performing-api-inventory-and-discovery▌
mukul975/Anthropic-Cybersecurity-Skills · updated May 25, 2026
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Performs API inventory and discovery to identify all API endpoints in an organization's environment including documented, undocumented, shadow, zombie, and deprecated APIs. The tester uses passive traffic analysis, active scanning, DNS enumeration, JavaScript analysis, and cloud resource inventory to build a comprehensive API catalog. Maps to OWASP API9:2023 Improper Inventory Management. Activates for requests involving API discovery, shadow API detection, API inventory audit, or attack surface mapping.
| name | performing-api-inventory-and-discovery |
| description | 'Performs API inventory and discovery to identify all API endpoints in an organization''s environment including documented, undocumented, shadow, zombie, and deprecated APIs. The tester uses passive traffic analysis, active scanning, DNS enumeration, JavaScript analysis, and cloud resource inventory to build a comprehensive API catalog. Maps to OWASP API9:2023 Improper Inventory Management. Activates for requests involving API discovery, shadow API detection, API inventory audit, or attack surface mapping. ' |
| domain | cybersecurity |
| subdomain | api-security |
| tags | - api-security - owasp - api-discovery - shadow-api - inventory - attack-surface |
| version | 1.0.0 |
| author | mahipal |
| license | Apache-2.0 |
| nist_csf | - PR.PS-01 - ID.RA-01 - PR.DS-10 - DE.CM-01 |
Performing API Inventory and Discovery
When to Use
- Mapping the complete API attack surface of an organization before a security assessment
- Identifying shadow APIs deployed by development teams without security review
- Discovering deprecated or zombie API versions that remain accessible but unmaintained
- Finding undocumented API endpoints exposed through mobile applications, SPAs, or microservices
- Building an API inventory for compliance requirements (PCI-DSS, SOC2, GDPR)
Do not use without written authorization. API discovery involves scanning network infrastructure and analyzing traffic.
Prerequisites
- Written authorization specifying the target domains and network ranges
- Passive traffic capture capability (network tap, proxy, or cloud traffic mirroring)
- Active scanning tools: Amass, subfinder, httpx, and nuclei
- JavaScript analysis tools: LinkFinder, JS-Miner, or custom parsers
- Access to cloud console (AWS, Azure, GCP) for API gateway inventory
- Burp Suite Professional for passive API endpoint discovery
Workflow
Step 1: Passive API Discovery from Traffic Analysis
import re
import json
from collections import defaultdict
# Parse HAR file from browser developer tools or proxy
def analyze_har_for_apis(har_file_path):
"""Extract API endpoints from HTTP Archive (HAR) file."""
with open(har_file_path) as f:
har = json.load(f)
api_endpoints = defaultdict(lambda: {
"methods": set(), "content_types": set(),
"auth_types": set(), "count": 0
})
for entry in har["log"]["entries"]:
url = entry["request"]["url"]
method = entry["request"]["method"]
# Identify API patterns
api_patterns = [
r'/api/', r'/v\d+/', r'/graphql', r'/rest/',
r'/ws/', r'/rpc/', r'/grpc', r'/json',
]
if any(re.search(p, url) for p in api_patterns):
# Normalize the URL (remove query params and IDs)
normalized = re.sub(r'\?.*$', '', url)
normalized = re.sub(r'/\d+(/|$)', '/{id}\\1', normalized)
normalized = re.sub(
r'/[0-9a-f]{8}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{12}',
'/{uuid}', normalized)
ep = api_endpoints[normalized]
ep["methods"].add(method)
ep["count"] += 1
# Detect authentication type
for header in entry["request"]["headers"]:
name = header["name"].lower()
if name == "authorization":
if "bearer" in header["value"].lower():
ep["auth_types"].add("Bearer/JWT")
elif "basic" in header["value"].lower():
ep["auth_types"].add("Basic")
elif name == "x-api-key":
ep["auth_types"].add("API Key")
# Detect content type
content_type = next(
(h["value"] for h in entry["request"]["headers"]
if h["name"].lower() == "content-type"), None)
if content_type:
ep["content_types"].add(content_type.split(";")[0])
print(f"Discovered {len(api_endpoints)} unique API endpoints:\n")
for url, info in sorted(api_endpoints.items()):
methods = ", ".join(sorted(info["methods"]))
auth = ", ".join(info["auth_types"]) or "None"
print(f" [{methods}] {url}")
print(f" Auth: {auth} | Requests: {info['count']}")
return api_endpoints
Step 2: Active API Endpoint Discovery
# DNS enumeration for API subdomains
amass enum -d example.com -o amass_results.txt
subfinder -d example.com -o subfinder_results.txt
# Filter for API-related subdomains
grep -iE '(api|rest|graphql|ws|gateway|backend|internal|staging|dev|v1|v2)' \
amass_results.txt subfinder_results.txt | sort -u > api_subdomains.txt
# Check which subdomains are alive
cat api_subdomains.txt | httpx -status-code -content-length -title \
-tech-detect -o live_apis.txt
# Probe common API paths on each live subdomain
cat api_subdomains.txt | while read domain; do
for path in /api /api/v1 /api/v2 /graphql /swagger.json /openapi.json \
/api-docs /docs /health /status /metrics /actuator; do
curl -s -o /dev/null -w "%{http_code} %{url_effective}\n" \
"https://${domain}${path}" 2>/dev/null | grep -v "^404"
done
done
import requests
import concurrent.futures
def discover_api_endpoints(base_domains):
"""Actively probe for API endpoints across discovered domains."""
