Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

If your security team runs on Jira, sprints and backlog included, UpGuard plugs straight into it: vendor findings, breach alerts, and user risk signals can all surface as issues your team is already triaging. With this integration, you can: Set the trigger once: a new risk detected for a monitored vendor, a risk score dropping below a threshold you’ve set, a credential breach turning up on a watched domain, or a questionnaire response coming in.

In July 2026, two AI stories broke that appeared unrelated on the surface. But were they really? The first was an AI product's shared conversation links, meant for specific people, turning up in Google searches, some holding sensitive personal and company data. The second was a frontier AI lab's own model escaping a security sandbox during an internal evaluation and spending four and a half days inside three companies' systems. One involved ordinary users making a common mistake.

September is National Insider Threat Awareness Month, and most of the advice out there is about spotting a person. The insider here is rarely a person. It’s a credential nobody rotated, or an agent nobody kept watching. Each was access granted on purpose, then left unmonitored. The only question that matters afterward is whether anyone would have known.

‍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.

A vendor sends over a SOC 2 report. It lands in the queue, someone reads the cover page, sees the auditor's name and a clean-looking opinion letter, and marks the assessment complete. The reviewer moves on to the next vendor. Multiply that by a few hundred vendors a year, and it becomes less of a decision and more of a reflex.

Endpoint detection, cloud security posture management, email security, identity and access management, network segmentation. Security teams invest heavily in all these active risk vectors, but one category is growing faster than the rest: human risk, which considers what employees do day-to-day in the tools they're given and the ones they aren't.

It's 11:40 am. A security questionnaire just hit your inbox. You open the file and quickly realize you can't finish this alone. Legal needs to review the data processing language. Product has to complete the architecture section. Security is the only team that can sign off on incident response. So you split up the questionnaire, Slack each department their section to answer, and wait... and wait... and wait.

Most teams that assess cloud vendors already have a general idea of the Consensus Assessment Initiative Questionnaire (CAIQ) and Cloud Controls Matrix (CCM). However, you may not have a good answer for what it takes to run that assessment. Turning a vendor's trust center page, SOC 2 report, and security policy into a structured, defensible view of CCM control coverage is a different problem entirely.

Most vendor onboarding and app access work is waiting and follow-ups. Waiting for someone to notice a form came in, assign a tier, chase a questionnaire, or dig up the context behind a Slack request. Risk Automations workflows remove that wait and automate the follow-up. A trigger fires, and the workflow runs to a concrete outcome: a ticket created, a message sent, a risk tier assigned. To make those workflows easier to launch, Risk Automations includes an ever-expanding template library.

You approve five AI tools; your employees use 20. According to UpGuard's State of Shadow AI report, 81% of the workforce is already bringing unmonitored AI tools to work, and legacy security tools are leaving massive gaps in workforce Shadow AI and regulatory compliance. Modern AI governance platforms give you real-time visibility and runtime guardrails to close that gap. They back it up with automated auditing, so you have evidence when someone asks for it.