angr

v9.2.221 safe
4.0
Medium Risk

A multi-architecture binary analysis toolkit, with the ability to perform dynamic symbolic execution and various static analyses on binaries

🤖 AI Analysis

Final verdict: SAFE

The package angr v9.2.221 has been assessed with low risks across network, shell, obfuscation, and credential aspects. However, the incomplete maintainer's author information slightly increases the metadata risk, leading to a moderate overall risk score.

  • Low network and shell execution risks
  • No signs of obfuscation or credential harvesting
  • Incomplete maintainer's author information
Per-check LLM notes
  • Network: No network calls detected, which is normal for angr as it primarily focuses on binary analysis and does not inherently require internet access.
  • Shell: No shell execution patterns detected, consistent with angr's intended use for static and dynamic binary analysis without executing external commands.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The maintainer's author information is incomplete, suggesting a potential lack of transparency or a new/unverified account.

📦 Package Quality Overall: Low (3.8/10)

○ Low Test Suite 1.0

No test suite detected

  • No test files or test-runner configuration detected
◈ Medium Documentation 5.0

Some documentation present

  • Detailed PyPI description (2635 chars)
○ Low Contributing Guide 2.0

No contributing guide or governance files found

  • No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
○ Low Type Annotations 1.0

No type annotations detected

  • No type annotations, py.typed marker, or stub files detected
✦ High Multiple Contributors 10.0

Active multi-contributor project

  • 14 unique contributor(s) across 100 commits in angr/angr
  • Active community — 5 or more distinct contributors

🔬 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

No author email provided

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository angr/angr 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 angr 
Create a mini-application named 'BinaryInsight' using the Python package 'angr'. This tool aims to provide a user-friendly interface for performing basic static and dynamic analysis on executable files. It will enable users to explore the inner workings of binaries without needing deep expertise in reverse engineering or assembly language.

### Features:
1. **Static Analysis**:
   - Disassemble the binary and display the entry point.
   - Identify and display the imported functions.
   - List all strings found within the binary.
2. **Dynamic Analysis**:
   - Perform a basic dynamic symbolic execution to trace the control flow of the binary.
   - Highlight potential vulnerabilities such as buffer overflows or format string bugs.
3. **User Interface**:
   - Develop a simple command-line interface for ease of use.
   - Provide options to select the target binary file and specify analysis types.
4. **Report Generation**:
   - Automatically generate a report summarizing the findings from both static and dynamic analyses.

### Utilization of 'angr':
- Use 'angr' to load the binary and extract necessary information for static analysis.
- Leverage 'angr's symbolic execution capabilities to dynamically analyze the binary and detect potential security issues.
- Integrate 'angr's disassembly and string extraction functionalities into your application to enhance its analytical capabilities.

### Steps to Build 'BinaryInsight':
1. Install the required packages (`angr`, `cle`, `pyvex`), ensuring you have a suitable Python environment set up.
2. Design the command-line interface, allowing users to input the path to their binary and choose between static or dynamic analysis.
3. Implement static analysis features by utilizing 'angr's API to load the binary, disassemble it, and extract relevant data.
4. For dynamic analysis, use 'angr's symbolic execution engine to simulate the execution of the binary under different conditions.
5. Develop a reporting system that compiles the results of the analyses into a readable format.
6. Test 'BinaryInsight' on various binaries to ensure accuracy and reliability.
7. Document the code and provide usage instructions for other developers interested in contributing or using the tool.

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