Security tooling has a familiar adoption problem. The organizations that need it most — the ones scaling fast enough that their attack surface is outgrowing their process — are often the same ones that can’t justify a sales call and a signed contract just to see whether a product fits. They want to turn it on, run it against real repositories, and see what it actually finds before anyone talks pricing. GitHub just made that path available to a lot more of them. The company raised the eligibility ceiling for self-serve GitHub Advanced Security (GHAS) trials, moving the cap from enterprises with up to 100 licenses to those with up to 300. Any GitHub Enterprise Cloud organization under that new threshold can start a 30-day trial directly from the “Billing and licensing” page in their enterprise settings, no sales conversation required. During the trial, an organization can add any number of committers and turn on both GitHub Secret Protection and GitHub Code Security acr...
Vulnerability prioritization is not a language problem. The safest agent architectures use models to interpret and explain, while deterministic systems traverse the evidence. Ask a security team a simple question: Of the vulnerabilities your scanner reported this morning, which ones can actually be exploited in production? The honest answer is often that nobody knows yet, and proving it can take hours or days. That makes it tempting to point an AI agent at the scanner output and ask for a prioritized list. The agent will respond immediately, in fluent prose, with a confident rationale. But if the evidence required to determine exploitability is not in the input, the answer is still a guess. Better model quality does not solve missing data. Exploitability Is a Property of a Path Exploitability is not simply a property of a vulnerability record. In production, it depends on relationships. To determine whether a vulnerable library matters, a team may need to establish that the packa...