Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

‍Last updated: August 20, 2026‍ A supplier breach or a tough question from a regulator can force a rushed third-party risk management (TPRM) evaluation. You need an answer before the next steering meeting. This list compares the 12 best third-party risk management tools in 2026, based on the capabilities that separate them in daily use, so you can shortlist faster. Whether you're an analyst running early research or a CISO approving the budget, you're working from the same criteria.

Most organizations experience a strange DNS problem at some point: The same domain name means something different depending on who's asking for it. For example, a single internal app, workspace.company.com, might need to serve a locked-down instance to finance, a live staging build to engineering, and a stable production build to support — all under one domain and from the same DNS server.

Top tips is a weekly column where we highlight what's trending in the tech world and share practical ways to navigate these shifts. This week, we're looking at spear-phishing: how cybercriminals weaponize social engineering, why your natural instinct can act as a security blind spot, and practical steps to verify suspicious requests before you take action. I would like to make a confession: I’m a well-versed tech expert, but I almost fell for a phishing scam.

Quantifying cyber risk in an enterprise IT environment starts from frequency. Incidents of a given type happen at some rate, that rate is observable across enough organizations to be estimated, and severity follows from what was affected. ‍ Operational technology inverts both halves. Frequency data barely exists, and the consequences are already documented in detail by people who have never thought about cyber. Working with that inversion rather than against it is what makes the modeling tractable.

Gartner predicted in mid-2025 that more than forty percent of agentic AI projects would be canceled by the end of 2027, citing escalating costs, unclear business value and inadequate risk controls. Treat the figure as a forward-looking estimate rather than a measurement, since canceled projects tend to be quietly renamed, absorbed or left to lapse rather than formally closed. ‍

Organizations have invested heavily in technologies that detect suspicious activity. Yet insider incidents continue to rise, and security teams are often left to investigate isolated alerts without sufficient context to determine whether an event poses a meaningful risk. Behavioral analytics helps close that gap.

AI coding tools help developers build and deploy LLM applications quickly, but this speed comes with new security risks. Traditional static application security testing (SAST) tools that are pattern based weren’t designed to detect LLM-specific issues such as prompt injection sinks and exposed system prompts. These vulnerabilities often don’t become apparent until applications are already running in production, when remediation is more difficult and expensive.

Security and engineering teams contend with a constant stream of signals about vulnerabilities, incidents, misconfigurations, identity risks, control gaps, and other findings across their environments. But an individual finding’s severity does not always reflect its potential organizational impact.

A security operations center is a centralized function that continuously monitors, detects, investigates, and responds to cyber threats across an organization's environment. The global SOC market was valued at USD 42.85 billion in 2024 in one estimate and is projected to reach USD 91.88 billion by 2034, while another estimate places it at USD 52.3 billion in 2025 with a projection of USD 130.2 billion by 2034 (market estimate).