Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Mistaking a lack of alerts for a lack of threats is a dangerous assumption. But in the world of dark web exposure, silence is rarely a sign of safety; it’s a blind spot. Relying on external alerts to discover your vulnerabilities means you are reacting far too late. Here are five questions you should answer that turn that assumption into something you can measure. If you answer "no" or "not sure," treat it as a blind spot that a dark web scan will address.

Most attack surface management (ASM) evaluations start with a name already on the table: a vendor from a G2 grid, an analyst shortlist, an inbound email, or a renewal conversation. Before you commit to a proof of concept (POC), you need to know how it compares. This page provides a capability matrix across 10 ASM vendors, followed by an honest section on each. UpGuard makes one of the platforms on this list, so every section, ours included, covers where the product isn't the right fit.

Most brand protection solutions rely on one assumption: scam activity happens on the open web. Security teams focus on catching fake domains, social profiles, marketplace listings, paste sites, and dark web forums. While that covers a lot of ground, it leaves out a major risk: the official app stores.

UpGuard Vendor Risk was built around the idea that third-party risk management (TPRM) works better when continuous risk intelligence and full lifecycle workflow execution live in the same system. That commitment has earned recognition from one of the most respected analyst firms in the industry. The IDC MarketScape model assesses vendors on both current capabilities and future strategies.

Most people don't hesitate to run a free security scan because they doubt it'll find anything. They hesitate because they don't know what the results will look like. Will it be 40 pages of raw data without context? A sales pitch disguised as a report? We'll walk through it screen by screen so you know exactly what to expect before entering a domain.

Analyzing vendor evidence is a massive undertaking, which is why more third-party risk management (TPRM) tools now offer AI capabilities that let teams upload evidence and get a faster read on a security assessment. When these capabilities come up in a vendor evaluation, the conversation almost always narrows to one question: how accurate are the AI results? A tool can answer every individual question correctly and still leave you exposed.

Apple's 2025 App Store Transparency Report states that the company blocked over $2.2 billion in fraudulent transactions and removed roughly 59,000 apps for bait-and-switch tactics: publishing one thing to gain approval, then swapping in something else once the app goes live. The year before, fraud accounted for 38,315 of Apple's 82,509 total app removals, roughly 46%, making it the second-largest removal category that year. Google's numbers point in the same direction.

Security leaders who already use the NIST Cybersecurity Framework often assume it covers AI, but it doesn't. The Cybersecurity Framework (CSF) protects the confidentiality, integrity, and availability of the systems around a model. Outcome risk from model decisions is a different job.

Most security stacks still find out about stolen credentials the hard way: when an attacker logs in with them. Sometimes the first warning sign is a customer complaint or a call from law enforcement. Dark web monitoring services for business close that gap by watching underground sources for any exposure tied to your domains, employees, code, and brand, so you can reset access before someone else gets there first.

Ask a security leader how secure their company is, and most will point to a number. A rating, maybe a grade, or a score out of some maximum that a vendor calculated for them. That number only measures half the problem. It tells you about your infrastructure: your email configuration, your encryption, what's visible on the internet. It tells you much less about whether your employees' credentials are already exposed to an attacker.