aacp

v1.4.0 suspicious
5.0
Medium Risk

Agent Action Compression Protocol — pipe-delimited coordination for multi-agent LLM systems

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package is flagged due to potential typosquatting and low maintainer activity, raising concerns about its legitimacy and ongoing support. Despite low risks in network, shell, obfuscation, and credential aspects, these signals combined with metadata risks suggest caution.

  • Potential typosquatting targeting 'amqp'
  • Low maintainer activity
Per-check LLM notes
  • Network: The package attempts to fetch data from external URLs which could be legitimate if it's intended for rule updates or configuration retrieval.
  • Shell: No shell execution patterns detected, indicating low risk of direct system command abuse.
  • Obfuscation: No obfuscation patterns detected, suggesting low risk.
  • Credentials: No credential harvesting patterns detected, indicating safe usage.
  • Metadata: The package shows signs of potential typosquatting and has low maintainer activity.
  • ⚠ Typosquatting target: amqp

🔬 Heuristic Checks

⚠ Outbound Network Calls score 3.0

Found 2 network call pattern(s)

  • try: with urllib.request.urlopen(COMMUNITY_RULES_URL, timeout=10) as resp:
  • try: with urllib.request.urlopen(endpoint, timeout=10) as resp: data
✓ Code Obfuscation

No obfuscation patterns detected

✓ Shell / Subprocess Execution

No shell execution patterns detected

✓ Credential Harvesting

No credential harvesting patterns detected

⚠ Typosquatting score 3.0

Possible typosquat of: amqp

  • "aacp" is 2 edit(s) from "amqp"
✓ Registered Email Domain

Email domain looks legitimate: gmail.com>

✓ Suspicious Page Links

All external links appear legitimate

⚠ Git Repository History score 2.5

Git history flags: Repository has zero stars and zero forks

  • Repository has zero stars and zero forks
⚠ Maintainer History score 4.0

2 maintainer concern(s) found

  • 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 aacp 
Create a Python-based mini-application named 'MultiAgentChat' that leverages the 'aacp' package for managing communication between multiple agents in a chat system. This application will serve as a proof-of-concept for coordinating actions and responses among different AI agents using the Agent Action Compression Protocol (AACP). The main goal of 'MultiAgentChat' is to demonstrate efficient and seamless interaction between agents in a simulated chat environment, where each agent has a specific role or capability.

### Key Features:
- **Agent Registration**: Allow users to register different types of agents (e.g., information retrieval, language translation, emotion analysis) within the system.
- **Message Routing**: Implement a mechanism to route messages to the appropriate agent based on predefined rules or tags.
- **Response Aggregation**: Collect responses from multiple agents and combine them into a coherent reply to the user.
- **Error Handling**: Ensure robust error handling to manage cases where an agent fails to respond or encounters issues during processing.
- **User Interface**: Develop a simple command-line interface (CLI) for users to interact with the system, including options to send messages, view agent status, and manage configurations.

### Utilizing the 'aacp' Package:
- **Communication Protocol**: Use the AACP provided by 'aacp' to establish a reliable communication channel between the main application and the registered agents. This includes setting up pipes for message passing and defining the structure of messages exchanged between entities.
- **Agent Coordination**: Leverage the capabilities of 'aacp' to synchronize actions among agents, ensuring that they can work together effectively to process complex queries or tasks.
- **Efficiency Improvements**: Explore how AACP can optimize the performance of the system, particularly in scenarios involving real-time data processing or high-volume interactions.

### Development Steps:
1. **Setup Environment**: Install Python and the 'aacp' package in your development environment.
2. **Design Architecture**: Plan out the overall architecture of 'MultiAgentChat', including the roles of the main application and individual agents.
3. **Implement Core Functionality**: Start coding the core functionalities such as agent registration, message routing, and response aggregation.
4. **Integrate 'aacp'**: Integrate the AACP protocol into the communication framework of 'MultiAgentChat'.
5. **Develop CLI**: Create a user-friendly CLI for interacting with the application.
6. **Testing & Debugging**: Thoroughly test the application to ensure all components work seamlessly together.
7. **Documentation & Deployment**: Write comprehensive documentation and prepare for deployment.

This project aims to showcase the potential of using advanced protocols like AACP for building sophisticated multi-agent systems in Python.