# Common API paths to test
API_PATHS = [
"/api", "/api/v1", "/api/v2", "/api/v3",
"/graphql", "/gql", "/query",
"/rest", "/json", "/rpc",
"/swagger.json", "/swagger/v1/swagger.json",
"/openapi.json", "/openapi.yaml", "/api-docs",
"/docs", "/redoc", "/explorer",
"/.well-known/openid-configuration",
"/health", "/healthz", "/ready",
"/status", "/info", "/version",
"/metrics", "/prometheus",
"/actuator", "/actuator/health", "/actuator/info",
"/admin", "/admin/api", "/internal",
"/debug", "/debug/vars", "/debug/pprof",
"/ws", "/websocket", "/socket.io",
"/grpc", "/twirp",
]
discovered = []
def check_endpoint(domain, path):
for scheme in ["https", "http"]:
url = f"{scheme}://{domain}{path}"
try:
resp = requests.get(url, timeout=5, allow_redirects=False,
verify=False) # TLS verification disabled for discovery; enable in production
if resp.status_code not in (404, 502, 503):
return {
"url": url,
"status": resp.status_code,
"content_type": resp.headers.get("Content-Type", ""),
"server": resp.headers.get("Server", ""),
"size": len(resp.content),
}
except requests.exceptions.RequestException:
pass
return None
with concurrent.futures.ThreadPoolExecutor(max_workers=20) as executor:
futures = {}
for domain in base_domains:
for path in API_PATHS:
future = executor.submit(check_endpoint, domain, path)
futures[future] = (domain, path)
for future in concurrent.futures.as_completed(futures):
result = future.result()
if result:
discovered.append(result)
print(f" [FOUND] {result['url']} -> {result['status']} ({result['content_type']})")
return discovered
Step 3: JavaScript Source Analysis for API Endpoints
import re
import requests
def extract_apis_from_javascript(js_urls):
"""Extract API endpoints from JavaScript source files."""
api_pattern = re.compile(
r'''(?:['"`])((?:/api/|/v[0-9]+/|/graphql|/rest/)[^'"`\s<>{}]+)(?:['"`])''',
re.IGNORECASE
)
url_pattern = re.compile(
r'''(?:['"`])(https?://[a-zA-Z0-9._-]+(?:\.[a-zA-Z]{2,})+(?:/[^'"`\s<>{}]*)?)(?:['"`])'''
)
fetch_pattern = re.compile(
r'''(?:fetch|axios|ajax|XMLHttpRequest|\.get|\.post|\.put|\.delete|\.patch)\s*\(\s*(?:['"`])([^'"`]+)'''
)
all_endpoints = set()
for js_url in js_urls:
try:
resp = requests.get(js_url, timeout=10)
content = resp.text
# Extract relative API paths
for match in api_pattern.findall(content):
all_endpoints.add(("relative", match))
# Extract absolute URLs
for match in url_pattern.findall(content):
if any(kw in match.lower() for kw in ["/api", "/v1", "/v2", "graphql"]):
all_endpoints.add(("absolute", match))
# Extract from fetch/axios calls
for match in fetch_pattern.findall(content):
all_endpoints.add(("fetch", match))
except requests.exceptions.RequestException:
pass
print(f"\nAPI endpoints discovered from JavaScript ({len(all_endpoints)}):")
for source, endpoint in sorted(all_endpoints):
print(f" [{source}] {endpoint}")
return all_endpoints
# Find JavaScript files from the target domain
def find_js_files(domain):
"""Discover JavaScript files from a web application."""
resp = requests.get(f"https://{domain}", timeout=10)
js_files = re.findall(r'src=["\']([^"\']+\.js[^"\']*)', resp.text)
full_urls = []
for js in js_files:
if js.startswith("http"):
full_urls.append(js)
elif js.startswith("//"):
full_urls.append(f"https:{js}")
elif js.startswith("/"):
full_urls.append(f"https://{domain}{js}")
return full_urls
Step 4: Cloud API Gateway Inventory
import boto3
def inventory_aws_apis():
"""Inventory all APIs in AWS API Gateway."""
