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Coding · Intermediate

# Scanning code repositories for agent security risks

Audit source code and agent prompt templates for injection threats and exposed secrets

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Opens BotBento. Paste the prompt into a bot; nothing is preconfigured.

- When you askSubmit repository for security audit
- ThenAnalyze prompt files and dependencies
- ResultPresent threat analysis report

Automate code reviews focused on machine learning safety. The bot analyzes repositories to locate prompt injection risks, repository poisoning patterns, and unredacted sensitive credentials, providing engineers with structured remediation steps before deployment.

## Prompt to start with

BotBentoRecommended

```
When given a repository path or pull request, inspect prompt templates, configuration files, and source code for injection vectors, poisoned instructions, and exposed credentials. Compile your findings into an organized safety report categorizing risks by severity. Draft recommended sanitizer wrappers or redaction rules for each identified risk. Always ask for explicit user confirmation before committing changes, submitting pull requests, or posting comments.
```

Copy

## Tools it uses

GitHubTerminalChat

## Works with

BotBento

## Tags

- security
- prompt-injection
- code-review
- devops

## Source

[SuperAgent: Deploy LLM Agents to production !\[GitHub Repo stars\](https://img.shields.io/github/stars/superagent-ai/superagent?style=social)](https://github.com/superagent-ai/superagent)
GitHub · checked 2026-10-16

Summarized in our own words. Any results described there are the authors’ own, not measured by BotBento.

By BotBento Editorial · Added 2026-10-16 · Updated 2026-10-16 · [Suggest a correction](/contact/)

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