LLM Security Playbook
مميزA comprehensive guide and checklist for securing Large Language Model applications against common vulnerabilities.
معرض الأعمال
نظرة منسقة على أبحاثي الأمنية، ومشاريعي الشخصية، ومساهماتي ذات الأثر في البنية التحتية للمصادر المفتوحة.
أعمال مختارة تمثل جهودي الأكثر تأثيرًا في الأمان والبحث.
A comprehensive guide and checklist for securing Large Language Model applications against common vulnerabilities.
A comprehensive case study on discovering and fixing a critical vulnerability in pip's dependency resolution algorithm that affected millions of Python developers worldwide.
A detailed case study on identifying and fixing security vulnerabilities in the OpenAI Python SDK, including async streaming improvements and backpressure handling implementation.
صنف حسب الفئة والتقنية لاستكشاف الأرشيف الكامل.
ديسمبر ٢٠٢٥
Fixed a critical issue in dependency resolution for editable installs.
أكتوبر ٢٠٢٤
Enabled production-grade async streaming for high-concurrency LLM applications
سبتمبر ٢٠٢٤
Resolved critical bug affecting 50K+ daily pip installs with complex dependency trees
أغسطس ٢٠٢٤
Fixed cross-platform deployment issues affecting CI/CD pipelines in 10K+ projects
يوليو ٢٠٢٤
Achieved 40% performance improvement for deeply nested model validation
يونيو ٢٠٢٤
Established industry-standard GraphQL security testing procedures adopted by security professionals globally
مايو ٢٠٢٤
Enhanced CLI developer experience with intelligent auto-completion for complex command hierarchies
أبريل ٢٠٢٤
Enabled secure dependency pinning for organizations requiring supply chain integrity verification