apigw = boto3.client('apigateway')
apigwv2 = boto3.client('apigatewayv2')
apis = []
# REST APIs (API Gateway v1)
rest_apis = apigw.get_rest_apis()
for api in rest_apis['items']:
resources = apigw.get_resources(restApiId=api['id'])
stages = apigw.get_stages(restApiId=api['id'])
for stage in stages['item']:
for resource in resources['items']:
for method in resource.get('resourceMethods', {}).keys():
apis.append({
"type": "REST",
"name": api['name'],
"stage": stage['stageName'],
"path": resource['path'],
"method": method,
"url": f"https://{api['id']}.execute-api.{boto3.session.Session().region_name}.amazonaws.com/{stage['stageName']}{resource['path']}",
"created": str(api.get('createdDate', '')),
})
# HTTP APIs (API Gateway v2)
http_apis = apigwv2.get_apis()
for api in http_apis['Items']:
routes = apigwv2.get_routes(ApiId=api['ApiId'])
stages = apigwv2.get_stages(ApiId=api['ApiId'])
for route in routes['Items']:
apis.append({
"type": "HTTP",
"name": api['Name'],
"route": route['RouteKey'],
"api_id": api['ApiId'],
"protocol": api['ProtocolType'],
})
print(f"\nAWS API Inventory ({len(apis)} endpoints):")
for api in apis:
print(f" [{api['type']}] {api.get('name')} - {api.get('method', '')} {api.get('path', api.get('route', ''))}")
return apis
Step 5: API Version and Shadow API Detection
def detect_shadow_and_zombie_apis(discovered_endpoints, documented_endpoints):
"""Compare discovered APIs against documented inventory."""
# Normalize endpoints for comparison
def normalize(ep):
ep = re.sub(r'/v\d+/', '/vX/', ep)
ep = re.sub(r'/\d+', '/{id}', ep)
return ep.lower().rstrip('/')
documented_normalized = {normalize(ep) for ep in documented_endpoints}
shadow_apis = [] # Discovered but not documented
zombie_apis = [] # Old versions still accessible
for ep in discovered_endpoints:
normalized = normalize(ep["url"])
if normalized not in documented_normalized:
# Check if it is an old version of a documented API
if re.search(r'/v[0-9]+/', ep["url"]):
zombie_apis.append(ep)
else:
shadow_apis.append(ep)
print(f"\nShadow APIs (undocumented): {len(shadow_apis)}")
for api in shadow_apis:
print(f" [SHADOW] {api['url']} -> {api['status']}")
print(f"\nZombie APIs (deprecated versions): {len(zombie_apis)}")
for api in zombie_apis:
print(f" [ZOMBIE] {api['url']} -> {api['status']}")
# Check if zombie APIs lack security controls
for api in zombie_apis:
resp = requests.get(api["url"], timeout=5)
if resp.status_code not in (401, 403):
print(f" [CRITICAL] Zombie API accessible without auth: {api['url']}")
return shadow_apis, zombie_apis
Key Concepts
| Term | Definition |
|---|---|
| Shadow API | An API deployed by a development team without going through the official API management or security review process |
| Zombie API | A deprecated or old API version that remains accessible and running but is no longer maintained or monitored |
| API Inventory | A comprehensive catalog of all APIs in an organization including endpoint URLs, owners, versions, authentication methods, and data classifications |
| Improper Inventory Management | OWASP API9:2023 - failure to maintain an accurate API inventory, leading to unmonitored and unprotected API endpoints |
| Attack Surface | The total set of API endpoints, methods, and parameters that an attacker can potentially interact with |
| API Sprawl | The uncontrolled proliferation of APIs in an organization, often resulting from microservice adoption without centralized governance |
Tools & Systems
- Amass: OWASP tool for attack surface mapping through DNS enumeration, web scraping, and API discovery
- httpx: Fast HTTP probing tool for validating discovered domains and identifying live API endpoints
- nuclei: Template-based scanner for detecting exposed API documentation, debug endpoints, and misconfigured services
- Swagger UI Detector: Tool for finding exposed Swagger/OpenAPI documentation endpoints across the organization
- Akto: API security platform that discovers APIs through traffic analysis and maintains an automated inventory
Common Scenarios
Scenario: Enterprise API Attack Surface Assessment
Context: A large enterprise has 200+ development teams using microservices. The security team suspects many undocumented APIs are exposed to the internet. A comprehensive API inventory is needed for a security audit.
