API Designer
Jeffallan/claude-skills
Designs REST and GraphQL APIs from resource modeling to an OpenAPI 3.1 contract, with versioning, pagination and RFC 7807 error handling.
Discover and inventory shadow API endpoints that operate outside documented OpenAPI/Swagger specs, using traffic analysis against API gateways (Kong, AWS API Gateway, Envoy), cloud configuration…
$ npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill detecting-shadow-api-endpoints -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills detecting-shadow-api-endpoints --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/detecting-shadow-api-endpoints .claude/skills/detecting-shadow-api-endpoints && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "detecting-shadow-api-endpoints" agent skill from https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/detecting-shadow-api-endpoints into .claude/skills/detecting-shadow-api-endpoints/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "detecting-shadow-api-endpoints", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/detecting-shadow-api-endpointsType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill detecting-shadow-api-endpoints -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills detecting-shadow-api-endpoints --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/detecting-shadow-api-endpoints .agents/skills/detecting-shadow-api-endpoints && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "detecting-shadow-api-endpoints" agent skill from https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/detecting-shadow-api-endpoints into .agents/skills/detecting-shadow-api-endpoints/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "detecting-shadow-api-endpoints", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill detecting-shadow-api-endpoints -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills detecting-shadow-api-endpoints --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/detecting-shadow-api-endpoints .cursor/skills/detecting-shadow-api-endpoints && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "detecting-shadow-api-endpoints" agent skill from https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/detecting-shadow-api-endpoints into .cursor/skills/detecting-shadow-api-endpoints/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "detecting-shadow-api-endpoints", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git --path skills/detecting-shadow-api-endpoints--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill detecting-shadow-api-endpoints -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills detecting-shadow-api-endpoints --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/detecting-shadow-api-endpoints .gemini/skills/detecting-shadow-api-endpoints && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "detecting-shadow-api-endpoints" agent skill from https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/detecting-shadow-api-endpoints into .gemini/skills/detecting-shadow-api-endpoints/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "detecting-shadow-api-endpoints", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills detecting-shadow-api-endpointsInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill detecting-shadow-api-endpoints -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/detecting-shadow-api-endpoints .github/skills/detecting-shadow-api-endpoints && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "detecting-shadow-api-endpoints" agent skill from https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/detecting-shadow-api-endpoints into .github/skills/detecting-shadow-api-endpoints/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "detecting-shadow-api-endpoints", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill detecting-shadow-api-endpoints -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills detecting-shadow-api-endpoints --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/detecting-shadow-api-endpoints .opencode/skills/detecting-shadow-api-endpoints && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "detecting-shadow-api-endpoints" agent skill from https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/detecting-shadow-api-endpoints into .opencode/skills/detecting-shadow-api-endpoints/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "detecting-shadow-api-endpoints", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
detecting-shadow-api-endpointsDiscover and inventory shadow API endpoints that operate outside documented OpenAPI/Swagger specs, using traffic analysis against API gateways (Kong, AWS API Gateway, Envoy), cloud configuration…
Detecting Shadow API Endpoints is an agent skill from mukul975/Anthropic-Cybersecurity-Skills. Discover and inventory shadow API endpoints that operate outside documented OpenAPI/Swagger specs, using traffic analysis against API gateways (Kong, AWS API Gateway, Envoy), cloud configuration scanning, and source code repository mining for undocumented routes. Use when assessing API attack surface, auditing for forgotten test environments or deprecated API versions still running, or building an API registration governance policy.
Its SKILL.md is about 3.6k tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files, including scripts and reference files (for example `references/api-reference.md` and `scripts/agent.py`).
It sits in Backend & APIs, covering REST APIs, OpenAPI specifications and Microservices. It works with OpenAPI and Amazon Web Services. The repository describes itself as: 817 structured cybersecurity skills for AI agents · Mapped to 6 frameworks: MITRE ATT&CK, NIST CSF 2.0, MITRE ATLAS, D3FEND, NIST AI RMF & MITRE F3 (Fight Fraud) · agentskills.io…. The licence is Apache-2.0.
3 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit 54a7988. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Ships 1 file in scripts/ (Python), which the agent can run.
Shell commands in SKILL.md call:
awsFrom the folder's file list and the shell code blocks in SKILL.md.
