Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Confidential and sensitive data moves across the dark web every second of every day, and that stolen data has become a reliable fuel source for breaches. In 2025, reports from Cybernews revealed that researchers had uncovered roughly 16 billion exposed credentials and that artificial intelligence (AI) now accelerates what attackers can do with that data once they have it.

Organizations keep their databases behind firewalls for a reason: the data inside is the data they can least afford to lose. A new class of AI middleware–Model Context Protocol (MCP) servers–exists specifically to reach into those protected systems on an AI model's behalf. One of them, DBHub, connects directly to SQL databases.

Shadow IT used to mean employees spinning up unsanctioned software-as-a-service (SaaS) apps that stored company data without approval. Today, shadow MCP and unsanctioned LLM integrations represent the next evolution, and they're more dangerous. Model context protocol (MCP) servers don't merely store data; they act on it, executing code, calling APIs, and accessing internal tools on behalf of AI agents that developers connect with a config file.

Higher education institutions are the most targeted sector for cyberattacks. Yet the teams responsible for managing that risk often face a structural disadvantage: they’re accountable for a vendor ecosystem they can’t fully see. Academic autonomy and the scale of university operations mean that vendors enter the institution through departments, research groups, and administrative teams before InfoSec has full visibility. This challenge is built into how higher education operates.

Higher education institutions don’t run on a single vendor ecosystem. They run on dozens of overlapping ones. Teaching, research, identity, payments, student services, cloud infrastructure, alumni engagement, and campus operations all rely on different third-party vendors. These often enter the institution through departments and administrative teams before InfoSec becomes aware of them. This is the operational reality that higher education TPRM software addresses.

A threat intelligence platform (TIP) is the software layer that bridges the gap between raw threat data and your team's security decisions. It aggregates signals from open, deep, and dark web sources, normalizes indicators of compromise (IOCs), enriches them with context like reputation scores and malware family attribution, and maps adversary tactics, techniques, and procedures (TTPs) so analysts can act instead of investigating.