MOTO Autonomous ASI AI Agent

by Intrafere• 92•• Scanned•Claim this listing•Request removal
Productivity & Workflowai inferenceai researchautomated discoveryautomated proof generationautomated theorem discovery

MOTO is an automated theorem generator for science. It's a creative novelty-seeking researcher with autonomous Lean 4 proof generation. Run for days at a time once pressing start - no interaction needed! Agents working in parallel from either local host LM studio, OpenRouter, OAuth or all 3. No internet required. Star us for more!

MOTO Autonomous ASI is an open-source ai agent by Intrafere, written mainly in Python, with 92 GitHub stars and the MIT license. Its code was last updated Oct 30, 2026.

Scan summary: scanned Nov 5, 2026 at commit e19ef25. Seen able to run shell commands, read environment and secrets. Scan policy

Scanned
Full scan at e19ef25 · Nov 5, 2026
Scanned Builds
Static code scanwarn
Secrets scanfail
Dependency audit31 known vulnerabilitiesfail
Manifestnonewarn
Buildpass
Boot & handshaken/a
Network egressn/a
Reproducible (×3)n/a

Findings (16)

  • high
    dropper issue
    Details are available to the maintainer after claiming this listing.
  • high
    credential-access issue
    Details are available to the maintainer after claiming this listing.
  • high
    credential-access issue
    Details are available to the maintainer after claiming this listing.
  • high
    credential-access 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
    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.
  • medium
    Runs shell commands. Fine for some tools, but it means the agent can run anything your user can.
    moto_launcher.py:699
  • medium
    python-multipart@0.0.9: 16 known vulnerabilities
    PYSEC-2026-1851, PYSEC-2026-1852, PYSEC-2026-3036, PYSEC-2026-3037, PYSEC-2026-3038 +11 more
    requirements-generic.txt
  • medium
    torch@2.9.1: 8 known vulnerabilities
    PYSEC-2026-139, PYSEC-2026-2286, GHSA-qfhq-4f3w-5fph, GHSA-rrmf-rvhw-rf47, PYSEC-2026-139 +3 more
    requirements-generic.txt
  • medium
    transformers@5.9.0: 2 known vulnerabilities
    PYSEC-2026-3929, PYSEC-2026-3929
    requirements-generic.txt
  • low
    Possible example credential in docs/tests: generic-api-key
    tests/integration/test_kimi_code.py:35
  • low
    Possible example credential in docs/tests: generic-api-key
    tests/unit/test_syntheticlib_route_inventory.py:35
  • low
    idna@3.9.0: 1 known vulnerability
    PYSEC-2026-215
    requirements-generic.txt
  • low
    No manifest declaring network access and environment variables (agent.json)

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