ansible-rulebook

v1.3.0 suspicious
5.0
Medium Risk

Event driven automation for Ansible

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows moderate risks due to shell execution and credential handling practices, though these alone do not confirm malicious intent. Further investigation into the context of shell command usage and credential management is advised.

  • Shell risk of 7/10
  • Credential risk of 7/10
Per-check LLM notes
  • Network: Network calls appear to be standard for making API requests and are likely used for authentication or external service interactions.
  • Shell: Shell execution patterns indicate the package may execute external commands, which could pose a risk if not properly sanitized or controlled.
  • Obfuscation: Base64 decoding is commonly used for data serialization and may not indicate malicious activity.
  • Credentials: The use of getpass for obtaining a vault password suggests handling sensitive information, potentially indicating secure credential management but also posing a risk if not properly secured.
  • Metadata: The author information is incomplete, suggesting a potentially less experienced maintainer or an automated upload.

📦 Package Quality Overall: Medium (6.4/10)

◈ Medium Test Suite 6.0

Partial test coverage signals detected

  • 2 test file(s) detected (e.g. perf_test.py)
◈ Medium Documentation 7.0

Some documentation present

  • 2 documentation file(s) (e.g. conf.py)
  • Detailed PyPI description (4210 chars)
○ Low Contributing Guide 4.0

No contributing guide or governance files found

  • Development Status classifier >= Beta
◈ Medium Type Annotations 5.0

Partial type annotation coverage

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

Active multi-contributor project

  • 15 unique contributor(s) across 100 commits in ansible/ansible-rulebook
  • Active community — 5 or more distinct contributors

🔬 Heuristic Checks

⚠ Outbound Network Calls score 3.0

Found 2 network call pattern(s)

  • ) self._session = aiohttp.ClientSession( connector=aiohttp.TCPConnector(limit=limit)
  • ket_token_url) async with aiohttp.ClientSession() as session: async with session.post( s
⚠ Code Obfuscation score 8.0

Found 4 obfuscation pattern(s)

  • os.write(project_data_fh, base64.b64decode(data.get("data"))) if not data.get("data") and n
  • _key") raw_data = base64.b64decode(data.get("data")) keys = template_key.split(".")
  • rulebook_raw_data = base64.b64decode(data.get("data")) response.check_vault = has_vau
  • ml.safe_load( base64.b64decode(data.get("data")) ) if data.get("type")
⚠ Shell / Subprocess Execution score 10.0

Found 5 shell execution pattern(s)

  • P"] = "/tmp" output = subprocess.check_output( [settings.ansible_galaxy_path, "collection", "l
  • .CompletedProcess: return subprocess.run( [exec_path, "-XshowSettings:properties", "-version"
  • one try: result = subprocess.run( [settings.ansible_galaxy_path, "collection", "l
  • try: p = subprocess.Popen(parsed_args["<cmd>"], shell=True) process = psut
  • s.Popen(parsed_args["<cmd>"], shell=True) process = psutil.Process(p.pid) wh
⚠ Credential Harvesting score 2.5

Found 1 credential access pattern(s)

  • ss: self.secret = getpass.getpass(prompt="Vault password: ") cli_args = " --ask-va
✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

No author email provided

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository ansible/ansible-rulebook 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 ansible-rulebook 
Create a fully-functional mini-application named 'EventWatcher' that leverages the 'ansible-rulebook' package to monitor and automate responses to specific events within a network environment. This application will serve as an event-driven automation tool that can trigger Ansible playbooks based on predefined rules and conditions. Here are the key steps and features to include in your project:

1. **Project Setup**: Initialize your project using Python's virtual environment. Install the 'ansible-rulebook' package along with any necessary dependencies.
2. **Rule Definition**: Define a set of rules using YAML files. These rules should specify conditions under which certain Ansible playbooks should be executed. For example, a rule might dictate that if a server's CPU usage exceeds a certain threshold, an Ansible playbook should be triggered to scale up resources.
3. **Event Source Integration**: Integrate at least two different types of event sources into your application. These could include log files, system metrics, or even custom API endpoints that simulate events. Ensure that these sources are polled periodically to check for new events.
4. **Playbook Execution**: When an event matches one of the defined rules, your application should execute the corresponding Ansible playbook. Make sure to handle errors gracefully and log all actions taken by the application.
5. **Monitoring & Logging**: Implement a logging mechanism to track all events processed by the application, including details about matched rules and executed playbooks. Consider adding a simple UI or dashboard to visualize this data.
6. **Configuration Management**: Allow users to configure the application through a configuration file or environment variables. This should include settings such as polling intervals, thresholds for triggering playbooks, and paths to event sources.
7. **Testing & Documentation**: Write tests to ensure that your application behaves as expected under various scenarios. Provide comprehensive documentation detailing how to install, configure, and use 'EventWatcher'.

By completing this project, you'll gain hands-on experience with event-driven architectures and Ansible automation, while also contributing a valuable tool for monitoring and managing network environments.

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