🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits moderate risk due to potential obfuscation and improper handling of shell commands, which could lead to vulnerabilities. However, there is no evidence of credential harvesting or severe issues.

Potential obfuscation to hide logic or evade analysis
Improper handling of shell commands leading to possible code injection

Per-check LLM notes

Network: The package makes network calls that appear to be checking for updates or news, which could be legitimate, but the lack of proper error handling and context suggests potential risks.
Shell: The use of subprocess and os.system indicates that the package executes shell commands, which can be risky if not properly sanitized or validated, potentially leading to code injection or other vulnerabilities.
Obfuscation: The code pattern suggests potential obfuscation which could be used to hide logic or evade analysis.
Credentials: No clear patterns indicative of credential harvesting were detected.
Metadata: The author's name is missing and the account seems new or inactive, raising some concerns but not enough to suggest high risk.

🔬 Heuristic Checks

⚠ Outbound Network Calls score 6.0

Found 4 network call pattern(s)

e/acellera/htmd" with urllib.request.urlopen(url) as r: version = json.loads(r.read()
ews(): try: res = requests.get("https://www.htmd.org/news/content", timeout=3) prin
lera.com/check" res = requests.post(url, data, timeout=10) except Exception as e: pr
llera.com/register" res = requests.post(url, data=data, timeout=10) # Check the response if

⚠ Code Obfuscation score 2.0

Found 1 obfuscation pattern(s)

file"]) as f: exec(compile(f.read(), _config["configfile"], "exec")) except Ex

⚠ Shell / Subprocess Execution score 10.0

Found 5 shell execution pattern(s)

# doctest: +SKIP """ os.system( 'find {} -type f -exec grep -n "{} {}" {{}} +'.form
port subprocess result = subprocess.run(cmd, capture_output=True, text=True, cwd=cwd) if result.
r.debug(cmd) result = subprocess.run(cmd, stdout=f, stderr=f, cwd=outdir) if result.returnco
try: ret = subprocess.Popen( os.path.join(home(shareDir=True), "license-
.format(modellerexe, pyfile), shell=True) newmol = Molecule("./prot_fill.B99990001.pdb") pri

✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

Email domain looks legitimate: acellera.com>

⚠ Suspicious Page Links score 2.0

Found 1 suspicious link(s) on the package page

Non-HTTPS external link: http://pubs.acs.org/doi/abs/10.1021/acs.jctc.6b00049

✓ Git Repository History

Repository Acellera/htmd 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 acellera-htmd

Develop a fully functional mini-application that leverages the 'acellera-htmd' Python package to simulate and analyze the behavior of molecules under various conditions. This application will be named 'MolSimAnalyzer'. Here are the key functionalities and steps to develop it:

1. **Project Setup**: Begin by setting up your development environment with Python and installing the 'acellera-htmd' package.
2. **User Interface**: Design a simple yet intuitive command-line interface (CLI) for users to interact with the application. The CLI should accept inputs such as the type of molecule, simulation parameters, and analysis criteria.
3. **Simulation Engine**: Utilize 'acellera-htmd' to create a high-throughput molecular dynamics (HTMD) simulation engine. This engine should be capable of running simulations on multiple molecules simultaneously, optimizing computational resources.
4. **Parameter Tuning**: Implement a feature that allows users to adjust simulation parameters such as temperature, pressure, and time steps. These adjustments should reflect real-world experimental conditions.
5. **Analysis Tools**: Develop tools within the application that use 'acellera-htmd' to analyze the simulation data. These tools should include but not be limited to calculating average energy levels, bond lengths, and molecular dynamics trajectories.
6. **Visualization**: Integrate visualization capabilities that allow users to visualize the molecular structures and their movements over time. This could involve generating static images or animations based on the simulation results.
7. **Report Generation**: Create a feature that generates comprehensive reports summarizing the simulation outcomes, including key metrics and visualizations.
8. **Documentation**: Ensure that the application comes with detailed documentation explaining how to install, configure, and use each feature effectively.

The goal is to create a versatile tool that researchers and students can use to explore molecular dynamics in a controlled and efficient manner. Focus on making the application user-friendly while ensuring it takes full advantage of 'acellera-htmd's capabilities.