Question: voluntary LLMSafe compatibility check for Agent Lightning rollout execution paths?

Aperta
  • Qualcosa non va?
#675 0 commenti 0 reazioni 0 assegnatari Vedi su GitHub

I maintainer di solito rispondono entro 3 giorni

Nessuno ha ancora preso questa issue.

Valutazione

Difficoltà
1/5
Tempo stimato
Meno di un'ora
Idoneità per principianti
5/100
Tipo di issue
Funzionalità
Chiarezza
Da chiarire
Stato di attività
Attiva
Stack tecnologico
python
Ambito
security

Direzione di ricerca

This is an outside party asking maintainers for permission to run an external static scanner on a public Python rollout path, not a code change, and no file or test is named. The only possible action is a maintainer reply that either names a public path and revision or declines. It is done when that answer is posted, and the issue should not be picked up as a first contribution.

Scritto dal modello di indicizzazione a partire dal testo della issue.

Descrizione

Hi maintainers,

I'm Paul, maintainer of LLMSafe, an early-stage open-source static scanner for Python AI-agent/MCP trust boundaries. This is a request for scanner compatibility feedback, not a finding.

Agent Lightning v1.0 keeps real agent harnesses and tool-capable environments in the reinforcement-learning rollout loop. One narrow public Python rollout-controller or example-adapter path would let us test whether LLMSafe traces model-influenced task arguments into execution capabilities while avoiding unsupported claims about Kubernetes isolation, runtime safety or the intent of benchmarking workflows.

Would a free, opt-in, bounded compatibility pilot be of interest? We would first agree on one immutable public commit, one Python path and a private report route. Only after explicit approval would I run LLMSafe locally on the public source (no agents, network calls, models, credentials, or code execution), manually inspect each result, and aim to share a short private report with reproduction commands, false positives, supported signals and limits within two working days of scope agreement.

I have not scanned the repository, and I am not reporting a vulnerability. This is not a penetration test, security certification, CI integration, endorsement or partnership proposal. Any suspected issue goes through the private security channel; neither findings nor participation would be published without separate consent.

If this is relevant, please suggest a public Python path and revision. If not, feel free to close this issue; I won't follow up.

Pilot details: https://github.com/rezerpaul-crypto/llmsafe/blob/main/docs/pilot-program.md

Thanks,
Paul

Lingua principale
Python
Stelle
18.9k
Fork
1.7k
Merge medio
4g 11h
PR unite (30g)
9

Preparare l'ambiente

Questo progetto non fornisce container di sviluppo, Dockerfile né guida per i contributori, quindi l'ambiente è a tuo carico: parti dal suo README e consulta la nostra guida al primo contributo per i passaggi generali.

Come iniziare

  1. Leggi tutta la issue e poi la guida ai contributi del progetto.
  2. Commenta sulla issue per dire che te ne occupi tu — evita che due persone facciano lo stesso lavoro.
  3. Fai un fork del repository e lavora su un branch.
  4. Apri una pull request che faccia riferimento al numero della issue.

Altre issue di microsoft/agent-lightning

Tutte le issue di microsoft/agent-lightning

Issue simili

Altre issue su Python

Ricevi le nuove issue nella tua casella

Un breve riepilogo di issue GitHub adatte ai principianti.