AI Analysis
Final verdict: SUSPICIOUS
The package exhibits significant risks due to its execution of shell commands and use of unconventional coding practices, indicating potential malicious intent. While there is no direct evidence of credential theft, the high network and obfuscation risks raise concerns about its true purpose.
- High shell risk
- Significant network risk
- Unconventional coding practices
Per-check LLM notes
- Network: The package makes network calls to external URLs, which could potentially be used for data exfiltration or C2 communications.
- Shell: The package executes shell commands, which is highly suspicious and could indicate the presence of a backdoor or other malicious functionality.
- Obfuscation: The code uses unconventional and potentially misleading import patterns which may serve to obscure the actual functionality of the package.
- Credentials: No suspicious patterns for credential harvesting were detected in the provided code snippet.
- Metadata: The maintainer has a new or inactive PyPI account and the repository shows no activity.
Heuristic Checks
Outbound Network Calls
score 6.0
Found 4 network call pattern(s)
Mozilla/5.0"} html = requests.get(self.form_url, headers=headers).text match = re.sl with data""" res = requests.post(self.form_id.response, data=data, timeout=5) if resne version)""" res = requests.post(form_link, data=data, timeout=5) if res.status_codemeout self.session = requests.Session() # Public API # -----------------------------
Code Obfuscation
score 2.0
Found 1 obfuscation pattern(s)
_pk = importlib.__import__(self.package_name) current: str = _pk.__version__ except
Shell / Subprocess Execution
score 10.0
Found 6 shell execution pattern(s)
".split() return subprocess.run(cmd) except Exception: cmd = f"python".split() return subprocess.run(cmd) def check_for_update( self, *,]".split() try: subprocess.run(cmd) except Exception: try: cmd2[{pkg}]".split() subprocess.run(cmd2) except Exception: click.echo(f"{] result = subprocess.run(cmd, capture_output=True, text=True) data = json.lo_path.resolve())]) subprocess.run(ffmpeg_cmd, stdout=subprocess.DEVNULL, stderr=subprocess.DEV
Credential Harvesting
No credential harvesting patterns detected
Typosquatting
No typosquatting candidates detected
Registered Email Domain
No author email provided
Suspicious Page Links
All external links appear legitimate
Git Repository History
score 2.5
Git history flags: Repository has zero stars and zero forks
Repository has zero stars and zero forks
Maintainer History
score 2.0
1 maintainer concern(s) found
Author "somewhatcold (AbsoluteWinter)" 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 absfuyu
Create a personal task management application using Python, which leverages the 'absfuyu' package for enhanced functionality. This app should allow users to add tasks, mark them as completed, and delete them. Additionally, it should have features such as setting due dates, categorizing tasks into different lists (e.g., Work, Home, Personal), and prioritizing tasks. The 'absfuyu' package can be utilized to handle the core logic of task management. For example, use its functions to store and retrieve tasks efficiently, manage task categories, and handle user inputs. Steps to create the application: 1. Set up your Python environment and install the 'absfuyu' package. 2. Design the user interface for adding, viewing, updating, and deleting tasks. 3. Implement the task management functionalities using 'absfuyu', ensuring tasks are stored persistently and can be retrieved based on various criteria (due date, category, priority). 4. Add additional features like setting reminders for upcoming tasks and generating reports based on task completion rates. 5. Test the application thoroughly to ensure all features work as expected. 6. Document the application's usage and provide instructions for users.