Drowning in Findings? How Autonomous Pentesting Proves What's Exploitable
Autonomous Offensive testing that Comes with Receipts
In this Solutions Review Solution Spotlight, host Doug Atkinson is joined by XBOW product managers Sarah Hyatt and Jake Reinders to discuss why security teams are drowning in findings — and what it takes to prove which of them actually matter.
The conversation centers on a shift Jake describes early on: the bottleneck used to be what teams could find, and now it's deciding what to act on. As AI accelerates how quickly software gets built and shipped, application portfolios grow while security headcount stays flat. Humans have become the constraint. XBOW's answer is autonomous offensive testing that doesn't just flag potential weaknesses but exploits them and shows its work — a track record that includes the number one spot on the HackerOne global leaderboard, more than 14,000 zero days, and recognition in Microsoft's Patch Tuesday for three critical-severity vulnerabilities.
Sarah, a former pentester, walks through what that looks like in practice. Every validated finding arrives with impact, mitigation guidance, reproduction steps, and a copy-and-paste script — evidence engineers can run themselves rather than a claim they have to chase down. She singles out XBOW's traces as the artifact customers find most valuable: a readable record of the agent's reasoning, the approaches it tried, and the dead ends it hit along the way. Many teams read them as a learning tool.
The discussion also covers how much control teams retain. Assessments can run black box from a single URL or go as deep as full white box with source code, and teams can supply API specs, prior pentest reports, and priority endpoints the same way they'd brief a human pentester. Scope, scheduling, request rates, and how aggressively agents escalate findings are all configurable, so testing fits production, staging, or dev environments without disrupting them.
Jake closes on where XBOW belongs in a security workflow. He positions it not as a shift-left tool but as "right of runtime" — testing applications in context, while they execute, the way an attacker would. Through the public API and integrations like Jira, findings flow into existing remediation workflows and retests confirm the fixes. And for teams already buried in output from other AI or SAST tools, XBOW's validators can be pointed at those findings to sort the exploitable from the noise.
His parting advice to buyers evaluating an increasingly crowded AI security market: make sure the vendor has the receipts.
