🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits high credential risk due to its monitoring of sensitive files and obfuscation techniques, raising concerns about hidden functionality or malicious intent. However, no direct evidence of malicious behavior is present.

High credential risk due to monitoring of sensitive files
Significant obfuscation suggesting attempts to hide functionality

Per-check LLM notes

Network: No network calls detected, which is normal unless the package's functionality requires external API interactions.
Shell: No shell execution patterns detected, indicating the package does not execute system commands without user intervention.
Obfuscation: The code uses complex import patterns and skips tests based on environment variables, suggesting an attempt to hide functionality or logic.
Credentials: The package monitors for access to sensitive files like /etc/shadow and private keys such as id_rsa, indicating potential monitoring or logging of actions that could involve sensitive information.
Metadata: The package shows signs of low maintainer activity and poor metadata quality, which may indicate potential risk.

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

⚠ Code Obfuscation score 4.0

Found 2 obfuscation pattern(s)

test.mark.skipif( not __import__("os").getenv("AGENT_MOSS_LLM_API_KEY"), reason="需要设置 AGEN
file): self.checker = __import__("agent_moss.engine.logic_rules", fromlist=["LogicRulesChecker"]).LogicRulesChecker(linux_profile) def test_sensitive_pa

✓ Shell / Subprocess Execution

No shell execution patterns detected

⚠ Credential Harvesting score 10.0

Found 6 credential access pattern(s)

的 file_access 模式 # （如 /etc/shadow）不立即 Deny。因为敏感路径可能出现在字符串字面量中， # 而纯正则无法可靠区分字符串和执行路径。交
（正常脚本不会读 shadow/ssh 密钥） ("/etc/shadow", re.compile(r"/etc/shadow")), ("id_rsa", re.compile(r"
("/etc/shadow", re.compile(r"/etc/shadow")), ("id_rsa", re.compile(r"\bid_rsa\b")), ("id_ed2
wget --post-file"}, {"/etc/shadow", "id_rsa", "id_ed25519"}, "critical", "检测到
解码后管道执行，可能是混淆逃逸。"), "/etc/shadow": ("critical", "检测到访问系统密码文件。"), "id_rsa": ("critica
rn( pattern=r"/etc/shadow", risk_level="critical", ri

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

No author email provided

⚠ Suspicious Page Links score 4.0

Found 2 suspicious link(s) on the package page

Non-HTTPS external link: http://127.0.0.1:9090/api/v1/analyze
Non-HTTPS external link: http://127.0.0.1:9090/api/v1/health

✓ Git Repository History

No GitHub repository linked

No GitHub repository link found

⚠ Maintainer History score 6.0

3 maintainer concern(s) found

Author name is missing or very short
Author "" appears to have only 1 package on PyPI (new or inactive account)
Package has no PyPI classifiers (low effort / metadata quality)

✓ Known CVE Vulnerabilities

No known vulnerabilities found in OSV database.

💡 AI App Starter Prompt

Use this prompt to build a project with agent-moss

Create a Python-based mini-application called 'SecurityGuard' that leverages the 'agent-moss' package to analyze and secure AI agents. SecurityGuard should serve as a comprehensive tool for evaluating the security posture of various AI systems, providing insights into potential vulnerabilities and suggesting remediation strategies.

The application should include the following key features:
1. **Agent Profiling**: Allow users to input details about their AI agents, such as the type of AI model, the environment it operates in, and any known configurations or plugins.
2. **Risk Assessment**: Use 'agent-moss' to perform a multi-layered security analysis on the AI agent, identifying risks related to data privacy, model integrity, and operational safety.
3. **Vulnerability Scanning**: Implement a feature that scans the AI agent for known vulnerabilities and provides a detailed report on findings, including severity ratings and recommended actions.
4. **Remediation Guidance**: Offer suggestions for mitigating identified risks and improving overall security, based on best practices and expert recommendations.
5. **User Interface**: Develop a simple and intuitive command-line interface (CLI) for interacting with SecurityGuard, making it easy for users to run analyses and review results.
6. **Reporting**: Generate comprehensive reports summarizing the security assessment, including visual representations of risk levels and detailed explanations of findings.

In utilizing the 'agent-moss' package, focus on integrating its core functionalities for security analysis and leveraging its multi-layer approach to provide a thorough evaluation of AI agent security. Ensure that the application not only identifies issues but also educates users on how to address them effectively.