discover-ai

name	discover-ai
description	Scan cloud accounts and GitHub repos to discover AI/ML services and build an AI system inventory.
user-invocable	true

Discover AI

You are helping a founder discover what AI/ML services are running in their cloud accounts and code repositories.

What to do

Read shasta.config.json for python_cmd, aws_profile, azure_subscription_id, and github_repos. Use that for all commands (shown as <PYTHON_CMD>).

1. Discover cloud AI services

For AWS (if aws_profile is set):

<PYTHON_CMD> -c "
import json
from shasta.config import get_aws_client
from shasta.aws.ai_discovery import discover_aws_ai_services

client = get_aws_client()
client.validate_credentials()
result = discover_aws_ai_services(client)
print(json.dumps(result, indent=2, default=str))
"

For Azure (if azure_subscription_id is set):

<PYTHON_CMD> -c "
import json
from shasta.config import get_azure_client
from shasta.azure.ai_discovery import discover_azure_ai_services

client = get_azure_client()
client.validate_credentials()
result = discover_azure_ai_services(client)
print(json.dumps(result, indent=2, default=str))
"

2. Scan GitHub repos for AI usage

Whitney is the standalone source-code scanner, shipped at github.com/transilienceai/whitney. Install with pip install whitney if it is not already present.

whitney scan . --json > /tmp/whitney-findings.json 2>/dev/null || echo '[]' > /tmp/whitney-findings.json
<PYTHON_CMD> -c "
import json
data = json.load(open('/tmp/whitney-findings.json'))
for f in data:
    sev = (f.get('severity') or 'info').upper()
    print(f'[{sev}] {f.get(\"check_id\")}: {f.get(\"title\")}')
print(f'\nTotal: {len(data)} finding(s)')
"

3. Present results

Show a clear AI system inventory:

• Cloud AI services discovered (by service type and count)
• AI SDKs found in code (with versions)
• Any security issues found (hardcoded keys, prompt injection risks, etc.)
• Suggest running /ai-scan for full compliance assessment