🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits significant network and shell risks, suggesting potential unauthorized external communication and execution of subprocesses. While there are no definitive signs of credential theft, the combination of these factors raises concerns about possible malicious intent.

High network risk
High shell risk

Per-check LLM notes

Network: The presence of network connection attempts and HTTP requests suggests potential unauthorized external communication.
Shell: Subprocess calls to execute scripts or commands might indicate the package is designed to run additional processes, which could be used for malicious purposes.
Obfuscation: The code shows signs of obfuscation through base64 encoding, which could be used for legitimate purposes such as data encryption but may also indicate attempts to hide malicious activities.
Credentials: No clear patterns indicating credential harvesting have been detected.
Metadata: The package shows low maintainer activity and poor metadata quality, raising suspicion but not conclusive evidence of malice.

🔬 Heuristic Checks

⚠ Outbound Network Calls score 7.5

Found 5 network call pattern(s)

try: with socket.create_connection((host, port), timeout=0.5): return True
try: with socket.create_connection((host, port), timeout=0.5): return e
try: with socket.create_connection((host, port), timeout=0.3): return True
try: with urllib.request.urlopen(f"http://{host}:{port}/healthz", timeout=0.5) as r:
ken=...)`` and drive it via ``httpx.AsyncClient(transport=ASGITransport(app))``. """ from __future__ import

⚠ Code Obfuscation score 8.0

Found 4 obfuscation pattern(s)

ionCount"]), salt=base64.b64decode(sub["salt"]), stored_key=base64.b64decode(sub["s
lt"]), stored_key=base64.b64decode(sub["storedKey"]), server_key=base64.b64decode(s
ey"]), server_key=base64.b64decode(sub["serverKey"]), mechanism=mechanism,
try: client_proof = base64.b64decode(client_proof_b64, validate=False) except Exception as ex

⚠ Shell / Subprocess Execution score 10.0

Found 6 shell execution pattern(s)

ss on ``port``.""" return subprocess.Popen( [ sys.executable, "-m", "secantus",
cess.Popen[bytes]: return subprocess.Popen( [ sys.executable, "-m", "bench.load_wri
ort = _free_port() proc = subprocess.Popen( [ sys.executable, "-m", "secantus",
dir / "mongod.log" proc = subprocess.Popen( [ "mongod", "--bind_ip", "1
cess.Popen[bytes]: return subprocess.Popen( [ sys.executable, "-m", "secantus",
end("--drop") p = subprocess.Popen( argv, stdin=subprocess.DEVN

✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

Email domain looks legitimate: joedrumgoole.com>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

No GitHub repository linked

No GitHub repository link found

⚠ Maintainer History score 6.0

3 maintainer concern(s) found

Author name is missing or very short
Author "" appears to have only 1 package on PyPI (new or inactive account)
Package has no PyPI classifiers (low effort / metadata quality)

✓ Known CVE Vulnerabilities

No known vulnerabilities found in OSV database.

💡 AI App Starter Prompt

Use this prompt to build a project with SecantusDB

Create a mini-library management system using the Python package 'SecantusDB'. This application will allow users to manage a collection of books, including adding new books, updating book details, searching for books by title or author, and deleting books from the library catalog. Additionally, implement features to track borrowed books and manage user accounts. Utilize 'SecantusDB' as the backend database to store all information related to books and users. Ensure that your application can perform CRUD operations efficiently, leveraging the MongoDB compatibility of 'SecantusDB'. Include error handling and validation checks to ensure data integrity. Finally, provide a simple command-line interface for interacting with the library management system.