AI Analysis
Final verdict: SUSPICIOUS
The package exhibits significant obfuscation risks and potential for executing arbitrary code, raising concerns about its safety. While there are no clear signs of credential harvesting or severe network/shell risks, the overall risk profile warrants further scrutiny.
- High obfuscation risk due to the presence of eval()
- Potential execution of arbitrary code through obfuscated code
Per-check LLM notes
- Network: The use of urllib to open URLs and cache data suggests the package may fetch external resources, but without more context, it's hard to determine if this is benign or malicious.
- Shell: Executing shell commands and running Python scripts via subprocess could be part of normal functionality, such as testing or configuration, but also raises concerns about potential command injection vulnerabilities or unintended behavior.
- Obfuscation: The presence of eval() and obfuscated code suggests potential for executing arbitrary code, indicating high risk.
- Credentials: No explicit patterns for harvesting credentials were detected.
- Metadata: The maintainer has only one package on PyPI, which may indicate a new or less active account, but no other suspicious activities were flagged.
Package Quality Overall: Medium (6.4/10)
✦ High
Test Suite
9.0
Test suite present — 9 test file(s) found
9 test file(s) detected (e.g. aiotest.py)
◈ Medium
Documentation
7.0
Some documentation present
Documentation URL: "Documentation" -> https://rogerbinns.github.io/apsw/Detailed PyPI description (3016 chars)
○ Low
Contributing Guide
4.0
No contributing guide or governance files found
Development Status classifier >= Beta
◈ Medium
Type Annotations
7.0
Partial type annotation coverage
Classifier: Typing :: Typed309 type-annotated function signatures detected in source
◈ Medium
Multiple Contributors
5.0
Limited contributor diversity
1 unique contributor(s) across 100 commits in rogerbinns/apswSingle author but highly active (100 commits)
Heuristic Checks
Outbound Network Calls
score 1.5
Found 1 network call pattern(s)
-> io.BytesIO: urlopen = urllib.request.urlopen cache_dir, file_name = get_cache_for(url)
Code Obfuscation
score 10.0
Found 6 obfuscation pattern(s)
: pass return eval(expr, imports) def convert_number_ranges(numbers: str) ->isempty(fh[2]) v = eval(get(fh[1])) self.assertEqual(len(v), 1) # 1 tupleisempty(fh[2]) v = eval("(" + get(fh[1]) + ")") # need parentheses otherwise indenttion="Implements SQL function eval() which runs SQL statements recursively", ), Extra(try: exec(compile(f.read(), cmd[0], "exec"), g, g) finally:es["vend"] = vend exec(compile(pathlib.Path("tools/vend.py").read_text("utf8"), "tools/ven
Shell / Subprocess Execution
score 10.0
Found 6 shell execution pattern(s)
t len(cmd) == 1 res = os.system(cmd[0]) if res != 0: self.write_error(f"e, in_stderr=""): p = subprocess.run(cmd, capture_output=True, encoding="utf8", text=True)env = None proc = subprocess.run( [sys.executable] + cov_params + ["-m", "apsw.ftenv = None return subprocess.run( [sys.executable] + cov_params + ["-m", "apsw.unenv[v] = val subprocess.check_call(["./configure"], cwd="sqlite3", env=env) # We allow enablesError): cflags = subprocess.run(["pkg-config", "--cflags", "icu-io"], **skw).stdout.strip()
Credential Harvesting
No credential harvesting patterns detected
Typosquatting
No typosquatting candidates detected
Registered Email Domain
Email domain looks legitimate: rogerbinns.com
Suspicious Page Links
All external links appear legitimate
Git Repository History
Repository rogerbinns/apsw appears legitimate
Maintainer History
score 2.0
1 maintainer concern(s) found
Author "Roger Binns" 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 apsw
Create a simple task management application using Python and the APSW package. This application will allow users to manage their daily tasks efficiently by adding, updating, deleting, and listing tasks stored in an SQLite database. The application should have a user-friendly command-line interface for interaction. Here’s a detailed breakdown of the steps and features you need to implement:
1. **Setup**: Install the APSW package and create a new SQLite database for storing tasks.
2. **Database Initialization**: Use APSW to create necessary tables (e.g., 'tasks') with columns like 'id', 'title', 'description', 'status', and 'due_date'.
3. **Add Task**: Implement a function that allows users to add new tasks to the database. Ensure that the user inputs a title, description, status ('pending' or 'completed'), and due date.
4. **List Tasks**: Develop a feature that lists all tasks in the database, showing their details in a readable format.
5. **Update Task**: Create functionality for updating any task's information, including its status and due date.
6. **Delete Task**: Allow users to delete specific tasks based on their ID.
7. **Search Tasks**: Implement a search feature where users can find tasks by providing keywords from the title or description.
8. **Status Tracking**: Enable tracking of task completion statuses through a command that shows only pending or completed tasks.
9. **User Interface**: Design a simple and intuitive command-line interface that guides users through these operations.
Use APSW throughout the project to interact with the SQLite database, ensuring efficient and effective data handling. Remember to include error handling and validation checks for user inputs to enhance the reliability and usability of your application.