🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits several moderate to high-risk behaviors including potential insecure network calls, risky shell invocation, and credential exposure, raising suspicion about its security posture.

Insecure network calls
Risky shell invocation
Potential for API key exposure

Per-check LLM notes

Network: The network calls suggest external API interactions which could be legitimate, but the incomplete URLs and potential typo in 'promp' raise concerns about misconfiguration or unintended behavior.
Shell: The use of subprocess.run and Popen with shell=True is risky as it can lead to arbitrary code execution if not properly sanitized, indicating a significant security concern.
Obfuscation: No obfuscation patterns were detected.
Credentials: The code snippet indicates potential for API key exposure through environment variables or function arguments, which could be a security risk if not properly managed.
Metadata: The package contains non-secure links which could indicate potential security risks, but there are no clear signs of typosquatting or other malicious intent.

🔬 Heuristic Checks

⚠ Outbound Network Calls score 6.0

Found 4 network call pattern(s)

try: response = requests.post( f"{self.api_url}/rl-model/select-next-promp
from a URL""" response = httpx.get(url) encoded_content = base64.b64encode(response.content
etry", 3)) async with httpx.AsyncClient(transport=transport) as client: response = await
URITY}/verify" async with httpx.AsyncClient() as client: response = await client.post(url, json=

✓ Code Obfuscation

No obfuscation patterns detected

⚠ Shell / Subprocess Execution score 8.0

Found 4 shell execution pattern(s)

o generate AIFF audio subprocess.run(["say", "-o", temp_aiff_path, prompt], check=True)
o WAV using afconvert subprocess.run( ["afconvert", "-f", "WAVE", "-d", "LEI16", temp
environment process = subprocess.Popen( command, stdout=subprocess.PIPE, stderr=subproc
env=env, shell=True, ) logger.info(f"Started {command}")

⚠ Credential Harvesting score 2.5

Found 1 credential access pattern(s)

ey = kwargs.get("api_key") or os.getenv("API_KEY") if not api_key: from fastapi import H

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

Email domain looks legitimate: gmail.com

⚠ Suspicious Page Links score 10.0

Found 5 suspicious link(s) on the package page

Non-HTTPS external link: http://0.0.0.0:8718
Non-HTTPS external link: http://0.0.0.0:8718/v1/self-probe
Non-HTTPS external link: http://0.0.0.0:8718/v1/self-probe\nAuthorization:
Non-HTTPS external link: http://0.0.0.0:9094/v1/self-probe-image
Non-HTTPS external link: http://0.0.0.0:9094/v1/self-probe-file

✓ Git Repository History

Repository msoedov/agentic_security appears legitimate

⚠ Maintainer History score 2.0

1 maintainer concern(s) found

Author "Alexander Miasoiedov" 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 agentic_security

Your task is to create a Python-based application named 'VulnerabilityHunter' using the 'agentic_security' package. This application will serve as a comprehensive tool for scanning and identifying potential security vulnerabilities in a given set of URLs or IP addresses. The application should be user-friendly and capable of generating detailed reports on detected vulnerabilities.

Step 1: Installation
- Start by installing the 'agentic_security' package using pip.

Step 2: User Interface
- Design a simple command-line interface where users can input URLs or IP addresses they want to scan.
- Allow users to specify the type of scan they wish to perform (e.g., quick scan, deep scan).

Step 3: Scanning Process
- Utilize 'agentic_security' to perform the scans. Ensure that the application supports both real-time scanning and scheduled scans.
- Implement functionality to detect common vulnerabilities such as SQL injection, XSS, and CSRF.

Step 4: Reporting
- Develop a feature to generate detailed reports upon completion of each scan. Reports should include information like the type of vulnerability, severity level, and steps to mitigate the risk.
- Provide options to export these reports in formats like PDF or CSV.

Suggested Features:
- Real-time vulnerability alerts via email or SMS.
- Historical data tracking for trend analysis.
- Integration with popular bug tracking systems (e.g., Jira).
- Support for multiple languages and locales.

Remember to document your code thoroughly and ensure the application is robust against errors and exceptions.