Jan 16
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Writing Glider queries that actually surface real vulnerabilities is harder than it looks. In this session, we break down common mistakes that lead to noisy results, missed findings, and rejected submissions — and how to fix them using more robust patterns. We cover why grepping almost always fails unless it’s extremely high-precision, how to rely on standards and behavior instead of naming assumptions, and when to use dataflow analysis to properly validate security checks like oracle prices. We also talk about why try/except can silently weaken your logic, how to scope queries so they’re easier to triage, and what separates “good” queries from truly legendary ones. If you’re contributing to Glider, participating in contests, or just trying to write cleaner, higher-signal Web3 security queries, this one’s for you. Topics covered: • When grepping is acceptable (and when it absolutely isn’t) • Detecting behavior instead of guessing function or variable names • Using dataflow analysis to check validations correctly • Avoiding try/except traps in Glider queries • How to scope queries without overengineering them • What “legendary” Glider queries really look like in practice • Practical tips for submissions, edits, and avoiding duplicate work 📌 Recorded live for the Remedy security researcher community 🧠 Beginner-friendly, but packed with real-world Glider insights ⭐ GLIDER CONTEST: https://r.xyz/glider-query-database Glider IDE: https://glide.r.xyz/ Remedy platform: https://r.xyz/ 📌 Remedy - web3 Security Researcher Community Join our Discord for live researcher interviews, challenges, and discussions. → https://discord.com/invite/HW7c6dFC5B