Our AI strategy for preemptive security
Agentic AI is reshaping offensive security testing, and for good reason. The idea of autonomous agents that can plan, probe, and validate attack paths around the clock is genuinely exciting, especially for organizations that have far more attack surface than they have hours in the day or budget to test it. But as more agentic pentesting platforms come to market, a pattern has emerged that’s worth discussing honestly, because it affects how security teams should evaluate this new category.
Many of these emerging platforms built and proved out their technology, at least in part, by running it against public Vulnerability Disclosure Programs (VDPs) and bug bounty programs, including programs on the Bugcrowd Platform. Some still do. That’s not inherently wrong. Live programs are one of the few places to test offensive tooling against real, production targets with permission, and it’s a reasonable way to validate a new approach before asking customers to trust it.
What’s worth digging into is what that testing has actually shown. Across the submissions we’ve seen from these tools, the overwhelming majority have been low-signal: duplicates, theoretical issues with no real exploitability, or reports that don’t hold up under review. Meanwhile, the highest-severity, highest-signal findings on those same programs continue to come overwhelmingly from skilled human researchers, many of whom are already using the same frontier models as part of their own process. That last point matters. If an agentic system could consistently out-find that population of motivated, model-assisted humans on live bounty programs, it would mean that system had surpassed the best offensive researchers in the world. That’s an extraordinary claim, and it deserves real scrutiny rather than being taken on faith from a product page.
There’s also a structural reason VDPs and bug bounty programs, rather than paid engagements, tend to be the proving ground of choice. Programs that pay for a managed service typically also pay for expert triage, which means every submission gets reviewed by people who have spent years learning to separate real vulnerabilities from noise. For a new tool trying to validate itself, that’s a convenient, free quality check: someone else is already doing the sorting. And someone else is footing the bill.
The tradeoff is that the noise has to go somewhere. Every low-quality submission a triage team reviews and closes out is time not spent on legitimate findings from the program’s actual researcher community. It’s a real operational cost, and it’s being absorbed by the programs and the humans behind them, not by the vendors generating the volume.
None of this is an argument against agentic testing as a category. Autonomous agents are genuinely good at certain things: continuous coverage across sprawling attack surfaces, testing assets that would otherwise never see a human tester, and catching common, well-understood flaw classes fast and affordably. The technology is a real and useful complement to human-led testing, not a replacement for it. But it does raise a fair question for any security leader evaluating this category: who is responsible for filtering the output before it reaches your team? If a platform’s track record depends on someone else’s triage layer to look credible, that’s worth knowing before you point it at your own environment, because without that layer, your team may end up doing the sorting instead.
That’s the problem we built Savant Pathseeker to solve for. Rather than shipping raw agent output and asking your security team to figure out what’s real, Pathseeker is native to the Bugcrowd Platform, so agentic findings move through the same evidence-based validation Bugcrowd customers already rely on for human-led testing. Findings arrive with reproducible proof of exploitability, not just a list of things that might be wrong: continuous, scalable coverage across your external web apps and APIs, without turning your security team into the triage desk for someone else’s agent.
If you’re evaluating agentic pentesting, it’s worth asking any vendor a simple question: what happens to the findings your tool can’t confirm, and who checks its work? If you don’t get a good answer, give us a call. We can do it. We’re doing it for them, we can do it for you.
Learn more about Savant Pathseeker.