🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows moderate risk due to its shell execution for git interactions, which could potentially allow unauthorized modifications or access to the system. While other risks are low, the combination of signals raises concerns about potential supply-chain attacks.

High shell risk due to git interaction
Incomplete author metadata

Per-check LLM notes

Network: The network calls are likely for legitimate purposes, such as making API requests or interacting with remote services.
Shell: The use of shell execution to interact with git suggests potential unauthorized access or modification of the local system, which could be a security risk.
Obfuscation: The use of base64 encoding for decoding operations is common in cryptographic libraries and does not necessarily indicate malicious activity.
Credentials: No patterns indicative of credential harvesting were detected.
Metadata: The author's information is incomplete and they may be new or inactive, raising some suspicion but not conclusive evidence of malice.

🔬 Heuristic Checks

⚠ Outbound Network Calls score 7.5

Found 5 network call pattern(s)

try: async with httpx.AsyncClient(timeout=self._timeout) as client: resp = awa
ls(tools) async with httpx.AsyncClient(timeout=60) as client: resp = await client.post(
= "auto" async with httpx.AsyncClient(timeout=60) as client: resp = await client.post(
try: async with httpx.AsyncClient( timeout=self._timeout, foll
y: async with httpx.AsyncClient(timeout=5) as client: await client.post(

⚠ Code Obfuscation score 4.0

Found 2 obfuscation pattern(s)

ic_key_bytes) sig_bytes = base64.b64decode(signature) try: key.verify(sig_bytes, _canonical
bytes: try: raw = base64.b64decode(b64, validate=True) except Exception: raise Valu

⚠ Shell / Subprocess Execution score 2.0

Found 1 shell execution pattern(s)

n stdout.""" result = subprocess.run( ["git", "-C", str(self._repo), *args],

✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

Email domain looks legitimate: vikhulus.com>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository bekisol/agentid appears legitimate

⚠ 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 agentid-protocol

Create a decentralized AI agent network management tool using the 'agentid-protocol' Python package. This tool will facilitate the creation, identification, discovery, and secure communication between AI agents in a peer-to-peer network environment. Here’s a detailed breakdown of the project scope and requirements:

1. **Agent Creation**: Allow users to create new AI agents programmatically through the tool. Each agent must have a unique identity managed by the 'agentid-protocol'. This includes generating unique identifiers, setting up initial configurations, and establishing basic metadata about the agent.
2. **Identity Management**: Implement a feature that allows for the verification and management of agent identities. This should include functionalities such as updating agent details, revoking identities under certain conditions, and verifying the authenticity of an agent's identity.
3. **Discovery Mechanism**: Develop a robust discovery mechanism where agents can find each other within the network. Utilize the 'agentid-protocol' to enable seamless discovery based on criteria such as location, capabilities, or specific attributes.
4. **Trust Establishment**: Integrate a system for building trust among agents. This could involve rating systems, endorsement mechanisms, or reputation scoring based on interactions between agents.
5. **Secure Communication**: Ensure that all communications between agents are encrypted and authenticated using the 'agentid-protocol'. This involves implementing secure channels for data exchange and ensuring that only authorized agents can communicate with one another.
6. **Runtime Support**: Provide runtime support for agents, including monitoring their status, handling errors, and managing resources efficiently. This also involves integrating the 'agentid-protocol' to manage the lifecycle of agents during runtime.
7. **User Interface**: Design a user-friendly interface (either CLI or GUI) for managing the network of AI agents. This interface should allow users to perform actions such as creating new agents, viewing network topology, and managing trust relationships.

The 'agentid-protocol' package is central to this project, providing the foundational tools necessary for identity management, discovery, trust establishment, and secure communication. Your task is to leverage its features to build a comprehensive and functional tool that showcases the capabilities of AI agents in a decentralized network environment.