gitnexus-taint-analysis

Analyze source-to-sink data-flow findings in GitNexus's CFG/taint/PDG subsystem.

Updated Jun 23, 2026
One-click install
npx skills add https://github.com/guideops/agentic-shared --skill gitnexus-taint-analysis-guideops
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: gitnexus-taint-analysis
Source: https://github.com/guideops/agentic-shared/tree/main/skills/gitnexus-taint-analysis
Command: npx skills add https://github.com/guideops/agentic-shared --skill gitnexus-taint-analysis-guideops

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill provides expert knowledge and tools for working with GitNexus's CFG/taint/PDG subsystem, helping users understand, extend, and reason about source→sink data-flow findings.

Core Features & Use Cases

  • Expert Knowledge: Offers detailed information on control-flow graphs, reaching definitions, and intra- + inter-procedural taint.
  • Use Case: When debugging false positives/negatives in --pdg output, or when reviewing and extending the taint code.
  • Layered Approach: Provides a layered substrate for understanding the build order and how each layer contributes to the analysis.

Quick Start

Use the gitnexus-taint-analysis skill to review the interprocedural taint code for a specific function.

Frequently Asked Questions about gitnexus-taint-analysis

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I debug false positives in source to sink taint analysis output?▼

Taint analysis tracks how untrusted data flows from sources to sinks using control-flow graphs and reaching definitions. It is needed when reviewing code for security vulnerabilities or understanding interprocedural data dependencies across function calls.

How do I debug false positives in source to sink data-flow findings?▼

To debug false positives in source to sink data-flow findings, examine the program dependence graph output and the layered taint analysis build order. Tracing reaching definitions and interprocedural control-flow edges helps isolate which layer introduces the incorrect path.

What's the best way to review and extend interprocedural taint code?▼

Reviewing interprocedural taint code requires understanding the layered build order of the analysis subsystem. Examine how each layer contributes to control-flow graphs and reaching definitions to extend source-to-sink data-flow tracking accurately.

How does a program dependence graph help with taint analysis?▼

A program dependence graph models both data and control dependencies between program statements. It provides the structural substrate needed to trace source-to-sink data-flow paths and reason about reaching definitions during interprocedural taint analysis.

Why does my interprocedural taint analysis miss certain data-flow paths?▼

Interprocedural taint analysis produces false negatives when reaching definitions or control-flow edges are incomplete across function boundaries. Debugging requires reviewing the interprocedural taint code and verifying the layered build order to locate missing source-to-sink paths.