Pre-execution security guardrails for your agent execution loops
Maintainers usually reply within 1 day
Nobody has claimed this yet.
Assessment
- Difficulty
- 5/5
- Estimated time
- Over a week
- Newbie friendliness
- 15/100
- Issue type
- Feature
- Clarity
- Needs clarification
- Activity status
- Active
- Domain
- ai-infra-agents, security
Research direction
The issue proposes an opt-in pre-execution security hook for agent execution loops but names no files, tests, or integration points. Start by reading the repository’s agent execution and tool invocation entry points to assess where a hook could fit. Done would require an agreed scope and integration plan; the issue does not specify expected behavior or tests.
Written by the indexing model from the issue text.
Description
Hey team 👋
When autonomous AI agents execute shell commands or code loops, prompt injections and hallucinations can accidentally run destructive commands (e.g., rm -rf, environment secret exfiltration, or unauthorized process spawns).
We built a lightweight, pre-execution security engine in Python & FastAPI that intercepts command strings at the execution boundary and blocks threats in ~1.3ms to 3ms before they hit the terminal.
🛡️ Key Features:
- Sub-3ms Overhead: Zero noticeable delay in agent execution loops.
- 48/48 Integration Tests: Benchmark-verified on live terminal agent workflows.
- Zero-Network Privacy Option: Runs 100% offline via local Python import or through a hosted API endpoint.
Would you be open to an opt-in pre-execution security hook for your repo, or trying a free test API key for your core maintainer team this week?
- Dominant language
- Python
- Stars
- 30.2k
- Forks
- 4.9k
- Avg merge
- 11h 46m
- Merged PRs (30d)
- 160
Getting set up
- No Dockerfile or Docker Compose file
- Has a pull request template
- Read the contributing guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
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