AI Analysis
Final verdict: SUSPICIOUS
The package exhibits significant obfuscation and疑似被墙了，不过看起来你是想让我给出一个关于名为NumOpt的Python包的安全评估报告。根据提供的信息，这个包存在一些可疑的行为和风险信号，尤其是代码混淆程度高，并且疑似为著名库numpy的商标抢注（typosquatting）。综合考虑，我认为这个包的风险较高，建议谨慎处理。
- High obfuscation risk
- Potential typosquatting targeting numpy
Per-check LLM notes
- Network: No network calls detected, which is normal unless the package requires network interactions for its functionality.
- Shell: No shell executions detected, which is expected and safe.
- Obfuscation: The code shows signs of obfuscation with unusual naming patterns and structures which could indicate an attempt to hide functionality.
- Credentials: No clear patterns indicative of credential harvesting were found in the provided code snippets.
- Metadata: Suspicious maintainer history and git repository metrics suggest potential risk.
- ⚠ Typosquatting target: numpy
Heuristic Checks
Outbound Network Calls
No suspicious network call patterns found
Code Obfuscation
score 10.0
Found 5 obfuscation pattern(s)
se(self.nsamples, 1) def eval(self, args): x = args[0] x = x.toarray()urrogate.nx) def eval(self_jac, args): x = args[0]rogate.nx) # def eval(self_jac, args): # x = args[0] #Sparsity.dense(1, 1) def eval(self, args): x = args[0] x = x.toarray(), 1) def eval(self_hess, args): x = args[0]
Shell / Subprocess Execution
No shell execution patterns detected
Credential Harvesting
No credential harvesting patterns detected
Typosquatting
score 3.0
Possible typosquat of: numpy
"NumOpt" is 2 edit(s) from "numpy"
Registered Email Domain
No author email provided
Suspicious Page Links
All external links appear legitimate
Git Repository History
score 2.5
Git history flags: Repository has zero stars and zero forks
Repository has zero stars and zero forks
Maintainer History
score 2.0
1 maintainer concern(s) found
Author "Zcaic" 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 NumOpt
Design a mini-application called 'SystemOptimizer' that leverages the 'NumOpt' package to assist engineers in optimizing various parameters of an engineering system. The application should be able to take input from users about the system they wish to optimize, including initial parameters and constraints, and then output an optimized set of parameters based on the user's specifications. Step 1: Define the Problem - Users will input the type of system they want to optimize (e.g., mechanical, electrical). - They will specify the variables that need optimization and any constraints that must be adhered to. Step 2: Data Input - Provide a user-friendly interface where engineers can input numerical data related to their system, such as material properties, dimensions, etc. - Allow users to upload files containing necessary data if needed. Step 3: Optimization Process - Use the 'NumOpt' package to perform the optimization process based on the inputs provided. - Ensure that the optimization respects all specified constraints. Step 4: Results Presentation - Display the optimized parameters clearly and concisely. - Include visualizations like graphs or charts to help interpret the results. - Provide a summary report of the optimization process and outcomes. Suggested Features: - Support multiple types of optimization algorithms available in 'NumOpt'. - Allow users to save their optimization projects and results for future reference. - Implement a feature for sensitivity analysis to show how changes in certain parameters affect the outcome. - Offer the ability to compare different optimization scenarios side-by-side. How 'NumOpt' is Utilized: - Utilize 'NumOpt' for defining the problem space and constraints. - Apply its optimization algorithms to find the best solution given the input parameters. - Use its capabilities for post-processing and analysis of optimization results.