Generative AI With Langchain AI Agent

by benman1• 1.5k•• Scanned•Claim this listing•Request removal
Learning Resourcesagentchatgptclaudeclaude 3 5 sonnetdeepseek

Build production-ready LLM applications and advanced agents using Python, LangChain, and LangGraph. This is the companion repository for the book on generative AI with LangChain.

Generative AI With Langchain is an open-source ai agent by benman1, written mainly in Jupyter Notebook, with 1,451 GitHub stars and the MIT license. Its code was last updated Sep 26, 2026.

Scan summary: scanned Nov 5, 2026 at commit 87e17fd. Seen able to run dynamic code. Scan policy

Scanned
Full scan at 87e17fd · Nov 5, 2026
Scanned
Static code scanwarn
Secrets scanpass
Dependency audit169 known vulnerabilitiesfail
Manifestnonewarn
Buildfail
Boot & handshaken/a
Network egressn/a
Reproducible (×3)n/a

Findings (30)

  • high
    dependencies issue
    Details are available to the maintainer after claiming this listing.
  • high
    dependencies issue
    Details are available to the maintainer after claiming this listing.
  • high
    dependencies issue
    Details are available to the maintainer after claiming this listing.
  • high
    dependencies issue
    Details are available to the maintainer after claiming this listing.
  • high
    dependencies issue
    Details are available to the maintainer after claiming this listing.
  • high
    dependencies issue
    Details are available to the maintainer after claiming this listing.
  • high
    dependencies issue
    Details are available to the maintainer after claiming this listing.
  • high
    dependencies issue
    Details are available to the maintainer after claiming this listing.
  • medium
    Deserializes data with pickle/marshal, which can execute code.
    chapter9/ray/build_index.py:128
  • medium
    langchain@0.3.17: 2 known vulnerabilities
    PYSEC-2026-2192, PYSEC-2026-2555
    requirements.txt
  • medium
    langchain-community@0.3.16: 1 known vulnerability
    PYSEC-2026-1515
    requirements.txt
  • medium
    langchain-text-splitters@0.3.5: 2 known vulnerabilities
    PYSEC-2026-1520, PYSEC-2026-77
    requirements.txt
  • medium
    langgraph@0.3.34: 1 known vulnerability
    PYSEC-2026-83
    requirements.txt
  • medium
    langsmith@0.3.15: 3 known vulnerabilities
    PYSEC-2026-2582, PYSEC-2026-2583, GHSA-f4xh-w4cj-qxq8
    requirements.txt
  • medium
    fsspec@2024.9.0: 1 known vulnerability
    PYSEC-2026-4217
    requirements.txt
  • medium
    google-cloud-aiplatform@1.99.0: 2 known vulnerabilities
    PYSEC-2026-2499, PYSEC-2026-2500
    requirements.txt
  • medium
    langgraph-checkpoint@2.1.2: 3 known vulnerabilities
    PYSEC-2026-1527, PYSEC-2026-2573, PYSEC-2026-2574
    requirements.txt
  • medium
    langgraph-sdk@0.1.74: 2 known vulnerabilities
    PYSEC-2026-2575, PYSEC-2026-4240
    requirements.txt
  • medium
    nbconvert@7.9.2: 4 known vulnerabilities
    PYSEC-2026-1691, PYSEC-2026-2229, PYSEC-2026-2230, GHSA-pjvx-prjx-h659
    requirements.txt
  • medium
    protobuf@4.25.9: 1 known vulnerability
    PYSEC-2026-1805
    requirements.txt
  • medium
    pyarrow@19.0.1: 1 known vulnerability
    PYSEC-2026-113
    requirements.txt
  • medium
    torch@2.9.1: 4 known vulnerabilities
    PYSEC-2026-139, PYSEC-2026-2286, GHSA-qfhq-4f3w-5fph, GHSA-rrmf-rvhw-rf47
    requirements.txt
  • medium
    Install or build failed in a clean environment
    er the following options: 1. set up custom discovery (`find` directive with `include` or `exclude`) 2. use a `src-layout` 3. explicitly set `py_modules` or `packages` with a list of names To find more information, look for "package discovery" on setuptools docs.
  • low
    datasets@3.4.0: 1 known vulnerability
    PYSEC-2026-3716
    requirements.txt
  • low
    langchain-anthropic@0.3.5: 1 known vulnerability
    PYSEC-2026-2556
    requirements.txt
  • low
    langchain-openai@0.3.19: 1 known vulnerability
    PYSEC-2026-76
    requirements.txt
  • low
    streamlit@1.37.1: 2 known vulnerabilities
    PYSEC-2026-212, PYSEC-2026-2285
    requirements.txt
  • low
    idna@3.9.0: 1 known vulnerability
    PYSEC-2026-215
    requirements.txt
  • low
    requests@2.32.5: 1 known vulnerability
    PYSEC-2026-2275
    requirements.txt
  • low
    No manifest declaring network access and environment variables (agent.json)

Network activity

During install
files.pythonhosted.orgpypi.org
While running
Not run — the code wasn't started in this scan

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