Academic papers related to fuzzing, binary analysis, and exploit dev, which I want to read or have already read
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Updated
Feb 21, 2025 - Python
Academic papers related to fuzzing, binary analysis, and exploit dev, which I want to read or have already read
Official implementation of RiskLoc, a method for localizing multi-dimensional root causes in time-series data.
Root Cause Analysis in the Industrial Domain using Knowledge Graphs: A Case Study on Power Transformers
Root cause first. An idiot admires complexity, a genius admires simplicity.
Blame the right commit, not just the right file — MCP server walks a stack trace through git blame and PR context to surface root cause and author.
Persona Auditor — audit AI-generated code from a real user's perspective. Digital personas exhaustively traverse every user journey, then god's-eye attribution collapses bugs into a few root causes for precise fixing. Agent skill (Claude Code / Codex / Cursor / DSH).
git-bisect for coding agents — align a failed Claude Code run against your last successful run of the same task, span by span, and pinpoint the first divergent step in seconds, not hours.
Tiny debugging puzzle about tracing incident logs through a call graph
Portable AI-assisted debugging skill: root cause first, minimal patch, verification, risk, and learning log.
Incident review and remediation protocol with evidence timelines, root-cause review, appeals, and GenLayer consensus.
调试建筑师:项目完成后扫描报错、分析根因、归档教训、生成预防规则、检测技能漏洞。
A compact Octavus worker that turns a raw stack trace into a cited root-cause brief. Multi-language, offline parsing + agent reasoning.
Evidence-based, replicable protocols and rigorous n=1 case studies for endometriosis and adenomyosis. Root-cause framework, no hormonal contraception, WHOOP + Garmin tracked. Part of the EndEndo.io ecosystem.
Fix the macOS bug where the Minecraft Java launcher can't update itself (error 9 / Operation not permitted). Root cause, permanent fix, and a repair script.
Diagnose stack traces and logs locally to save AI tokens - root cause, the exact frame, and a fix, without spending a Claude/GPT call. Optional AI escalation.
Log investigation agent — ingests CloudWatch/Datadog logs, identifies root cause patterns, suggests fixes using LLM analysis
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