🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows moderate risks, particularly concerning obfuscation and metadata anomalies. While the network and shell risks are relatively low, the combination of factors raises concerns about potential malicious intent.

moderate obfuscation risk
minimal activity and single contributor

Per-check LLM notes

Network: The use of an HTTP client suggests the package may communicate over the network, which is not inherently suspicious but should be reviewed for the legitimacy of its network activities.
Shell: No shell execution patterns detected, indicating low risk of direct system command execution.
Obfuscation: The presence of base64 decoding suggests potential obfuscation, but without more context, it's unclear if this is intended for legitimate encoding purposes or as a form of obfuscation.
Credentials: No patterns indicative of credential harvesting were found.
Metadata: The package shows signs of being potentially malicious due to minimal activity, single contributor, and lack of maintainer history.

🔬 Heuristic Checks

⚠ Outbound Network Calls score 1.5

Found 1 network call pattern(s)

else: async with httpx.AsyncClient(timeout=timeout_ms / 1000) as client: resp = awa

⚠ Code Obfuscation score 2.0

Found 1 obfuscation pattern(s)

(s: str) -> bytes: return base64.b64decode(s) """Public types for agent-cid (Python port).""" from __

✓ 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: 2 total
Single contributor with only 2 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 agent-cid

Create a mini-application called 'AgentCidManager' that leverages the 'agent-cid' Python package to manage content-addressed artifacts for AI agents. This tool will serve as a simple yet powerful utility for developers and data scientists who work with AI models and need to efficiently handle and track their artifacts.

The application should include the following core functionalities:
1. **Artifact Registration**: Users should be able to register new artifacts with the application. Each artifact must have a unique identifier based on its content (content-addressed).
2. **Artifact Retrieval**: Once registered, users should be able to retrieve artifacts using their unique identifiers.
3. **Artifact Validation**: The application should validate the integrity of the artifacts by comparing their current state with the original content-addressed identifier.
4. **Artifact Versioning**: Support for multiple versions of the same artifact, allowing users to keep track of different states of development.
5. **Artifact Sharing**: Implement functionality to share artifact identifiers securely, enabling collaboration among team members.
6. **User Interface**: Develop a command-line interface (CLI) for easy interaction with the application.
7. **Documentation**: Provide comprehensive documentation detailing how to use each feature of the application.

The 'agent-cid' package will be utilized extensively throughout the project. Specifically, it will be used for generating content-addressed identifiers for artifacts, validating these identifiers, and managing the versioning of artifacts. Additionally, explore how the package can enhance the security and efficiency of artifact sharing within the application.