GroundingLMM AI Agent

by mbzuai-oryx• 968•• Scanned•Claim this listing•Request removal
Data Science & MLfoundation modelsllm agentlmmvision and languagevision language model

[CVPR 2024 🔥] Grounding Large Multimodal Model (GLaMM), the first-of-its-kind model capable of generating natural language responses that are seamlessly integrated with object segmentation masks.

GroundingLMM is an open-source ai agent by mbzuai-oryx, written mainly in Python, with 968 GitHub stars and the Apache-2.0 license. Its code was last updated Sep 5, 2026.

Scan summary: scanned Nov 5, 2026 at commit 1454b45. Seen able to run dynamic code. Scan policy

Scanned
Full scan at 1454b45 · Nov 5, 2026
Scanned
Static code scanwarn
Secrets scanfail
Dependency audit324 known vulnerabilitiesfail
Manifestnonewarn
Buildfail
Boot & handshaken/a
Network egressn/a
Reproducible (×3)n/a

Findings (55)

  • high
    code-execution issue
    Details are available to the maintainer after claiming this listing.
  • high
    code-execution issue
    Details are available to the maintainer after claiming this listing.
  • high
    code-execution issue
    Details are available to the maintainer after claiming this listing.
  • high
    code-execution issue
    Details are available to the maintainer after claiming this listing.
  • high
    code-execution issue
    Details are available to the maintainer after claiming this listing.
  • high
    code-execution issue
    Details are available to the maintainer after claiming this listing.
  • high
    code-execution issue
    Details are available to the maintainer after claiming this listing.
  • high
    secrets 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.
  • 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.
    dataset/utils/grefer.py:55
  • medium
    Deserializes data with pickle/marshal, which can execute code.
    dataset/utils/refcoco_refer.py:68
  • medium
    Deserializes data with pickle/marshal, which can execute code.
    mmdet/apis/test.py:188
  • medium
    Deserializes data with pickle/marshal, which can execute code.
    mmdet/core/utils/dist_utils.py:84
  • medium
    setuptools@59.5.0: 5 known vulnerabilities
    PYSEC-2022-43012, PYSEC-2025-49, PYSEC-2026-1918, PYSEC-2026-3447, GHSA-xmj3-9gf7-h52w
    GranD/level_1_inference/8_grit/requirements.txt
  • medium
    accelerate@0.25.0: 1 known vulnerability
    PYSEC-2026-3804
    requirements.txt
  • medium
    deepspeed@0.12.5: 1 known vulnerability
    PYSEC-2024-109
    requirements.txt
  • medium
    diffusers@0.22.3: 3 known vulnerabilities
    PYSEC-2026-2446, PYSEC-2026-40, PYSEC-2026-41
    requirements.txt
  • medium
    fastapi@0.100.1: 1 known vulnerability
    PYSEC-2024-38
    requirements.txt
  • medium
    flash-attn@2.3.6: 1 known vulnerability
    PYSEC-2026-2477
    requirements.txt
  • medium
    fsspec@2023.12.2: 1 known vulnerability
    PYSEC-2026-4217
    requirements.txt
  • medium
    idna@3.6.0: 2 known vulnerabilities
    PYSEC-2024-60, PYSEC-2026-215
    requirements.txt
  • medium
    jinja2@3.1.2: 5 known vulnerabilities
    PYSEC-2026-1471, PYSEC-2026-1472, PYSEC-2026-1473, PYSEC-2026-1474, PYSEC-2026-1475
    requirements.txt
  • medium
    markdown@3.5.1: 1 known vulnerability
    PYSEC-2026-89
    requirements.txt
  • medium
    msgpack@1.0.7: 2 known vulnerabilities