Approach:
- DNS enumeration discovers 340 subdomains, 45 contain API-related keywords (api, rest, gateway, backend)
- Active probing of all subdomains with API path wordlist discovers 127 live API endpoints
- JavaScript analysis of the main web application reveals 34 API endpoints, 8 of which point to undocumented internal services
- AWS API Gateway inventory shows 67 REST APIs and 23 HTTP APIs across 12 accounts
- Cross-referencing against the official API catalog: 31 shadow APIs (undocumented), 14 zombie APIs (deprecated versions)
- 3 zombie APIs have no authentication, exposing customer data through endpoints that were supposed to be decommissioned
- 2 shadow APIs expose internal admin functions to the internet without authorization
Pitfalls:
- Only checking documented API endpoints and missing shadow APIs deployed outside the API gateway
- Not scanning JavaScript bundles where frontend applications hardcode API endpoint URLs
- Missing APIs behind non-standard ports or subpaths
- Not checking for multiple API versions where older versions may lack security controls
- Assuming all APIs go through the API gateway when some may be directly exposed
Output Format
## API Inventory and Discovery Report
**Organization**: Example Corp
**Assessment Date**: 2024-12-15
**Domains Scanned**: 340
### Summary
| Category | Count |
|----------|-------|
| Total APIs Discovered | 127 |
| Documented APIs | 82 |
| Shadow APIs (undocumented) | 31 |
| Zombie APIs (deprecated) | 14 |
| APIs Without Authentication | 8 |
| APIs Exposing Sensitive Data | 5 |
### Critical Findings
1. **Zombie API**: api-v1.example.com/api/v1/users - Deprecated in 2022,
still accessible, no authentication required, returns full user data
2. **Shadow API**: internal-tools.example.com/api/admin - Admin functions
exposed to internet without authorization
3. **Exposed Documentation**: 12 Swagger UI instances accessible publicly,
revealing full API schema and endpoint details
How to use performing-api-inventory-and-discovery on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add performing-api-inventory-and-discovery
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches performing-api-inventory-and-discovery from GitHub repository mukul975/Anthropic-Cybersecurity-Skills and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate performing-api-inventory-and-discovery. Access the skill through slash commands (e.g., /performing-api-inventory-and-discovery) or your agent's skill management interface.
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
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Use Cases▌
Task Automation & Efficiency
Automate repetitive workflows and reduce manual effort
Example
Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Knowledge Enhancement
Learn new skills, understand complex topics, get expert guidance
Example
Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Quality Improvement
Enhance output quality through reviews, suggestions, and refinements
Example
Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client with skill support
- ›Clear understanding of task or problem to solve
- ›Willingness to iterate and refine outputs
Time Estimate
15-45 minutes depending on use case complexity
Installation Steps
- 1.Install skill using provided installation command
- 2.Test with simple use case relevant to your work
- 3.Evaluate output quality and relevance
- 4.Iterate on prompts to improve results
- 5.Integrate into regular workflow if valuable
Common Pitfalls
- ⚠Expecting perfect results without iteration
- ⚠Not providing enough context in prompts
- ⚠Using skill for tasks outside its intended scope
- ⚠Accepting outputs without review and validation
Best Practices▌
✓ Do
- +Start with clear, specific prompts
- +Provide relevant context and constraints
- +Review and refine all outputs before using
- +Iterate to improve output quality
- +Document successful prompt patterns
✗ Don't
- −Don't use without understanding skill limitations
- −Don't skip validation of outputs
- −Don't share sensitive information in prompts
- −Don't expect skill to replace human judgment
💡 Pro Tips
- ★Be specific about desired format and style
- ★Ask for multiple options to choose from
- ★Request explanations to understand reasoning
- ★Combine AI efficiency with human expertise
When to Use This▌
✓ Use When
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid When
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
Learning Path▌
- 1Familiarize yourself with skill capabilities and limitations
- 2Start with low-risk, non-critical tasks
- 3Progress to more complex and valuable use cases
- 4Build expertise through regular use and experimentation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.6★★★★★40 reviews- ★★★★★Charlotte Singh· Dec 20, 2024
Registry listing for performing-api-inventory-and-discovery matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Aarav Mensah· Dec 16, 2024
performing-api-inventory-and-discovery has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Aditi Jackson· Dec 12, 2024
Keeps context tight: performing-api-inventory-and-discovery is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Shikha Mishra· Dec 4, 2024
Useful defaults in performing-api-inventory-and-discovery — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Yash Thakker· Nov 23, 2024
performing-api-inventory-and-discovery has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Ira Smith· Nov 7, 2024
Useful defaults in performing-api-inventory-and-discovery — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Hiroshi Shah· Nov 3, 2024
We added performing-api-inventory-and-discovery from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Soo Patel· Nov 3, 2024
performing-api-inventory-and-discovery reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Charlotte Ghosh· Oct 26, 2024
I recommend performing-api-inventory-and-discovery for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Aditi Shah· Oct 22, 2024
performing-api-inventory-and-discovery fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
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