OpenAI Raises Bug Bounty Rewards to $100,000 for Critical Vulnerabilities

OpenAI has significantly increased its maximum bug bounty payout from $20,000 to $100,000 for critical security vulnerabilities in its infrastructure and products. The update, announced via the company’s official blog, targets “exceptional and differentiated” findings, reflecting heightened investment in AI security as adoption grows¹. The program, hosted on Bugcrowd since April 2023, has already rewarded 209 submissions, with new incentives like limited-time bonuses and API credit microgrants for researchers².

Program Scope and Incentives

The expanded bug bounty program covers vulnerabilities in OpenAI’s APIs, ChatGPT, and underlying systems. Critical flaws—such as remote code execution (RCE) or authentication bypasses—now qualify for the $100,000 reward, while high-severity issues can earn up to $20,000. OpenAI has also introduced time-bound bonuses for specific vulnerability classes, though exact criteria remain undisclosed³. Researchers may additionally receive API credits to prototype security tools, a move aimed at fostering long-term collaboration¹.

Industry Context and Security Partnerships

The payout increase aligns with broader AI security challenges, including prompt injection and model manipulation. OpenAI has partnered with SpecterOps for red-teaming exercises and cites ongoing efforts to harden defenses against adversarial attacks¹. Stephen Kowski of SlashNext noted the program’s competitiveness compared to peers like DeepSeek, which faced criticism for security gaps². The bounty expansion coincides with rising scrutiny of generative AI systems, where vulnerabilities could enable data exfiltration or misuse at scale.

Relevance to Security Professionals

For security teams, OpenAI’s program offers a template for incentivizing external research while mitigating risks in fast-evolving technologies. The focus on “differentiated” findings suggests prioritization of novel attack vectors, such as AI-specific exploits beyond traditional web vulnerabilities. Organizations deploying AI models can adapt similar strategies, combining bug bounties with proactive measures like:

Regular red-team assessments targeting AI pipelines
Monitoring for anomalous model outputs (e.g., data leakage via generated responses)
Implementing strict API rate limits and access controls

OpenAI’s transparency about paid submissions—without disclosing specifics—provides measurable benchmarks for other firms evaluating their own programs³.

Conclusion

The bounty increase underscores the escalating stakes in AI security, where vulnerabilities may have cascading impacts across applications. While monetary rewards attract researchers, sustained collaboration through microgrants and partnerships could yield more systemic improvements. As AI adoption accelerates, such programs will likely become standard for mitigating emergent threats.