Who it is for
Agent Lightning — agentic RL infrastructure
pyproject.toml:4
Scanned repository says: Agent Lightning — agentic RL infrastructure
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Agent Lightning — agentic RL infrastructure
pyproject.toml:4🪶 ~3,500 lines of code: We treat simplicity as the first principle.
README.md:22🧩 Train with real agent harnesses: Agents interact with the model through the Agent Lightning v1.0 proxy with ZERO changes, while keeping tools, context, control flow, and environments in the loop.
README.md:23☸️ Native Kubernetes support: Run agents directly as Kubernetes Jobs without relying on external sandbox services.
README.md:24The following is an example installation on a CUDA 13.0 machine:
README.md:29Manifest declares Python >=3.12 as a requirement.
pyproject.toml:21Declares a dependency on fastapi.
pyproject.toml:23Declares a dependency on uvicorn.
pyproject.toml:24Declares a dependency on pydantic.
pyproject.toml:25Declares a dependency on httpx.
pyproject.toml:26Declares a dependency on httpx-retries.
pyproject.toml:27Declares a dependency on hydra-core.
pyproject.toml:28A license or copying file is present; its terms have not been reviewed.
LICENSE:1These are references in selected source files, not proof that a feature works at runtime.
Read from commit 69f5a40 at Oct 12, 2026, 5:33 AM UTC. Source links open that exact commit. Repository statements are unreviewed and do not affect the score.
Critical details are withheld publicly for the first 30 days after a scan. A matched pattern is a lead for investigation, not a confirmed vulnerability.
Dependencies: 35 exact runtime versions from uv.lock checked against OSV.dev on Oct 12, 2026; 4 with known advisories. Reachability is not checked.
The code loads a model with trust_remote_code enabled, which downloads and runs Python from the model's repository. Whoever controls that repository controls code running inside the agent.
Leave trust_remote_code off, or pin the model to a reviewed revision hash.
Model output is used without being checked against a schema. Unexpected or malformed output can break later steps or be trusted when it should not be.
Validate model output with Zod, JSON Schema, Pydantic or provider structured output.
Model output is used without being checked against a schema. Unexpected or malformed output can break later steps or be trusted when it should not be.
Validate model output with Zod, JSON Schema, Pydantic or provider structured output.
A model call has no visible fallback. If the provider fails or is rate limited, the whole agent fails with it.
Configure a secondary model or explicit fallback path for provider failures.
Metal Mantra could not confirm that the owner controls the stated domain. The domain may belong to someone else.
Verify the domain using the Metal Mantra DNS TXT challenge.
anyio 4.13.0 (PyPI) has known advisories: GHSA-5p39-cfhj-2xmp, GHSA-82r6-8w77-94w6, PYSEC-2026-4024, PYSEC-2026-4025 (highest severity critical). AnyIO: TLSStream IDNA 2003 host name encoding enables potential TLS certificate spoofing
Upgrade to a fixed version listed in the advisory and regenerate the lockfile.
cryptography 48.0.0 (PyPI) has known advisories: GHSA-537c-gmf6-5ccf, GHSA-g6cj-pr64-35w5, GHSA-jwv3-5hgf-82ww, GHSA-m2h6-j472-rp4c, PYSEC-2026-3552 (highest severity high). Vulnerable OpenSSL included in cryptography wheels
Upgrade to a fixed version listed in the advisory and regenerate the lockfile.
hydra-core 1.3.2 (PyPI) has known advisories: GHSA-2cp2-2r3c-7p7r, GHSA-c3wx-c55w-pxjq, PYSEC-2026-3850 (highest severity high). Hydra: hydra.utils.instantiate with untrusted config can lead to code execution
Upgrade to a fixed version listed in the advisory and regenerate the lockfile.
No privacy policy link was found on the stated homepage. Buyers cannot see how the vendor handles their data.
Expose a clear Privacy Policy link on the official homepage.
No terms link was found on the stated homepage. Buyers cannot see the conditions that apply to using the service.
Expose a clear Terms link on the official homepage.
Each pillar starts at 100. Rule deductions reduce its score; weights determine the overall contribution.
No user reports yet.
Each report is one signed-in GitHub account saying what happened. We do not verify that the account ran the agent, and reports never change the automated score or grade. For a security problem, use the disclosure page instead of a public note.
Share the full report so its scope and limits travel with the score.