VectorizedMultiAgentSimulator AI Agent

by proroklab• 627•• Scanned•Claim this listing•Request removal
Learning Resourcesgymgym environmentmarlmulti agentmulti agent learning

VMAS is a vectorized differentiable simulator designed for efficient Multi-Agent Reinforcement Learning benchmarking. It is comprised of a vectorized 2D physics engine written in PyTorch and a set of challenging multi-robot scenarios. Additional scenarios can be implemented through a simple and modular interface.

VectorizedMultiAgentSimulator is an open-source ai agent by proroklab, written mainly in Python, with 627 GitHub stars and the GPL-3.0 license. Its code was last updated May 19, 2026.

Scan summary: scanned Nov 5, 2026 at commit 9658bc5. Seen able to run shell commands, run dynamic code. Scan policy

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Scanned
Full scan at 9658bc5 · Nov 5, 2026
Scanned Builds
Static code scanwarn
Secrets scanpass
Dependency audit0 known vulnerabilitiespass
Manifestnonewarn
Buildpass
Boot & handshaken/a
Network egressn/a
Reproducible (×3)n/a

Findings (3)

  • medium
    Runs shell commands. Fine for some tools, but it means the agent can run anything your user can.
    mpe_comparison/mpe_performance_comparison.py:100
  • medium
    Deserializes data with pickle/marshal, which can execute code.
    mpe_comparison/mpe_performance_comparison.py:130
  • 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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