agentidemp-py

v0.1.0 suspicious
5.0
Medium Risk

Idempotency keys for LLM agent retries. Deterministic content-derived keys (sha256-hex, UUIDv5, scoped). Pairs with cachebench miss-aware retry. Zero runtime deps.

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows no immediate signs of malicious intent such as network calls or shell executions. However, the metadata risk score is high due to low repository activity and a single commit, which raises concerns about potential supply-chain attacks.

  • High metadata risk due to low repository activity
  • Single commit in the repository
Per-check LLM notes
  • Network: No network calls detected, which is normal unless the package requires external communication for its functionality.
  • Shell: No shell execution patterns detected, indicating low risk of executing unauthorized commands.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The repository's low activity and single commit suggest it may be suspicious.

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

✓ Code Obfuscation

No obfuscation patterns detected

✓ Shell / Subprocess Execution

No shell execution patterns detected

✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

Email domain looks legitimate: gmail.com>

✓ Suspicious Page Links

All external links appear legitimate

⚠ Git Repository History score 7.5

Git history flags: Repository has zero stars and zero forks

  • Repository has zero stars and zero forks
  • Very few commits: 1 total
  • Single contributor with only 1 commit(s) — possibly throwaway account
⚠ Maintainer History score 6.0

3 maintainer concern(s) found

  • Only one version has ever been released — brand new package
  • Author name is missing or very short
  • Author "" appears to have only 1 package on PyPI (new or inactive account)
✓ Known CVE Vulnerabilities

No known vulnerabilities found in OSV database.

💡 AI App Starter Prompt

Use this prompt to build a project with agentidemp-py 
Create a simple web-based task management application using Python Flask and integrate it with the 'agentidemp-py' package for handling retries of tasks when they fail due to transient errors. This application will allow users to create, view, update, and delete tasks. Additionally, the app will demonstrate how to use idempotency keys to ensure that tasks can be retried without duplication or unintended side effects.

### Application Features:
1. **User Authentication:** Users can register, login, and logout securely.
2. **Task Management:** Users can create new tasks, view their tasks, update task status, and delete completed tasks.
3. **Retry Mechanism:** Implement a retry mechanism for task processing using 'agentidemp-py'. When a task fails, it should be retried using an idempotency key to ensure that the task is processed exactly once, even if multiple retries are attempted.
4. **Logging:** Log all task operations and retry attempts for auditing purposes.
5. **UI/UX:** Design a simple, user-friendly interface using HTML/CSS/JS.

### Utilizing 'agentidemp-py':
- **Idempotency Keys Generation:** Use 'agentidemp-py' to generate unique idempotency keys for each task based on deterministic content-derived methods like SHA256 hex or UUIDv5.
- **Retry Logic:** Integrate 'agentidemp-py' with your task processing logic to handle retries gracefully. If a task fails, store its idempotency key and try to process it again until it succeeds or reaches a maximum retry count.
- **Cache Integration:** Optionally, pair 'agentidemp-py' with a caching system (like Redis) to avoid unnecessary retries by checking if the task has already been processed using its idempotency key.

### Step-by-Step Guide:
1. Set up a Flask application with user authentication.
2. Create endpoints for CRUD operations on tasks.
3. Implement a task processing function that generates an idempotency key for each task using 'agentidemp-py'.
4. Add retry logic to the task processing function using the idempotency key.
5. Test the application thoroughly to ensure that tasks are processed correctly, even with simulated failures.
6. Deploy the application to a platform like Heroku or AWS for easy access.