gitnexus-taint-analysis

Analyze taint propagation from sources to sinks in GitNexus CFG/PDG.

45.2k|5.0k|Updated Aug 2, 2025
One-click install
npx skills add https://github.com/abhigyanpatwari/GitNexus --skill gitnexus-taint-analysis
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: gitnexus-taint-analysis
Source: https://github.com/abhigyanpatwari/GitNexus/tree/main/gitnexus-claude-plugin/skills/gitnexus-taint-analysis
Command: npx skills add https://github.com/abhigyanpatwari/GitNexus --skill gitnexus-taint-analysis

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Analyze taint propagation within GitNexus's CFG/taint/PDG subsystem to support precise reasoning about source-to-sink flows and interprocedural taint.

Core Features & Use Cases

  • Intra-procedural taint analysis to trace data-flow from sources to sinks within a function, including sanitizer handling.
  • Interprocedural taint analysis that composes function-level summaries across the call graph to reveal taint propagation paths.
  • Guidance for developers reviewing and extending the CFG/taint code paths and interpreting explain outputs.

Quick Start

Trace a tainted input through a simple function call to determine if it reaches a sink and verify the corresponding taint summary exists for the callee.

Frequently Asked Questions about gitnexus-taint-analysis

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

FAQPage Schema
How do I trace taint propagation from sources to sinks using CFG and PDG analysis?▼

Taint propagation traces how data flows from sources to sinks by navigating the control flow graph and program dependence graph. It applies strict data-flow sequencing and monotone propagation for reproducible findings.

What is interprocedural taint analysis and how does it work across a call graph?▼

Interprocedural taint analysis composes function-level summaries across the call graph to reveal source-to-sink taint propagation paths. It satisfies a summary-based model to track flows between functions.

How do I interpret taint explain outputs during a code review?▼

Taint explain outputs illuminate source-to-sink data flows by detailing the propagation path. Reviewing these outputs helps developers verify sanitizer handling and trace intra-procedural data-flow traces.

Can I use static analysis to detect taint flows within a single function including sanitizer handling?▼

Intra-procedural taint analysis traces data-flow from sources to sinks within a single function. It identifies whether tainted input reaches a sink and verifies if sanitizers interrupt the propagation path.

What is the best way to extend intra-procedural taint analysis for interprocedural call graph traversal?▼

Extending to interprocedural analysis requires composing function-level taint summaries across the call graph. This ensures deterministic data-flow sequencing is maintained when tracing paths between callers and callees.

Why does my taint analysis report inconsistent data-flow findings across multiple runs?▼

Inconsistent findings occur when propagation is not deterministic and monotone. The analysis requires strict data-flow sequencing and a summary-based interprocedural model to guarantee reproducible taint propagation results.