alist-org
Add Feature: Automatically Delete Detrimental Issues
Please make sure of the following things
- [ ] I have read the documentation.
- [ ] I'm sure there are no duplicate issues or discussions.
- [ ] I'm sure this feature is not implemented.
- [ ] I'm sure it's a reasonable and popular requirement.
Description of the feature / 需求描述
As the repository grows, managing issues becomes increasingly complex. While most issues serve as valuable tools for tracking bugs, feature requests, and discussions, some can become detrimental to the project's health, reputation, or security. These may include: Issues containing sensitive information (e.g., credentials, private data) accidentally exposed Malicious issues created to spread misinformation or disrupt project workflow Outdated or irrelevant issues that no longer align with current project goals but cause confusion for new contributors Issues with severely negative or unconstructive language that harm team morale or community 氛围 There is a need for a systematic way to identify and automatically remove such detrimental issues without requiring constant manual supervision. This feature would help maintain a clean, focused issue tracker while protecting the project from potential harm.
Suggested solution / 实现思路
- Detrimental Issue Detection Criteria The system should allow repository administrators to define custom detection rules based on multiple factors: Content-based filters: Keywords/phrases (e.g., "hack", "exploit", "confidential"), regular expressions, or natural language processing to identify harmful language Metadata-based filters: Issue labels (e.g., "security-risk", "spam"), creation time (e.g., issues older than X years with no activity), or author patterns (e.g., accounts with high spam flags) Structural analysis: Issues containing links to malicious domains, file attachments with dangerous extensions, or unusually high numbers of up/down votes indicating controversial content
- Automated Deletion Workflow Scheduled scans: Regular background jobs (configurable frequency: daily/weekly/monthly) to check for issues matching defined criteria Pre-deletion review queue: An optional staging area where critical issues (e.g., those labeled "security-critical") go through a manual approval process before deletion Audit logging: Detailed records of all automated deletions including timestamps, issue URLs, and matched criteria for compliance and troubleshooting
- Configuration and Permissions Granular access controls: Only users with "admin" or custom role permissions can define/modify deletion rules Rule versioning: History of rule changes to revert accidental misconfigurations Exclusion lists: Allow whitelisting specific issues, labels, or authors from the deletion process
Use Cases Scenario 1: Sensitive Data Protection A developer accidentally creates an issue containing API keys. The system detects the keyword "API_KEY" in the issue body and automatically deletes it within 10 minutes of creation, preventing exposure to unauthorized users. Scenario 2: Spam Management A bot creates multiple issues with irrelevant marketing content. The system identifies these based on the "spam" label applied by the community and deletes all such issues during the nightly scan, keeping the issue list clutter-free. Scenario 3: Reputation Management An unhappy user posts an issue with abusive language targeting the development team. The NLP-based toxicity detector flags the issue, which is moved to the review queue. A project manager reviews the content and approves deletion to maintain a positive community environment. Benefits Improved Security: Proactively removes security risks like exposed credentials or exploit discussions Enhanced Productivity: Reduces time spent on manual issue triaging for obvious detriments Better Community Experience: Maintains a constructive discussion environment by eliminating toxic content Cleaner Codebase Management: Automatically archives/removes outdated technical debt that no longer adds value Implementation Considerations False Positive Protection: Include safety features like deletion delays (24-hour hold for non-urgent cases) and easy undo functionality (30-day recovery window) Performance Impact: Optimize scan algorithms to avoid overloading repository servers during peak usage Internationalization: Ensure language-specific filters work for multilingual repositories API Compatibility: Provide webhook notifications for external tools to track deletion events Conclusion This feature would empower repository maintainers to proactively manage their issue trackers, balancing automation with control. By systematically addressing detrimental content, projects can focus on productive development while minimizing risks associated with malicious or irrelevant issues. The combination of custom rules, safety mechanisms, and auditability makes this a valuable addition to any large-scale repository management strategy. Labels: Feature Request Enhancement Security Issue Management
Additional context / 附件
No response
