🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows significant signs of potential malicious activity, especially concerning credential risk and obfuscation. While some risks may be justified for functionality, the overall pattern is alarming.

High credential risk due to access attempts to critical system files
Significant obfuscation techniques observed

Per-check LLM notes

Network: The network calls could be legitimate if the package is designed to communicate with external services or APIs.
Shell: The shell execution might indicate that the package performs system-specific tasks, but it's risky and could potentially execute arbitrary commands.
Obfuscation: The presence of patterns related to bypassing comments and executing commands suggests potential obfuscation or evasion techniques.
Credentials: Access attempts to critical system files like /etc/shadow and /etc/passwd indicate a high risk of credential harvesting or unauthorized access.

🔬 Heuristic Checks

⚠ Outbound Network Calls score 4.5

Found 3 network call pattern(s)

with ( socket.create_connection((hostname, port), timeout=timeout) as sock,
: resp = httpx.get(f"{base}{endpoint}", timeout=timeout) i
try: resp = httpx.get(url, timeout=timeout, follow_redirects=True)

⚠ Code Obfuscation score 8.0

Found 4 obfuscation pattern(s)

): pipe.model.eval() _d3_state["pipeline"] = pipe _d3_s
ned("gpt2") model.eval() _d4_state["model"] = model _d4_sta
Li_comment_bypass"), (re.compile(r"'\s*;\s*exec\b|\bxp_cmdshell\b|\bsp_executesql\b", re.I), 1.0, "SQLi_exec"), (re.compile(r"\bwa
"CmdInj_python_os"), (re.compile(r"exec\s*\(|eval\s*\(|compile\s*\(", re.I), 0.85, "CmdInj_eval"),

⚠ Shell / Subprocess Execution score 2.0

Found 1 shell execution pattern(s)

process result = subprocess.run( ["ioreg", "-rd1", "-c", "IOPlatformExpertD

⚠ Credential Harvesting score 10.0

Found 4 credential access pattern(s)

e", params={"path": "/etc/passwd"}, agent_id="my-agent", input_data="Ignor
"{'path': '/etc/passwd'} or {'query': 'SELECT *'}" ),
Critical system config ("/etc/shadow", 4.0), ("/etc/passwd", 4.0), ("/etc/*", 4.0),
("/etc/shadow", 4.0), ("/etc/passwd", 4.0), ("/etc/*", 4.0), # User secret material

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

No author email provided

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

No GitHub repository linked

No GitHub repository link found

⚠ Maintainer History score 2.0

1 maintainer concern(s) found

Author "Agastya Todi" 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 agentarmor-core

Develop a secure chatbot application using the 'agentarmor-core' package. This application will serve as a personal assistant, capable of performing tasks such as scheduling appointments, setting reminders, and providing weather updates. It will also include a feature where users can ask for news updates on specific topics.

The application should adhere to strict security protocols, utilizing all eight layers of defense provided by 'agentarmor-core'. These layers include physical security, network security, host security, application security, data security, identity management, operational security, and compliance.

Here are the steps to develop the application:
1. Set up a virtual environment and install necessary packages including 'agentarmor-core'.
2. Design the application architecture, ensuring it integrates seamlessly with 'agentarmor-core'.
3. Implement user authentication and authorization mechanisms leveraging 'agentarmor-core's identity management layer.
4. Develop functionalities for scheduling, reminders, and weather updates, ensuring these features are protected under 'agentarmor-core's application security layer.
5. Integrate a news API to fetch and provide news updates based on user preferences, with data secured according to 'agentarmor-core's data security guidelines.
6. Test the application thoroughly to ensure all features work as expected while adhering to the security standards set by 'agentarmor-core'.
7. Deploy the application, maintaining compliance with regulations through 'agentarmor-core's compliance layer.
8. Monitor the application's performance and security status continuously, using 'agentarmor-core's operational security tools.

Throughout development, utilize 'agentarmor-core' to implement comprehensive security measures at every stage, from initial setup to deployment and ongoing maintenance.