# LangChain — CWE-407 Scan Result: CLEAN

**Date:** 2026-03-30
**Target:** https://github.com/langchain-ai/langchain (Python)
**Scanner:** Agent Blackops CWE-407 sweep
**Focus:** chain/agent tool dedup, document loader dedup, vectorstore result dedup, callback handler membership

## Findings

No CWE-407 defects found. The codebase is primarily orchestration/configuration code, not heavy data processing.

**Examined patterns:**
- **multi_vector.py** line 108-111: `if d.metadata[self.id_key] not in ids` — O(D^2) dedup, but bounded by search k parameter (typically k=4..20). Not a practical defect.
- **jsx.py** line 66-68: `if tag not in component_tags` — O(T^2) dedup of JSX component tags, bounded by typical JSX file size (tens of unique tags).
- **langchain_core**: Uses `dict` for visited tracking (function_calling.py), sets for membership tests throughout. Clean patterns.
- **partners/**: No linear membership patterns in loops.
- **text-splitters/**: No scalable dedup patterns.

LangChain's architecture is inherently bounded — document counts come from vector search k, tool lists are developer-defined (typically < 20), callback lists are small. No data-proportional linear scans inside loops.
