🤖 AI Analysis

Final verdict: SAFE

The package has minimal risks associated with it, with no signs of malicious activity. The primary concern lies in the shell execution patterns and metadata maintenance, but these do not indicate any immediate threat.

Low network risk
Potential issues with shell execution need further investigation
Minimal effort in metadata management

Per-check LLM notes

Network: No network calls were detected.
Shell: Shell execution patterns observed are likely related to the package's functionality, but further investigation is needed to ensure there is no unintended behavior.
Obfuscation: No obfuscation patterns detected, indicating low risk.
Credentials: No credential harvesting patterns detected, indicating low risk.
Metadata: The package shows low effort in maintaining metadata and author details, but there are no clear signs of malicious intent or typosquatting.

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

✓ Code Obfuscation

No obfuscation patterns detected

⚠ Shell / Subprocess Execution score 10.0

Found 5 shell execution pattern(s)

lingo is accessible. try: subprocess.call(['clingo', '--version'], stdout=subprocess.PIPE, stderr=subp
hich('clingo') response = subprocess.Popen(['clingo', '--version'], stdout=subprocess.PIPE, start_new_s
svg_output] subproc = subprocess.Popen(oog_cmds) subproc.wait() def convert_taxon_id(taxo
l(toy_tgz_bact, respath) subprocess.call([ 'm2m', 'addedvalue', '-n', toy_bact, '-o',
draft_tgz_path, respath) subprocess.call([ 'm2m_analysis', 'enum', '-n', draft_path, '-o',

✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

Email domain looks legitimate: inria.fr>

⚠ Suspicious Page Links score 10.0

Found 7 suspicious link(s) on the package page

Non-HTTPS external link: http://www.ncbi.nlm.nih.gov/pubmed/15712108
Non-HTTPS external link: http://doi.wiley.com/10.1111/tpj.12627
Non-HTTPS external link: http://dx.plos.org/10.1371/journal.pcbi.1005276
Non-HTTPS external link: http://www.ncbi.nlm.nih.gov/pubmed/19425125
Non-HTTPS external link: http://bioinformatics.ai.sri.com/ptools/
Non-HTTPS external link: http://gnu.org/licenses/gpl.html

✓ Git Repository History

Repository aureme/metage2metabo appears legitimate

⚠ 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 Metage2Metabo

Develop a web-based mini-application using Python and Flask that leverages the 'Metage2Metabo' package to automatically reconstruct draft metabolic networks from given genomic data. This application should allow users to upload their own genomic datasets, specify organism details, and receive a reconstructed metabolic network as output. Additionally, include features such as visualization of the reconstructed network, basic pathway analysis, and export options for the network data. Utilize Metage2Metabo's capabilities for automatic reconstruction and graph-based metabolic analysis to provide users with insights into the metabolic pathways of their organisms of interest.