Links to these hosts (documentation or services it may open):
apisec.aiwiz.iocheckmarx.comtreblle.comblog.securelayer7.netFrom URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Detecting Shadow API Endpoints loads about 3.6k tokens when it runs, and up to ~4.2k if it reads all its reference files. Until then it costs about 117 tokens; SKILL.md has 242 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.
The full file from mukul975/Anthropic-Cybersecurity-Skills at commit 54a7988, republished under its Apache-2.0 licence (© mukul975). 242 words, ~3,623 tokens.
.claude/skills/detecting-shadow-api-endpoints/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.Shadow APIs are API endpoints operating within an organization's environment that are not tracked, documented, or secured. They emerge from rapid development cycles, forgotten test environments, deprecated API versions left running, third-party integrations, or developer side projects deployed without governance. Shadow APIs bypass authentication and monitoring controls, creating hidden entry points for attackers. Studies show that up to 30% of API endpoints in large organizations are undocumented, making shadow API detection a critical component of API security posture management.
Compare live API traffic against documented OpenAPI specifications to identify undocumented endpoints:
#!/usr/bin/env python3
"""Shadow API Endpoint Detector
Compares observed API traffic patterns against documented
OpenAPI specifications to identify undocumented (shadow) endpoints.
"""
import json
import re
import yaml
import sys
from collections import defaultdict
from datetime import datetime
from typing import Dict, List, Set, Tuple, Optional
from dataclasses import dataclass, field
@dataclass
class DiscoveredEndpoint:
method: str
path_pattern: str
first_seen: str
last_seen: str
request_count: int
source_ips: Set[str] = field(default_factory=set)
status_codes: Set[int] = field(default_factory=set)
has_auth_header: bool = False
documented: bool = False
class ShadowAPIDetector:
# Common patterns for parameterized path segments
PARAM_PATTERNS = [
(re.compile(r'/\d+'), '/{id}'),
(re.compile(r'/[0-9a-f]{8}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{12}'), '/{uuid}'),
(re.compile(r'/[a-zA-Z0-9]{20,40}'), '/{token}'),
]
def __init__(self):
self.documented_endpoints: Set[Tuple[str, str]] = set()
self.discovered_endpoints: Dict[Tuple[str, str], DiscoveredEndpoint] = {}
def load_openapi_spec(self, spec_path: str):
"""Load documented endpoints from OpenAPI specification."""
with open(spec_path, 'r') as f:
if spec_path.endswith('.json'):
spec = json.load(f)
else:
spec = yaml.safe_load(f)
paths = spec.get('paths', {})
for path, methods in paths.items():
# Normalize OpenAPI path parameters
normalized_path = re.sub(r'\{[^}]+\}', '{id}', path)
for method in methods:
if method.upper() in ('GET', 'POST', 'PUT', 'DELETE', 'PATCH', 'HEAD', 'OPTIONS'):
self.documented_endpoints.add((method.upper(), normalized_path))
print(f"Loaded {len(self.documented_endpoints)} documented endpoints from {spec_path}")
def normalize_path(self, path: str) -> str:
"""Normalize an observed path by replacing dynamic segments with placeholders."""
# Remove query string
path = path.split('?')[0]
for pattern, replacement in self.PARAM_PATTERNS:
path = pattern.sub(replacement, path)
return path
def process_access_log(self, log_file: str, log_format: str = "common"):
"""Process API access logs to discover endpoints."""