    PYSEC-2026-3625, GHSA-j586-36cw-2gc2
    requirements.txt
  • medium
    oauthlib@3.2.2: 3 known vulnerabilities
    PYSEC-2026-4113, PYSEC-2026-4114, GHSA-7984-qgvg-3j9c
    requirements.txt
  • medium
    opencv-python@4.8.0.74: 2 known vulnerabilities
    PYSEC-2023-183, GHSA-qr4w-53vh-m672
    requirements.txt
  • medium
    orjson@3.9.10: 2 known vulnerabilities
    PYSEC-2024-40, PYSEC-2026-107
    requirements.txt
  • medium
    pip@23.3.2: 6 known vulnerabilities
    PYSEC-2026-1795, PYSEC-2026-1796, PYSEC-2026-196, PYSEC-2026-2875, PYSEC-2026-2876 +1 more
    requirements.txt
  • medium
    protobuf@4.25.1: 2 known vulnerabilities
    PYSEC-2026-1805, PYSEC-2026-1806
    requirements.txt
  • medium
    pyasn1@0.5.1: 8 known vulnerabilities
    PYSEC-2026-2263, PYSEC-2026-3455, PYSEC-2026-3456, PYSEC-2026-3457, GHSA-2qm8-x737-gmw5 +3 more
    requirements.txt
  • medium
    python-multipart@0.0.6: 9 known vulnerabilities
    PYSEC-2026-1850, PYSEC-2026-1851, PYSEC-2026-1852, PYSEC-2026-3036, PYSEC-2026-3037 +4 more
    requirements.txt
  • medium
    sentencepiece@0.1.99: 1 known vulnerability
    PYSEC-2026-1909
    requirements.txt
  • medium
    setuptools@68.0.0: 4 known vulnerabilities
    PYSEC-2025-49, PYSEC-2026-1918, PYSEC-2026-3447, GHSA-xmj3-9gf7-h52w
    requirements.txt
  • medium
    starlette@0.27.0: 7 known vulnerabilities
    PYSEC-2026-161, PYSEC-2026-1941, PYSEC-2026-1943, PYSEC-2026-2280, PYSEC-2026-2281 +2 more
    requirements.txt
  • medium
    urllib3@2.1.0: 8 known vulnerabilities
    PYSEC-2026-141, PYSEC-2026-1994, PYSEC-2026-1995, PYSEC-2026-1996, PYSEC-2026-1998 +3 more
    requirements.txt
  • medium
    werkzeug@3.0.1: 7 known vulnerabilities
    PYSEC-2026-2043, PYSEC-2026-2044, PYSEC-2026-2045, PYSEC-2026-2046, PYSEC-2026-2320 +2 more
    requirements.txt
  • medium
    Install or build failed in a clean environment
    f `flash-attn` is a first-party package, consider adding `torch` to its `build-system.requires`. Otherwise, either add it to your `pyproject.toml` under: [tool.uv.extra-build-dependencies] flash-attn = ["torch"] or `uv pip install torch` into the environment and re-run with `--no-build-isolation`.
  • low
    bleach@6.0.0: 2 known vulnerabilities
    GHSA-8rfp-98v4-mmr6, GHSA-gj48-438w-jh9v
    requirements.txt
  • low
    filelock@3.13.1: 4 known vulnerabilities
    PYSEC-2026-1374, PYSEC-2026-1375, GHSA-69hj-f68j-2879, GHSA-8mx5-7m5m-r77g
    requirements.txt
  • low
    fonttools@4.47.0: 1 known vulnerability
    PYSEC-2026-1389
    requirements.txt
  • low
    pydantic@1.10.12: 1 known vulnerability
    PYSEC-2026-1812
    requirements.txt
  • low
    requests@2.31.0: 3 known vulnerabilities
    PYSEC-2026-1872, PYSEC-2026-1873, PYSEC-2026-2275
    requirements.txt
  • low
    scikit-learn@1.3.2: 1 known vulnerability
    PYSEC-2024-110
    requirements.txt
  • low
    tqdm@4.64.1: 1 known vulnerability
    PYSEC-2026-1976
    requirements.txt
  • low
    zipp@3.17.0: 1 known vulnerability
    PYSEC-2026-2074
    requirements.txt
  • low
    No manifest declaring network access and environment variables (agent.json)

Network activity

During install
api.github.comfiles.pythonhosted.orggithub.compypi.orgraw.githubusercontent.com
While running
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