AI Analysis
Final verdict: SAFE
The package shows minimal risk indicators with no network calls, shell executions, or obfuscation techniques observed. The metadata suggests a new or less active maintainer, but this alone does not indicate a supply-chain attack.
- No network calls
- No shell executions
- Single package from maintainer
Per-check LLM notes
- Network: No network calls detected, which is normal unless the package requires network interactions.
- Shell: No shell executions detected, indicating no immediate signs of malicious activities.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: The maintainer has only one package, which could indicate a new or less active account, but no other suspicious activities are flagged.
Heuristic Checks
Outbound Network Calls
No suspicious network call patterns found
Code Obfuscation
No obfuscation patterns detected
Shell / Subprocess Execution
No shell execution patterns detected
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 MDU-PHL/abritamr appears legitimate
Maintainer History
score 2.0
1 maintainer concern(s) found
Author "Kristy Horan" 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 abritamr
Create a command-line tool named 'AMRScanner' using Python that leverages the 'abritamr' package to analyze bacterial DNA sequences for antibiotic resistance markers. This tool should allow users to upload FASTA files containing genomic sequences and run AMRFinderPlus on these sequences to identify potential antibiotic resistance genes. The application should output a report detailing the presence of any identified AMR genes, along with their locations within the genome and relevant metadata such as gene names and associated antibiotics. Key Features: 1. User-friendly command-line interface allowing users to specify input FASTA files and output directories. 2. Integration with 'abritamr' to run AMRFinderPlus and parse its output. 3. Output generation in both human-readable text format and machine-readable CSV format. 4. Optional feature to visualize the distribution of AMR genes across the genome using a simple graphical representation. 5. Error handling to manage common issues like missing input files or unsupported file formats. 6. Documentation on how to install and use the tool, including examples and best practices. Utilization of 'abritamr': - Use 'abritamr.run_amrfinderplus()' method to execute AMRFinderPlus on user-provided genomic sequences. - Parse the results returned by 'abritamr' to extract information about identified AMR genes. - Utilize 'abritamr.parse_output()' function to process AMRFinderPlus output and generate structured data suitable for reporting. - Implement 'abritamr.visualize_genes()' for optional visualization of AMR gene distribution, if available.