OpenAI raises bug bounty rewards to $172,000 and tests its defenses with its models

AI labs are racing with a clear security premise: if models can detect software vulnerabilities with increasing accuracy, defenders are required to run them to protect infrastructure before attackers exploit them. In this context, OpenAI announced a partnership with researchers from Cathedral Systems to launch its next round of internal security hardening races, raising critical bug bounty rewards by more than fourfold, bringing the total value of exceptional reports to $172,000 including additional incentives.

This round relies on integrating Cathedral Systems researchers alongside internal engineering teams to test systems and discover weaknesses using the company's own models. The move follows a previous hardening round in which the company allocated 25 percent of product engineers to the task of finding and fixing software bugs. During that earlier experiment, engineers used the Codex model to investigate results, reproduce vulnerabilities in completely isolated environments, and prepare software updates for review and audit before release.

The proactive defense strategy bets on empowering a trusted network of defenders, as the company allocated $1 billion in the form of supported access to its models over six months to assist personnel on the front-line defense.Alongside this funding and expanded access, the company announced its intention to publish its security infrastructure architecture and document the engineering lessons learned. However, the official announcement left undisclosed areas; it did not specify the actual scope of the upcoming security round, its duration, or launch date, nor did it provide any quantitative data documenting the numeric results of the previous audit round.

We at the editorial board see this shift as having a direct practical implication for information-security officers and software-engineering teams in financial institutions and government bodies across the Gulf, Egypt and the Levant. As generative models become actual tools for scanning source code and automating patching, security review no longer relies on manual inspection or traditional static-analysis tools, but now requires embedding software models within isolated test environments to detect vulnerabilities before external exploitation. Publishing the architectural framework and lessons learned gives technology managers in the region a realistic model for setting access policies and assessing the readiness of their enterprise applications, while the rise of the global bounty ceiling to $172,000 forces a reassessment of local bug-bounty programs to retain engagement of specialized technical talent.

The real gamble in this path remains contingent on how well defensive organizations can match the speed at which the models themselves evolve and incorporate automated testing results into production pipelines. If major labs view their models as the first line of defense for testing their fortresses, your practical step as a technology officer is to review how you isolate automated code-testing environments, and ensure internal security teams stay ahead of any potential threat by employing software models before attackers do.