b2bTools

v3.0.8 suspicious
6.0
Medium Risk

bio2Byte software suite to predict protein biophysical properties from their amino-acid sequences

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits significant risks related to shell and obfuscation usage, which could potentially enable unauthorized command execution and code injection. While there's no clear evidence of malicious intent, these features warrant further investigation.

  • High shell risk due to os.system usage
  • High obfuscation risk due to eval() and __import__
Per-check LLM notes
  • Network: The network calls may be legitimate if the package is designed to fetch or post data, but without context, it could indicate potential data exfiltration.
  • Shell: Direct use of os.system suggests potential execution of external commands which can be risky and might be used for unintended purposes like executing arbitrary code.
  • Obfuscation: The use of eval() and __import__ suggests potential for code injection or dynamic execution, which could be used for malicious purposes.
  • Credentials: No direct evidence of credential harvesting was found.
  • Metadata: The package shows some minor concerns but no strong indicators of malicious activity.

📦 Package Quality Overall: Low (3.4/10)

○ Low Test Suite 1.0

No test suite detected

  • No test files or test-runner configuration detected
◈ Medium Documentation 7.0

Some documentation present

  • Documentation URL: "Documentation" -> https://bio2byte.be/b2btools/package-documentation
  • Detailed PyPI description (40733 chars)
◈ Medium Contributing Guide 7.0

Some contribution signals present

  • Separate author ("Wim Vranken") and maintainer ("Adrián Díaz, Sophie-Luise Heidig, Wim Vranken") listed
  • Development Status classifier >= Beta
○ Low Type Annotations 1.0

No type annotations detected

  • No type annotations, py.typed marker, or stub files detected
○ Low Multiple Contributors 1.0

Unable to verify contributor count: no GitHub repository found

  • No GitHub repository linked — contributor count unavailable

🔬 Heuristic Checks

⚠ Outbound Network Calls score 4.5

Found 3 network call pattern(s)

  • utf-8') req = urllib.request.Request(url, data) with urllib.request.urlop
  • l, data) with urllib.request.urlopen(req) as f: response = str(f.read
  • ID + ".fasta") response = requests.post(currentUrl) cData = ''.join(response.text) Seq = St
⚠ Code Obfuscation score 6.0

Found 3 obfuscation pattern(s)

  • ): original_numbering = eval(original_numbering) nmrStarFile = self.readNmrStarProje
  • tar) == type(""): is_star = eval(is_star) if is_star: allSeqInfo = b2bIo.readNmrStarSeque
  • __import__ does) """ m = __import__(name) comps = name.split('.') for comp in comps[1:]: m =
⚠ Shell / Subprocess Execution score 10.0

Found 6 shell execution pattern(s)

  • int('starting ', pdb) os.system(ring_bin+' -i '+pdb_folder+pdb+' -t 3 --all -E tmp_ringfiles
  • in os.listdir(folder): # os.system(rsabin+' '+folder+i+' '+outdir+i) ## parse ## diz =
  • int("starting ", pdb) os.system( ring_bin + " -i " + pdb
  • self.filename) pipe = os.popen( cmd ) output = pipe.read() ## The program
  • t(filename.split('.')[0]) subprocess.run( ["t_coffee", filename, "-output=fasta_aln", "-outfile
  • leName.split('.')[0]) subprocess.run( ["t_coffee", fileName, "-output=fasta_aln", "-o
✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

Email domain looks legitimate: vub.be

⚠ Suspicious Page Links score 2.0

Found 1 suspicious link(s) on the package page

  • Non-HTTPS external link: http://hmmer.org
✓ Git Repository History

No GitHub repository linked

  • No GitHub repository link found
⚠ Maintainer History score 2.0

1 maintainer concern(s) found

  • Author "Wim Vranken" 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 b2bTools 
Create a mini-application called 'ProteinAnalyzer' that leverages the 'b2bTools' Python package to analyze and predict the biophysical properties of proteins based on their amino acid sequences. This tool will be useful for researchers and students who need quick insights into protein behavior without deep computational resources.

**Step 1: User Interface Design**
Design a simple and intuitive command-line interface (CLI) where users can input the amino acid sequence of a protein. The CLI should also allow users to select which biophysical properties they want to predict (e.g., hydrophobicity, flexibility, etc.).

**Step 2: Input Validation**
Implement robust validation checks to ensure that the input amino acid sequence is valid and formatted correctly. Provide informative error messages if the input is incorrect.

**Step 3: Integration with b2bTools**
Use the 'b2bTools' package to process the validated amino acid sequence and generate predictions for the selected biophysical properties. Ensure that the integration is efficient and leverages the full capabilities of 'b2bTools'.

**Step 4: Result Presentation**
Display the results in a clear and organized manner. Include visual aids like graphs or charts to make the data more understandable. Allow users to save the results to a file in formats such as CSV or JSON.

**Suggested Features**:
- Support for multiple prediction types (hydrophobicity, flexibility, etc.)
- Option to compare multiple protein sequences side-by-side
- Interactive help menu for new users
- Detailed documentation explaining how to use the application and interpret the results

💬 Discussion Feed

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