AI Native Lang

Security

Security Disclosure Policy

Effective Date: March 17, 2026  ·  Last Updated: March 17, 2026

We take security seriously and appreciate the work of researchers who help keep AI Native Lang and its ecosystem safe. This page describes how to report vulnerabilities, what we commit to in response, and the coordinated disclosure process we follow.

If you believe you have found a security vulnerability, please do not open a public GitHub issue or post on social media. Instead, follow the private reporting steps below.

1. Scope — What Qualifies

We treat the following as in-scope security vulnerabilities:

  • The AINL compiler, interpreter, or runtime — any issue that allows code execution, capability escalation, or sandbox escape
  • Core language tooling and adapters — adapter privilege escalation, undeclared side effects, or bypass of the adapter allowlist
  • Packaging or dependency integrity — compromised build artifacts, tampered releases, or supply-chain attacks
  • Generated artifacts or execution surfaces produced by official AINL tooling
  • Training, evaluation, or orchestration components that could introduce meaningful security risk
  • ainativelang.com infrastructure — authentication bypass, XSS, CSRF, SQL injection, server-side request forgery, sensitive data exposure, broken access control
  • Official release pipelines or distribution mechanisms

The following are generally out of scope unless they create a concrete, reproducible exploit path:

  • Feature requests or usability issues
  • Performance degradation without a security impact
  • Pure correctness bugs with no security consequence
  • Risks arising solely from unsafe deployment choices outside official project defaults
  • Vulnerabilities in third-party infrastructure not maintained by AINL
  • Theoretical issues without a reproducible scenario or clear impact
  • Self-XSS or attacks that require physical access to an authenticated user’s device
  • Spam, phishing, or social engineering attacks
  • Denial-of-service attacks against the public website using automated tools

If you are unsure whether an issue is in scope, send us a brief summary and we will let you know before you invest time in a full report.

2. How to Report

Please report suspected vulnerabilities privately using one of the following channels:

Preferred: GitHub Security Advisory

Use the GitHub Security tab to submit a private advisory. This keeps the report encrypted and linked to the codebase for coordinated patching.

github.com/openclaw-ai/AI_Native_Lang →

Alternate: Encrypted Email

Email security@ainativelang.com with a clear subject line. For sensitive reports, request our PGP key before sending payload details.

security@ainativelang.com →

Do not open a public GitHub issue, post on forums, or share details on social media until we have had a reasonable opportunity to investigate and ship a fix. Coordinated disclosure protects users who have not yet updated.

3. What to Include in Your Report

The more detail you provide, the faster we can triage and fix the issue. Please include as much of the following as practical:

  • Affected component — compiler, runtime, adapter, website, specific file, or release version
  • Description of the vulnerability — what it is, why it is a security issue
  • Reproduction steps — the minimal sequence of actions needed to trigger the issue
  • Proof of concept — code, payload, screenshot, or recording (shared privately)
  • Estimated severity — your assessment of impact and exploitability (CVSS score if available)
  • Environment details — OS, AINL version, runtime version, container/cloud context
  • Suggested mitigations or patches, if you have them
  • Whether you intend to publish research about this finding, and your desired timeline

You do not need a complete, polished report to reach out. A brief heads-up with a summary is enough to start the conversation.

4. Our Response Commitments

These are targets, not contractual guarantees. Our team operates in good faith and will do its best to meet these timelines:

MilestoneTarget timeline
Initial acknowledgmentWithin 72 hours of receipt
Triage and severity assessmentAfter the issue is reproducible and understood — typically 7–14 days
Fix or mitigationCoordinated based on severity: critical (≤90 days), high (≤90 days), medium/low (best effort)
Coordinated disclosureAfter fix is available and users have had time to update — we will work with you on timing
CVE assignmentWe will request a CVE for accepted vulnerabilities with broad user impact

We will keep you informed throughout the process. If we need more information or cannot reproduce the issue, we will say so promptly.

5. Coordinated Disclosure Process

Once a report is accepted as a valid vulnerability, we follow this process:

01

Confirm and reproduce

We verify the issue in our environment and open a private tracking ticket. We will confirm receipt and initial severity assessment with you.

02

Assess severity and scope

We determine which components, versions, and deployment configurations are affected, and assign a severity using CVSS or equivalent.

03

Develop and validate a fix

We write and review a patch or mitigation. For complex issues, we may ask you to review a draft fix under embargo.

04

Coordinate release timing

We agree on a disclosure date with you. We aim to give users at least 7 days after a patched release before full technical details are published.

05

Release and publish advisory

We ship the fix, publish a GitHub Security Advisory or release note, and request a CVE where appropriate. You are credited unless you prefer anonymity.

6. Safe Harbor

We consider good-faith security research conducted in accordance with this policy to be authorized and will not initiate legal action against researchers who:

  • Report vulnerabilities privately before public disclosure
  • Do not access, modify, or exfiltrate data beyond what is necessary to demonstrate the issue
  • Do not degrade the availability of our services or affect other users
  • Do not use the vulnerability for financial gain or to harm AINL, its users, or third parties
  • Comply with applicable laws and act in good faith

This safe harbor applies to research conducted in accordance with this policy. We cannot provide legal protection for activities that fall outside these boundaries or that violate applicable law.

7. Supported Versions

Security fixes are prioritized for:

  • The latest stable release of AINL tooling and runtime
  • The current development branch, where a fix is feasible

Older versions may receive fixes at maintainer discretion based on severity, active exploit status, user impact, and available bandwidth. We will be transparent about end-of-support timelines for older major versions.

8. Acknowledgments

We maintain a Hall of Thanks for researchers who disclose vulnerabilities responsibly. Unless you prefer to remain anonymous, we will credit you in the associated advisory with your name and handle.

We do not currently operate a paid bug bounty program. We offer public recognition and our genuine gratitude. If this changes, we will update this page.

9. Contact

Security contact

Email: security@ainativelang.com

GitHub Advisories: Report a vulnerability

For general questions about the AINL security model, see the Security Model page. For privacy-related concerns, email privacy@ainativelang.com.