaulting to treating every vendor at the same risk level is common, it is not a resilient security strategy.

Humans have always sought to streamline productivity through the most convenient solutions available, prioritizing speed to stay ahead and gain an edge over the competition. From the assembly line to the cloud, the goal remains the same: do more with less friction. Today, that convenience is synonymous with AI. While these tools have revolutionized how we work, the reality remains that rapid innovation always comes with a hidden cost.