patterns = {
"common": re.compile(
r'(?P<ip>[\d.]+)\s+\S+\s+\S+\s+\[(?P<time>[^\]]+)\]\s+'
r'"(?P<method>\w+)\s+(?P<path>\S+)\s+\S+"\s+(?P<status>\d+)'
),
"json": None # Handle JSON logs separately
}
with open(log_file, 'r') as f:
for line in f:
if log_format == "json":
try:
entry = json.loads(line)
method = entry.get('method', entry.get('http_method', ''))
path = entry.get('path', entry.get('uri', ''))
status = int(entry.get('status', entry.get('status_code', 0)))
ip = entry.get('remote_addr', entry.get('client_ip', ''))
timestamp = entry.get('timestamp', entry.get('@timestamp', ''))
has_auth = bool(entry.get('authorization', entry.get('auth_header', '')))
except json.JSONDecodeError:
continue
else:
match = patterns[log_format].match(line)
if not match:
continue
method = match.group('method')
path = match.group('path')
status = int(match.group('status'))
ip = match.group('ip')
timestamp = match.group('time')
has_auth = 'Authorization' in line
# Only process API paths
if not path.startswith('/api') and not path.startswith('/v'):
continue
normalized = self.normalize_path(path)
key = (method.upper(), normalized)
if key not in self.discovered_endpoints:
self.discovered_endpoints[key] = DiscoveredEndpoint(
method=method.upper(),
path_pattern=normalized,
first_seen=timestamp,
last_seen=timestamp,
request_count=0,
documented=(key in self.documented_endpoints)
)
endpoint = self.discovered_endpoints[key]
endpoint.request_count += 1
endpoint.last_seen = timestamp
endpoint.source_ips.add(ip)
endpoint.status_codes.add(status)
if has_auth:
endpoint.has_auth_header = True
def identify_shadow_apis(self) -> List[DiscoveredEndpoint]:
"""Identify endpoints that are not in the documented specification."""
shadows = []
for key, endpoint in self.discovered_endpoints.items():
if not endpoint.documented:
shadows.append(endpoint)
# Sort by request count descending (most active shadows first)
shadows.sort(key=lambda e: e.request_count, reverse=True)
return shadows
def classify_risk(self, endpoint: DiscoveredEndpoint) -> str:
"""Classify the risk level of a shadow endpoint."""
risk_score = 0
# No authentication observed
if not endpoint.has_auth_header:
risk_score += 3
# High traffic volume
if endpoint.request_count > 1000:
risk_score += 2
elif endpoint.request_count > 100:
risk_score += 1
# Multiple source IPs (wider exposure)
if len(endpoint.source_ips) > 10:
risk_score += 2
# Successful responses (endpoint is functional)
if 200 in endpoint.status_codes or 201 in endpoint.status_codes:
risk_score += 1
# Write operations are higher risk
if endpoint.method in ('POST', 'PUT', 'DELETE', 'PATCH'):
risk_score += 2
# Sensitive path patterns
sensitive_patterns = ['admin', 'internal', 'debug', 'test', 'backup',
'config', 'health', 'metrics', 'graphql', 'console']
for pattern in sensitive_patterns:
if pattern in endpoint.path_pattern.lower():
risk_score += 3
break
if risk_score >= 8:
return "CRITICAL"
elif risk_score >= 5:
return "HIGH"
elif risk_score >= 3:
return "MEDIUM"
return "LOW"
def generate_report(self) -> dict:
"""Generate a comprehensive shadow API discovery report."""
shadows = self.identify_shadow_apis()
total_documented = len(self.documented_endpoints)
total_discovered = len(self.discovered_endpoints)
report = {
"scan_date": datetime.now().isoformat(),
"summary": {
"documented_endpoints": total_documented,
"total_discovered_endpoints": total_discovered,
"shadow_endpoints": len(shadows),
"shadow_ratio": f"{len(shadows)/max(total_discovered,1)*100:.1f}%",
},
"shadow_endpoints": []
}
for endpoint in shadows:
risk = self.classify_risk(endpoint)
report["shadow_endpoints"].append({
"method": endpoint.method,
"path": endpoint.path_pattern,
"risk_level": risk,
"request_count": endpoint.request_count,
"unique_sources": len(endpoint.source_ips),
"authenticated": endpoint.has_auth_header,
"status_codes": sorted(endpoint.status_codes),
"first_seen": endpoint.first_seen,
"last_seen": endpoint.last_seen,
})
return report
def main():
detector = ShadowAPIDetector()
# Load documented API specifications
spec_files = sys.argv[1:] if len(sys.argv) > 1 else ["openapi.yaml"]
for spec in spec_files:
if spec.endswith(('.yaml', '.yml', '.json')):
detector.load_openapi_spec(spec)
