airefinery-sdk

v1.31.3 suspicious
4.0
Medium Risk

AI Refinery™ by Accenture SDK for developing and executing AI multi-agent solutions.

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package has a moderate risk score due to potential obfuscation techniques and a new author account with limited metadata. Further investigation is recommended.

  • Potential obfuscation through base64 decoding
  • New author account with insufficient metadata
Per-check LLM notes
  • Network: The detected network calls seem to be standard HTTP POST requests which could be part of the legitimate functionality for an SDK that interacts with some service.
  • Shell: No shell execution patterns were detected.
  • Obfuscation: The observed base64 decoding patterns could indicate obfuscation but are likely part of normal functionality for handling encoded data.
  • Credentials: No evidence of credential harvesting patterns detected.
  • Metadata: Low risk but warrants further investigation due to the new author account and lack of detailed metadata.

📦 Package Quality Overall: Low (4.6/10)

○ Low Test Suite 1.0

No test suite detected

  • No test files or test-runner configuration detected
◈ Medium Documentation 5.0

Some documentation present

  • Detailed PyPI description (9357 chars)
○ Low Contributing Guide 2.0

No contributing guide or governance files found

  • No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
◈ Medium Type Annotations 5.0

Partial type annotation coverage

  • 229 type-annotated function signatures detected in source
✦ High Multiple Contributors 10.0

Active multi-contributor project

  • 6 unique contributor(s) across 49 commits in Accenture/airefinery-sdk
  • Active community — 5 or more distinct contributors

🔬 Heuristic Checks

⚠ Outbound Network Calls score 9.0

Found 6 network call pattern(s)

  • rows} response = requests.post( self.index_url, headers=self.headers, json=
  • } response = requests.post( url=self.search_url, header
  • w)}\n" response = requests.post( self.index_url, headers=sel
  • } response = requests.post( self.search_url, headers=se
  • ---------- resp = requests.post( endpoint, data=payload,
  • treamEvent]: with requests.post( endpoint, data=payload,
⚠ Code Obfuscation score 10.0

Found 6 obfuscation pattern(s)

  • audio_bytes = base64.b64decode(data["audio"]) events = [
  • yield base64.b64decode(data["data"]) elif data[
  • audio_bytes = base64.b64decode(data["audio"]) events = [
  • yield base64.b64decode(data["data"]) elif data["type"]
  • audio_bytes = base64.b64decode(audio_chunk) audio_bytes = np.frombuffer(aud
  • base64.b64decode(audio_data) )
✓ 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: accenture.com>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository Accenture/airefinery-sdk appears legitimate

⚠ Maintainer History score 4.0

2 maintainer concern(s) found

  • Author "Accenture" appears to have only 1 package on PyPI (new or inactive account)
  • Package has no PyPI classifiers (low effort / metadata quality)
✓ Known CVE Vulnerabilities

No known vulnerabilities found in OSV database.

💡 AI App Starter Prompt

Use this prompt to build a project with airefinery-sdk 
Develop a mini-application named 'AIRefineryChat' using the 'airefinery-sdk' package to demonstrate its capabilities in creating and managing AI multi-agent systems. This application will serve as a conversational interface where users can engage with multiple AI agents, each programmed for specific tasks or knowledge domains. For instance, one agent could be specialized in providing weather forecasts, another in offering travel advice based on user preferences, and yet another in answering general trivia questions. Users should be able to switch between these agents seamlessly and even request a combination of services from different agents simultaneously.

Core Features:
1. User Authentication: Allow users to sign up and log in to the application.
2. Agent Selection Interface: Provide a graphical or command-line interface for users to select which AI agent they want to interact with.
3. Multi-Agent Conversations: Enable the application to manage conversations with multiple agents at once, ensuring context is maintained between exchanges.
4. Customizable Agents: Offer the capability to customize agents based on user needs, such as adding new knowledge bases or changing response styles.
5. Analytics Dashboard: Include a feature that allows administrators to monitor performance metrics of deployed agents, like response time and accuracy.

Utilizing 'airefinery-sdk':
- Use the SDK to create and configure the AI agents for the application.
- Implement the SDK's API to handle interactions between users and agents.
- Leverage the SDK's tools for monitoring and optimizing agent performance.
- Integrate the SDK's security features to ensure safe user interactions with AI agents.

💬 Discussion Feed

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