What is Responsible Disclosure (AI)?
Responsible Disclosure (AI) is the ethical practice of reporting discovered vulnerabilities, safety issues, or harmful behaviours in AI systems to the affected organisation in a structured and confidential manner, giving them reasonable time to address the problem before any public announcement.
What is Responsible Disclosure in AI?
Responsible Disclosure in AI is the process by which security researchers, employees, customers, or other parties who discover vulnerabilities or safety issues in AI systems report those findings to the organisation responsible for the system. The reporter provides the organisation with a reasonable period to investigate and fix the issue before any public disclosure.
This practice has long been established in traditional cybersecurity, where researchers who find software vulnerabilities follow a structured process to report them to vendors. As AI systems become more widespread and more consequential, the same principles are being applied to AI-specific vulnerabilities such as jailbreaking techniques, bias issues, safety bypass methods, and data leakage risks.
Why Responsible Disclosure Matters for AI
AI systems are deployed in increasingly sensitive contexts, from healthcare and financial services to customer interactions and decision-making. Vulnerabilities in these systems can affect millions of users. Without a structured disclosure process, there are two problematic alternatives.
The first is that discoverers stay silent, meaning the vulnerability persists and can be exploited by malicious actors. The second is that discoverers publish their findings immediately, which alerts attackers to the vulnerability before the affected organisation can fix it.
Responsible disclosure provides a middle path. It ensures that vulnerabilities are addressed while minimising the window during which they can be exploited.
Key Elements of an AI Responsible Disclosure Programme
Clear Reporting Channels
Your organisation should publish clear instructions for how external parties can report AI vulnerabilities. This includes a dedicated email address, a web form, or a vulnerability reporting platform. The reporting process should be easy to find, typically on your website's security page, and straightforward to use.
Defined Response Timeline
Establish and publish the timeline for your response process. A typical framework includes acknowledging receipt within 48 hours, providing an initial assessment within two weeks, and working toward remediation within 90 days. For critical AI safety issues, the timeline should be shorter.
Legal Safe Harbour
One of the biggest barriers to responsible disclosure is fear of legal retaliation. Reporters worry that pointing out vulnerabilities could lead to lawsuits. Establish a clear policy that you will not take legal action against good-faith reporters who follow your disclosure guidelines. This safe harbour provision is essential for encouraging reports.
Scope Definition
Clearly define which AI systems and types of vulnerabilities are covered by your disclosure programme. This helps reporters understand whether their findings are in scope and guides them toward the appropriate reporting channel. Include AI-specific vulnerability types such as prompt injection, safety bypass, bias issues, and data leakage.
Communication Protocol
Define how you will communicate with reporters throughout the process. Provide regular updates on the status of their report, notify them when the issue has been fixed, and discuss the timeline for any public disclosure. Professional and respectful communication encourages future reports and builds goodwill with the security research community.
Building a Responsible Disclosure Programme
Step 1: Draft Your Policy
Write a clear, public-facing disclosure policy that covers reporting channels, scope, timeline, legal safe harbour, and the process for recognition or rewards. Use plain language accessible to non-lawyers.
Step 2: Establish Internal Processes
Create internal workflows for receiving, triaging, investigating, and remediating AI vulnerability reports. Assign clear ownership and ensure the right technical and legal stakeholders are involved at each stage.
Step 3: Integrate with AI Safety Testing
Connect your disclosure programme to your broader AI safety testing efforts. Vulnerability reports from external parties provide valuable intelligence about real-world attack vectors and failure modes that should inform your own testing methodologies.
Step 4: Consider a Bug Bounty Programme
For organisations with mature AI deployments, a bug bounty programme that offers financial rewards for qualifying vulnerability reports can significantly increase the volume and quality of reports you receive. Several major AI companies have launched AI-specific bug bounty programmes with positive results.
Step 5: Publish and Promote
Make your disclosure policy easy to find. Include it on your website, reference it in your AI product documentation, and promote it through relevant industry channels. A disclosure programme that nobody knows about cannot fulfil its purpose.
Regional Context for Southeast Asia
The security research community in Southeast Asia is growing rapidly. Countries like Singapore, Vietnam, and the Philippines have active cybersecurity communities that are increasingly turning their attention to AI vulnerabilities. By establishing a responsible disclosure programme, your organisation taps into this pool of external expertise.
Singapore's Cybersecurity Act and the country's national bug bounty programmes provide a model for how responsible disclosure can work in the region. Organisations operating across ASEAN should ensure their disclosure programmes comply with local cybersecurity regulations and are accessible in the languages of their operating markets.
Responsible Disclosure programmes are a strategic investment in the security and reliability of your AI systems. By providing a structured channel for external parties to report vulnerabilities, you gain access to a vast pool of security expertise that supplements your internal testing capabilities.
For business leaders in Southeast Asia, the calculus is straightforward. AI vulnerabilities will be discovered, whether by your team, by security researchers, or by malicious actors. A responsible disclosure programme ensures that when good-faith discoverers find problems, they have a clear and safe path to report them to you rather than publishing them publicly or ignoring them.
The cost of establishing and maintaining a disclosure programme is modest compared to the cost of an AI security incident that could have been prevented by an early report. It also demonstrates to regulators, customers, and partners that your organisation takes AI security seriously and operates transparently.
- Publish a clear and easily accessible disclosure policy that covers reporting channels, scope, timeline, and legal safe harbour.
- Establish internal workflows for receiving, triaging, and remediating AI vulnerability reports with clear ownership at each stage.
- Provide explicit legal safe harbour for good-faith reporters to remove the biggest barrier to responsible disclosure.
- Include AI-specific vulnerability types in your programme scope, such as prompt injection, safety bypass, bias, and data leakage.
- Communicate professionally and regularly with reporters to build trust and encourage future reports.
- Integrate external vulnerability reports into your AI safety testing programme to improve your own testing methodologies.
- Consider launching an AI-specific bug bounty programme once your disclosure processes are mature enough to handle the volume.
Frequently Asked Questions
How is AI responsible disclosure different from traditional cybersecurity disclosure?
The core principles are the same, but AI introduces additional vulnerability types that traditional cybersecurity disclosure programmes may not cover. These include AI-specific issues like jailbreaking techniques, prompt injection vulnerabilities, systematic bias in model outputs, safety control bypasses, and training data leakage. AI disclosure programmes need to include people with AI expertise in the triage and remediation process, not just traditional security engineers.
What if someone publicly discloses an AI vulnerability without contacting us first?
This is known as full disclosure and it puts your organisation in a reactive position. Your immediate priorities should be assessing the severity of the vulnerability, implementing a rapid fix or mitigation, and communicating transparently with affected users. To reduce the likelihood of full disclosure, make your responsible disclosure programme easy to find and use, and provide clear incentives for following the responsible path.
More Questions
Financial rewards through a bug bounty programme can significantly increase the quantity and quality of vulnerability reports you receive. However, they work best when your organisation has mature processes for handling reports efficiently. Start with a recognition-based programme and evolve toward financial rewards as your disclosure processes mature. When you do offer bounties, set clear criteria for what qualifies and ensure payment is prompt and fair.
Need help implementing Responsible Disclosure (AI)?
Pertama Partners helps businesses across Southeast Asia adopt AI strategically. Let's discuss how responsible disclosure (ai) fits into your AI roadmap.