# Process access logs
detector.process_access_log("/var/log/api/access.log")
report = detector.generate_report()
print(f"\n{'='*60}")
print(f"SHADOW API DISCOVERY REPORT")
print(f"{'='*60}")
print(f"Documented: {report['summary']['documented_endpoints']}")
print(f"Discovered: {report['summary']['total_discovered_endpoints']}")
print(f"Shadow: {report['summary']['shadow_endpoints']} ({report['summary']['shadow_ratio']})")
print()
for ep in report["shadow_endpoints"]:
risk_marker = {"CRITICAL": "[!!!]", "HIGH": "[!!]", "MEDIUM": "[!]", "LOW": "[.]"}
print(f" {risk_marker.get(ep['risk_level'], '[?]')} {ep['method']} {ep['path']}")
print(f" Risk: {ep['risk_level']} | Requests: {ep['request_count']} | Auth: {ep['authenticated']}")
# Save full report
with open("shadow_api_report.json", "w") as f:
json.dump(report, f, indent=2, default=str)
print(f"\nFull report saved to shadow_api_report.json")
if __name__ == "__main__":
main()# AWS: Discover API Gateway endpoints not in documentation
aws apigateway get-rest-apis --query 'items[*].[name,id]' --output table
# List all routes for each API
aws apigatewayv2 get-apis --query 'Items[*].[Name,ApiId,ProtocolType]' --output table
# AWS Lambda function URLs (potential shadow APIs)
aws lambda list-function-url-configs --function-name "*" 2>/dev/null
# Find ALB listener rules routing to undocumented backends
aws elbv2 describe-rules --listener-arn $LISTENER_ARN \
--query 'Rules[*].[Priority,Conditions[0].Values[0],Actions[0].TargetGroupArn]'# Search for undocumented route definitions in source code
# Express.js routes
grep -rn "app\.\(get\|post\|put\|delete\|patch\)" --include="*.js" --include="*.ts" src/
# Flask/Django routes
grep -rn "@app\.route\|@api\.route\|path(" --include="*.py" src/
# Spring Boot endpoints
grep -rn "@\(Get\|Post\|Put\|Delete\|Patch\)Mapping\|@RequestMapping" --include="*.java" src/
# Compare found routes against OpenAPI specification
diff <(grep -roh "'/api/[^']*'" src/ | sort -u) \
<(yq '.paths | keys[]' openapi.yaml | sort -u)# Kong plugin configuration - reject unregistered routes
plugins:
- name: request-validator
config:
allowed_content_types:
- application/json
body_schema: null
- name: pre-function
config:
access:
- |
-- Block requests to unregistered endpoints
local registered = kong.cache:get("registered_endpoints")
local path = kong.request.get_path()
local method = kong.request.get_method()
local key = method .. ":" .. path
if not registered[key] then
kong.log.warn("Shadow API access attempt: ", key)
return kong.response.exit(404, {error = "Endpoint not registered"})
end© mukul975, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 3 other files (scripts, references) in skills/detecting-shadow-api-endpoints of mukul975/Anthropic-Cybersecurity-Skills.
Open the folder on GitHubat commit 54a7988
Detecting Shadow API Endpoints next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Detecting Shadow API Endpoints this skillmukul975/Anthropic-Cybersecurity-Skills | 34k | — | ~3.6k | Automated safety check: Pass | Apache-2.0 | |
| API DesignerJeffallan/claude-skills | 12k | 2 repos | ~2k | Automated safety check: Pass | MIT | |
| OpenAPI to MCP Servermcp-use/mcp-use | 11k | — | ~5.2k | Automated safety check: Pass | Apache-2.0 | |
| Use Yaakmountain-loop/yaak | 19k | — | ~1.9k | Automated safety check: Pass | MIT | |
| Old Coder API DesignAmazingAng/old-coder | 749 | 1 repos | ~3.4k | Automated safety check: Pass | MIT | |
| API CallerNVIDIA/SkillEvaluator | 544 | 1 repos | ~1.1k | Automated safety check: Pass | Apache-2.0 |
Jeffallan/claude-skills
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mcp-use/mcp-use
Turns an OpenAPI or Swagger spec into an MCP server with the mcp-use TypeScript SDK, mapping each operation to a tool, wiring auth, testing and deploying.
mountain-loop/yaak
A skill your agent uses when the user mentions Yaak, a Yaak workspace, or the yaak command, or asks to call, hit, or smoke test HTTP/REST endpoints, save or organize API requests for reuse or manual…
AmazingAng/old-coder
Reviews or designs an HTTP/JSON API's endpoints, auth, pagination, versioning and deprecations, guarding against inventing a bespoke interface or silently breaking consumers.
