🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits moderate risk due to potential execution of unsanitized shell commands and incomplete author information. While there are no direct signs of malicious activity, the combination of these factors raises concerns about the package's integrity.

Executing shell commands directly using os.system
Incomplete author information and single package maintenance

Per-check LLM notes

Network: The network call appears to be downloading a compressed file from a URL, which is common for packages that require external resources.
Shell: Executing shell commands directly using os.system can introduce security risks, especially if the command strings are not properly sanitized or controlled.
Obfuscation: No obfuscation patterns detected, indicating low risk of malicious intent.
Credentials: No credential harvesting patterns detected, suggesting safe handling of sensitive information.
Metadata: The author information is incomplete and the maintainer has only one package, which may indicate a less experienced or potentially suspicious actor.

🔬 Heuristic Checks

⚠ Outbound Network Calls score 1.5

Found 1 network call pattern(s)

.join(homedir,"Rfam.cm") urllib.request.urlretrieve(url, gz_file_path) with gzip.open(gz_file_p

✓ Code Obfuscation

No obfuscation patterns detected

⚠ Shell / Subprocess Execution score 4.0

Found 2 shell execution pattern(s)

shortseq]) + '\n') os.system("cmscan --notextw -E 1e-4 -o {} --rfam --toponly {} {}".form
copyfileobj(f_in, f_out) os.system("cmpress {}".format(output_file_path)) ''' if __name__ =

✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

Email domain looks legitimate: gmail.com>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository febos/SQUARNA appears legitimate

⚠ Maintainer History score 4.0

2 maintainer concern(s) found

Author name is missing or very short
Author "" 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 SQUARNA

Develop a user-friendly RNA Secondary Structure Prediction Tool using the SQUARNA package in Python. This application will allow users to input RNA sequences and receive visual representations of their predicted secondary structures. Key functionalities include:

1. User Interface: Design a simple web-based interface where users can enter RNA sequences.
2. Input Validation: Ensure the entered RNA sequence is valid (consists only of A, U, C, G).
3. Prediction Engine: Utilize SQUARNA to predict the secondary structure of the input RNA sequence.
4. Visualization: Display the predicted secondary structure using a graphical representation such as a dot-bracket notation or a base-pair plot.
5. Explanation: Provide a brief explanation of the predicted structure, highlighting any notable features like hairpins, bulges, internal loops, and pseudoknots.
6. Save & Share: Allow users to save the predicted structure and share it via a unique URL.

The project should leverage SQUARNA's capabilities for accurate RNA secondary structure prediction, making it accessible to researchers and students alike through an intuitive and interactive web application.