ain-state-compiler

v0.4.0 suspicious
7.0
High Risk

The G-Brain Company Brain Primitive: continuously compiles Slack, Jira, and Gmail into an executable, conflict-resolved operational state for AI agents.

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows significant potential risks related to shell execution and credential handling, indicating possible misuse. Additionally, metadata inconsistencies raise concerns about the package's legitimacy.

  • High shell risk due to external command execution
  • Potential credential harvesting activities
  • Inconsistent metadata and short maintainer history
Per-check LLM notes
  • Network: Network calls include fetching URLs and making HTTP requests, which may be legitimate but warrant further investigation to ensure they are not used for unauthorized data transfer.
  • Shell: Shell executions involve running external commands and installing software, which could indicate potential risks such as downloading and executing malicious code or installing unwanted software.
  • Obfuscation: No obfuscation patterns detected in the provided code snippets.
  • Credentials: The code snippet indicates potential interactive harvesting of credentials which could be used for storing secrets securely but also poses a risk if not handled properly.
  • Metadata: The package has several red flags including a non-existent git repository, a very short maintainer history, and an author with limited information.

📦 Package Quality Overall: Low (3.2/10)

○ Low Test Suite 1.0

No test suite detected

  • No test files or test-runner configuration detected
◈ Medium Documentation 7.0

Some documentation present

  • Documentation URL: "Documentation" -> https://github.com/sambitmishra98/ain-state-compiler#readme
  • Detailed PyPI description (9295 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

  • 31 type-annotated function signatures detected in source
○ Low Multiple Contributors 1.0

Could not retrieve contributor data from GitHub

  • GitHub API error: 404

🔬 Heuristic Checks

⚠ Outbound Network Calls score 7.5

Found 5 network call pattern(s)

  • try: urllib.request.urlretrieve(installer_url, installer_path) _
  • ) if body else None req = urllib.request.Request( url, data=data, method=meth
  • , ) try: with urllib.request.urlopen(req, timeout=30) as resp: return json.lo
  • url = f"{url}?{qs}" req = urllib.request.Request( url, headers={"Authorization": f"Be
  • e}).encode("utf-8") req = urllib.request.Request( ollama_url, data=payload, h
✓ Code Obfuscation

No obfuscation patterns detected

⚠ Shell / Subprocess Execution score 10.0

Found 6 shell execution pattern(s)

  • on PATH.""" try: subprocess.run( [cmd, "--version"], stdout=subproce
  • s admin)...") subprocess.run( [installer_path, "/S"],
  • try: subprocess.run( "curl -fsSL https://ollama.com/install.
  • try: subprocess.run(["brew", "install", "ollama"], check=True) _
  • inutes)...") try: subprocess.run(["ollama", "pull", model], check=True) _print(f"[+]
  • try: result = subprocess.run( ["powershell", "-ExecutionPolicy", "Bypass"
⚠ Credential Harvesting score 5.0

Found 2 credential access pattern(s)

  • b-...)", secret=True, default=os.environ.get("SLACK_BOT_TOKEN", "")) # ---- Jira ---- _print("\n[2/5] J
  • if secret: val = getpass.getpass(full_label) else: val = input(full_label
✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

Email domain looks legitimate: ain-compiler.ai>

✓ Suspicious Page Links

All external links appear legitimate

⚠ Git Repository History score 3.0

Repository not found (deleted or private)

  • Repository not found (deleted or private)
⚠ Maintainer History score 6.0

3 maintainer concern(s) found

  • Package is very new: uploaded 2 day(s) ago
  • 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 ain-state-compiler 
Create a mini-app called 'OperationalSync' that integrates with Slack, Jira, and Gmail to provide a unified operational state for AI agents to execute tasks. The app should compile real-time data from these platforms, resolve any conflicts, and present a clean, actionable state for AI-driven workflows.

Step 1: Set up the project structure and install necessary packages including 'ain-state-compiler'.
Step 2: Develop APIs for connecting to Slack, Jira, and Gmail using their respective SDKs or APIs.
Step 3: Implement a state compiler using 'ain-state-compiler' to continuously fetch, process, and integrate data from all three platforms.
Step 4: Design a conflict resolution mechanism within the compiler to handle discrepancies between data sources.
Step 5: Create a user-friendly interface (web or CLI) where users can view the compiled state and initiate actions based on it.
Step 6: Integrate AI capabilities to suggest optimized workflows based on the compiled state.

Suggested Features:
- Real-time updates from Slack, Jira, and Gmail.
- Conflict detection and resolution logs.
- User-defined rules for workflow optimization.
- Actionable insights and task recommendations for users.
- Customizable views for different roles (e.g., managers, developers).

Utilize 'ain-state-compiler' to streamline the integration process and ensure the compiled state is accurate and consistent across all platforms.