Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

The standard answer to fragmented AI compliance is a responsibility matrix mapped across the lifecycle. Procurement accountable at intake, legal responsible for regulatory vetting, engineering accountable at implementation, security accountable for monitoring. Every stage has an owner and every function knows its part. ‍ Read that arrangement carefully and the problem is visible inside the solution.

A governance program looks complete until somebody asks it to prove something on a deadline it did not set. A supervisor sends an information request. An underwriter asks for control coverage before binding. A prospect's security team asks how a specific control operated last quarter, and the deal waits on the answer. ‍ Most programs can describe what they do accurately and cannot evidence it inside the window. The difference is not a documentation problem.

Arguments for quantifying cyber risk are abundant and mostly sound. What gets published far less often is a plain account of what a modeled figure does not tell you, which is unfortunate, because stating the limits is more persuasive to a skeptical audience than another argument for the method. ‍ We build these models. What follows is what they cannot do, written plainly, followed by what remains useful once those limits are accepted. ‍

In our previous “ABC’s of ‘ishing” posts, we explored how attackers use social media, calendar invites, fake CAPTCHA challenges, and other trusted tools to deceive users. This next installment looks at three phishing techniques that continue to put organizations and individuals at risk: evil twin phishing, domain spoofing, and email phishing.

Nucleus Insights flagged 14 vulnerabilities with real-world exploitation activity that looked risky before CISA added them to KEV. The key takeaway: all 14 were later listed in KEV. Acting on those signals would have been the right call every time, just earlier.

When you search for IT risk management software, the results rarely agree on what the category is. Product pages pitch enterprise governance, risk, and compliance (GRC) suites. Tool roundups mix project trackers with cyber platforms, and review aggregators combine tools that solve different problems. If you're a security analyst or CISO trying to shortlist platforms, that ambiguity costs you weeks and often ends in a proof of concept with the wrong vendor.

An organization licenses ChatGPT Enterprise. An employee opens a second browser profile, signs into the personal account already logged in there, and pastes a customer extract into it. Same laptop, same managed browser, same corporate egress, same person, same web address. ‍ Every control in the path reads that session as ordinary and correct, because by every attribute any of them can see, it is.

A company too young or too small to have an incident history still has to answer the underwriter at renewal, the enterprise customer running a security review, and the board asking what the exposure is. The usual objection is that quantification needs a baseline and there is none. ‍ The objection rests on a mistaken assumption about how these models work.

At UpGuard, we believe your Trust Center should be the single place your prospects and customers go to get their trust questions answered. Today, we're excited to announce subprocessor listing in the Trust Center. This capability lets you publish your subprocessors directly where buyers already look for trust signals. You can also keep that list up to date and enable customers to subscribe to updates.