NVIDIA/SkillEvaluator
Call any REST API dynamically. An agent skill from NVIDIA/SkillEvaluator.
itsmostafa/aws-agent-skills
AWS API Gateway for REST and HTTP API management. An agent skill from itsmostafa/aws-agent-skills.
mukul975/Anthropic-Cybersecurity-Skills
Weighs infrastructure, TTP, malware code and timing evidence with the Diamond Model and competing hypotheses to reach a confidence-rated attribution.
mukul975/Anthropic-Cybersecurity-Skills
Walks through reverse engineering Go-compiled malware in Ghidra: parsing buildinfo and pclntab, recovering stripped function names and extracting dependencies.
mukul975/Anthropic-Cybersecurity-Skills
Guides forensic analysis of Windows LNK shortcut files and Jump Lists with LECmd, JLECmd and manual parsing to show file access and program execution.
mukul975/Anthropic-Cybersecurity-Skills
Hunts Windows malware persistence with Sysinternals Autoruns, covering run keys, services, scheduled tasks and drivers, with baseline comparison.
mukul975/Anthropic-Cybersecurity-Skills
Guides a Windows forensic examination of the NTFS Master File Table to recover deleted-file evidence, build timelines and spot timestomping.
mukul975/Anthropic-Cybersecurity-Skills
Detects DNS tunneling, ICMP exfiltration and HTTP-based covert channels in packet captures and DNS logs when hunting for hidden command-and-control traffic.
Works with
Categories
Discover and inventory shadow API endpoints that operate outside documented OpenAPI/Swagger specs, using traffic analysis against API gateways (Kong, AWS API Gateway, Envoy), cloud configuration…. Detecting Shadow API Endpoints is an agent skill from mukul975/Anthropic-Cybersecurity-Skills. Discover and inventory shadow API endpoints that operate outside documented OpenAPI/Swagger specs, using traffic analysis against API gateways (Kong, AWS API Gateway, Envoy), cloud configuration scanning, and source code repository mining for undocumented routes.
Detecting Shadow API Endpoints fits situations like: assessing API attack surface; auditing for forgotten test environments; deprecated API versions still running; building an API registration governance policy.
Run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill detecting-shadow-api-endpoints -a claude-code`. Or copy the skill folder (skills/detecting-shadow-api-endpoints in mukul975/Anthropic-Cybersecurity-Skills) into .claude/skills/detecting-shadow-api-endpoints in your project. Claude Code loads it when a task matches its description.
Run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill detecting-shadow-api-endpoints -a codex`. Or copy the skill folder (skills/detecting-shadow-api-endpoints in mukul975/Anthropic-Cybersecurity-Skills) into .agents/skills/detecting-shadow-api-endpoints in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill detecting-shadow-api-endpoints -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/detecting-shadow-api-endpoints, .gemini/skills/detecting-shadow-api-endpoints, .github/skills/detecting-shadow-api-endpoints and .opencode/skills/detecting-shadow-api-endpoints in your project.
Going by SKILL.md and its folder, Detecting Shadow API Endpoints needs Python for the scripts in its folder and the command-line tools its instructions call (aws). Our summary lists: Python 3.
SKILL.md names 5 domains. As links in the text: apisec.ai, wiz.io, checkmarx.com, treblle.com and blog.securelayer7.net. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
Detecting Shadow API Endpoints is published under the Apache-2.0 licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
About 3.6k tokens (SKILL.md is roughly 14k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 553 tokens, read only when the agent opens those files.
Skills that share tags, products or a category with Detecting Shadow API Endpoints: API Designer (Jeffallan/claude-skills, 12k stars), OpenAPI to MCP Server (mcp-use/mcp-use, 11k stars), Use Yaak (mountain-loop/yaak, 19k stars) and Old Coder API Design (AmazingAng/old-coder, 749 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
mukul975 (a GitHub user) maintains it in mukul975/Anthropic-Cybersecurity-Skills, which has 33,870 GitHub stars. The repository holds 639 skills in this directory. The repository was last updated on August 31, 2026.
Source: mukul975/Anthropic-Cybersecurity-Skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.