Organizations budget for AI as a risk vector to mitigate but have no procurement or deployment model for AI agents as continuous, autonomous security auditors capable of finding vulnerabilities like the 13-year-old Apache ActiveMQ RCE before adversaries do. The capability gap is not technical — it is organizational and economic: security budgets are structured around reactive tooling, and no marketplace or outcome-based pricing model exists to deploy defensive agent workloads at scale. A two-sided market connecting agent auditing capabilities to organizations with exposed attack surfaces would unlock currently stranded defensive value.

Organizations lack a procurement model for continuous AI-driven security auditing — budgets fund reactive tools while known vulnerability classes like the 13-year Apache ActiveMQ RCE sit undiscovered because no outcome-based marketplace connects defensive AI capabilities to exposed attack surfaces.

CISOs and security leads at mid-to-large enterprises (1,000+ employees) with complex software stacks who already spend on pentesting, bug bounties, and SAST/DAST but get coverage that is periodic, shallow, or slow.

Companies already pay $50K-$500K per pentest engagement and fund bug bounty programs (HackerOne paid $300M+ to date); an always-on agent marketplace with pay-per-validated-finding pricing slots directly into existing security budgets while delivering continuous coverage no human team can match.

MVP: a sandboxed execution environment where registered security agents (built by third-party developers or in-house) run scoped audits against customer-authorized targets, with findings triaged and deduplicated by a verification agent before payout — start with open-source dependency and config audits to minimize scope risk.

Global application security market is ~$10B and penetration testing alone is ~$3B; an outcome-priced agent marketplace could capture 5-10% within 3 years as it replaces periodic engagements with continuous coverage.