PyPI / langchain-core / 1.6.13
langchain-core 1.6.13
- Source
- https://github.com/langchain-ai/langchain
- Tag scanned
langchain-core==1.6.13- Directory
libs/core- Compared with
langchain-core==1.6.12(0 signals introduced since)- Files
- 372 scanned, 27 skipped (binary, oversized, or unrecognised)
- Signals
- 0 critical · 0 warn · 19 info
- Scan time
- 14.3 s
- LLM review
- Reviewed by claude-haiku-5-5 (Anthropic): 19 of 19 warn and critical signals; 19 demoted to info.
- Disclude version
- 4.1.0
- Scanned (UTC)
- 2026-10-22 11:29
Signals
Ordered by severity, then signals introduced in this release. Hidden characters are shown as ⟨U+…⟩.
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= = returnlikely benign Lazy attribute loader that caches imported symbols in the module globals.Reasoning
The snippet is the standard PEP 562 lazy-loading pattern: a module-level __getattr__ imports the requested attribute with import_attr and caches it in globals(). The name comes from a fixed lookup of the package's own public API, not from untrusted input, and this is a well-known library idiom.
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= return Falselikely benign Call-stack introspection to determine whether a caller is internal to the library.Reasoning
inspect.currentframe() is used in a try/except AttributeError to check the caller's module for internal-use deprecation handling. It only reads the call stack for diagnostics and does not execute or exfiltrate anything.
-
= = returnlikely benign Lazy attribute loader for the callbacks package.Reasoning
Same standard lazy-import __getattr__ pattern as the other langchain_core package __init__ files, resolving a known public symbol and caching it. No untrusted input or dangerous operation is involved.
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info
warn→ info by reviewdynamic-attributelibs/core/langchain_core/document_loaders/__init__.py:34:5= = returnlikely benign Lazy attribute loader for the document_loaders package.Reasoning
Standard PEP 562 lazy-import __getattr__ for the document_loaders package. It resolves the library's own public symbols by name and caches them, which is routine.
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= = returnlikely benign Lazy attribute loader for the documents package.Reasoning
Standard lazy-import __getattr__ in the documents package, resolving its own public names. The pattern is benign and matches the rest of the package.
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= = returnlikely benign Lazy attribute loader for the embeddings package.Reasoning
Standard lazy-import __getattr__ for the embeddings package, using fixed module-internal names. No dynamic execution of untrusted data occurs.
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info
warn→ info by reviewdynamic-attributelibs/core/langchain_core/example_selectors/__init__.py:42:5= = returnlikely benign Lazy attribute loader for the example_selectors package.Reasoning
Standard lazy-import __getattr__ for the example_selectors package. It resolves known public symbols and caches them, with no security-relevant behavior.
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= = returnlikely benign Lazy attribute loader for the indexing package.Reasoning
Standard PEP 562 lazy-import __getattr__ in the indexing package, matching the common langchain_core pattern for deferred imports.
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info
warn→ info by reviewdynamic-attributelibs/core/langchain_core/language_models/__init__.py:111:5= = returnlikely benign Lazy attribute loader for the language_models package.Reasoning
Standard lazy-import __getattr__ for the language_models package, resolving the library's own symbols. The globals() write is the usual caching step.
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= = returnlikely benign Lazy attribute loader for the load package.Reasoning
Standard lazy-import __getattr__ in the load package. Although the load area handles serialization, this snippet only resolves fixed attribute names through import_attr and does not deserialize or execute untrusted data.
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= = returnlikely benign Lazy attribute loader for the messages package.Reasoning
Standard PEP 562 lazy-import __getattr__ for the messages package, using the library's own public names. This is routine.
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info
warn→ info by reviewdynamic-attributelibs/core/langchain_core/output_parsers/__init__.py:96:5= = returnlikely benign Lazy attribute loader for the output_parsers package.Reasoning
Standard lazy-import __getattr__ for the output_parsers package. It resolves known symbols and caches the result, with no dynamic execution of external input.
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= = returnlikely benign Lazy attribute loader for the outputs package.Reasoning
Standard lazy-import __getattr__ in the outputs package, matching the same benign library-wide pattern.
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= = returnlikely benign Lazy attribute loader for the prompts package.Reasoning
Standard lazy-import __getattr__ for the prompts package, resolving its own public symbols. The snippet shows no template execution or other risky behavior.
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= = returnlikely benign Lazy attribute loader for the runnables package.Reasoning
Standard lazy-import __getattr__ in the runnables package, resolving known names and caching them in globals.
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= = returnlikely benign Lazy attribute loader for the tools package.Reasoning
Standard lazy-import __getattr__ for the tools package. The names come from a fixed internal mapping, not from untrusted input, so there is no evasion.
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= = returnlikely benign Lazy attribute loader for the tracers package.Reasoning
Standard lazy-import __getattr__ in the tracers package, the same benign deferred-import pattern used across langchain_core.
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= = returnlikely benign Module-level __getattr__ that lazily imports a named attribute from the package and caches it in globals().Reasoning
This is the standard lazy-import idiom in __getattr__: it resolves a module attribute by name via import_attr with the package's own __spec__.parent, caches the result in globals(), and returns it. The pattern is legitimate and widely used in langchain packages; nothing here executes fetched data or obscures intent.
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= = returnlikely benign Module-level __getattr__ that lazily imports vectorstore attributes by name and caches them in globals().Reasoning
Same lazy-loading __getattr__ pattern as the utils package: import_attr resolves a name within the package's own modules, and the result is cached in globals(). It is a common, benign way to defer heavy imports and matches the rest of the library's structure.
Reproduce This Scan
Run disclude locally to verify. Add --format sarif for SARIF output. Add --llm (with an API key in the environment) to include the LLM review.
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