AI Analysis
Final verdict: SUSPICIOUS
The package has low risks in terms of network, shell, obfuscation, and credential harvesting activities. However, the metadata risk is moderately high due to insecure links and low community engagement.
- Insecure external link
- Lack of community engagement
- Single release
- Minimal author information
Per-check LLM notes
- Network: The network calls appear to be related to health checks, authentication, and status checks, which are typical for many legitimate services.
- Shell: No shell execution patterns were detected.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: The package shows several red flags including an insecure external link, lack of community engagement, a single release, and an author with minimal information.
Heuristic Checks
Outbound Network Calls
score 7.5
Found 5 network call pattern(s)
urllib.request req = urllib.request.urlopen(f"{API_BASE}/health", timeout=8) data = jso).encode() req = urllib.request.Request( f"{API_BASE}/auth/revoke"," ) urllib.request.urlopen(req, timeout=10) except Exception:mpt}).encode() req = urllib.request.Request( f"{API_BASE}/v1/check", dOST" ) with urllib.request.urlopen(req, timeout=15) as resp: data = json.l
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
Email domain looks legitimate: gmail.com>
Suspicious Page Links
score 2.0
Found 1 suspicious link(s) on the package page
Non-HTTPS external link: http://127.0.0.1:8000/v1/check
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 6.0
3 maintainer concern(s) found
Only one version has ever been released — brand new packageAuthor name is missing or very shortAuthor "" 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 agent-shield-int
Create a Python-based command-line utility named 'PromptGuard' that leverages the 'agent-shield-int' package to detect potential prompt injection attacks against large language models (LLMs). This tool should allow users to input various prompts and receive real-time feedback on their safety level based on three distinct layers of detection provided by 'agent-shield-int': Vigil, DistilBERT ONNX, and Rules. The application should be user-friendly, offering options to test individual prompts as well as batch files containing multiple prompts. Additionally, integrate a feature that allows users to save and review past analyses. Ensure the application includes clear documentation and examples to help other developers understand how to use 'agent-shield-int' effectively.