Ensuring AI systems remain safe and secure against misuse and abuse

The OpenAI Safety Bug Bounty program addresses the rising risk of AI abuse by inviting external researchers to probe vulnerabilities that could cause tangible harm. By focusing on non‑security threats, the initiative complements traditional bug bounties and builds a layered defense against emerging threats.

Technical Solution

The core solution establishes a structured pipeline where reported incidents are evaluated against a risk matrix, prioritized, and assigned to specialized response teams. This pipeline integrates automated reproducibility checks, manual expert review, and cross‑team coordination to ensure swift mitigation of high‑impact scenarios.

Risk Identification Framework

Researchers submit findings using a standardized template that captures scenario details, reproducibility metrics, and potential harm vectors. The framework categorizes reports into agentic risks, proprietary data leaks, and model‑generation abuses, allowing precise triage and resource allocation.

Program Scope Definition

The scope explicitly includes agentic threats such as MCP attacks, prompt injection, and data exfiltration attempts that achieve a 50% success rate. It also covers model outputs disclosing proprietary information, as well as any behavior that could be weaponized at scale.

By delineating clear boundaries, the program prevents overlap with the traditional security bounty while encouraging deep exploration of edge‑case misuse pathways that could otherwise remain hidden.

Triaging and Routing Process

Submitted reports first enter the Safety triage queue, where a dedicated team evaluates the technical merit and potential impact. If a report aligns more closely with a security vulnerability, it is rerouted to the parallel Security Bug Bounty stream for appropriate handling.

This dual‑track approach ensures that each issue receives the expertise it demands, reducing resolution time and preserving the integrity of both safety and security domains.

Compliance and Ethical Guidelines

All testing must adhere to the terms of service of any third‑party platforms involved, and researchers are required to obtain any necessary permissions before probing live systems. The program enforces strict data handling policies to protect user privacy and prevent accidental disclosure of sensitive information.

Ethical conduct is reinforced through a clear code of conduct, mandatory reporting channels, and a commitment to non‑disclosure of exploit details until a fix is deployed.

Reward Structure and Reporting Mechanisms

Rewards are calibrated based on the severity, reproducibility, and potential real‑world impact of the reported issue. High‑impact agentic abuses can merit top‑tier payouts, while nuanced proprietary leaks receive proportionate compensation.

Researchers submit findings via a secure portal that logs metadata, timestamps, and evidence artifacts, enabling transparent communication and auditability throughout the remediation lifecycle.