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Lamborghini Carjackers Lured by $243M Cyberheist

The parents of a 19-year-old Connecticut honors student accused of taking part in a $243 million cryptocurrency heist in August were carjacked a week later — while out house-hunting in a brand new Lamborghini. Prosecutors say the couple was beaten and briefly kidnapped by six young men who traveled from Florida as part of a botched plan to hold the parents for ransom.

Image: ABC7NY.  youtube.com/watch?v=xoiaGzwrunY

Late in the afternoon of Aug. 25, 2024 in Danbury, Ct., a married couple in their 50s pulled up to a gated community in a new Lamborghini Urus (investigators say the sports car still had temporary tags) when they were intentionally rear-ended by a Honda Civic.

A witness told police they saw three men exit a van that was following the Honda, and said the men began assaulting the couple and forcing them into the van. Local police officers spotted the van speeding from the scene and pursued it, only to find the vehicle crashed and abandoned a short distance away.

Inside the disabled van the police found the couple with their hands and feet bound in duct tape, the man visibly bruised after being assaulted with a baseball bat. Danbury police soon reported arresting six suspects in the kidnapping, all men aged 18-26 from Florida. They also recovered the abandoned Lamborghini from a wooded area.

A criminal complaint (PDF) filed on Sept. 24 against the six men does not name the victims, referring to them only as a married couple from Danbury with the initials R.C. and S.C. But prosecutors in Connecticut said they were targeted “because the co-conspirators believed the victims’ son had access to significant amounts of digital currency.”

What made the Miami men so convinced R.C. and S.C.’s son was loaded with cryptocurrency? Approximately one week earlier, on Aug. 19, a group of cybercriminals that allegedly included the couple’s son executed a sophisticated phone-based social engineering attack in which they stole $243 million worth of cryptocurrency from a victim in Washington, D.C.

That’s according to ZachXBT, a frequently cited crypto crime investigator who published a lengthy thread that broke down how the theft was carried out and ultimately exposed by the perpetrators themselves.

ZachXBT’s post included a screen recording of a Discord chat session made by one of the participants to the $243 million robbery, noting that two of the people involved managed to leak the username of the Microsoft Windows PCs they were using to participate in the chat.

One of the usernames leaked during the chat was Veer Chetal. According to ZachXBT, that name corresponds to a 19-year-old from Danbury who allegedly goes by the nickname “Wiz,” although in the leaked video footage he allegedly used the handle “Swag.”  Swag was reportedly involved in executing the early stages of the crypto heist — gaining access to the victim’s Gmail and iCloud accounts.

A still shot from a video screenshare in which one of the participants on the Discord voice chat used the Windows username Veer Chetal. Image: x.com/zachxbt

The same day ZachXBT published his findings, a criminal indictment was issued in Washington D.C. charging two of the men he named as involved in the heist. Prosecutors allege Malone “Greavys” Lam, 20, of Miami and Los Angeles, and Jeandiel “Box” Serrano, 21, of Los Angeles conspired to steal and launder over $230 million in cryptocurrency from a victim in Washington, D.C. The indictment alleges Lam and Serrano were helped by other unnamed co-conspirators.

“Lam and Serrano then allegedly spent the laundered cryptocurrency proceeds on international travel, nightclubs, luxury automobiles, watches, jewelry, designer handbags, and rental homes in Los Angeles and Miami,” reads a press release from the U.S. Department of Justice.

By tracing the flow of funds stolen in the heist, ZachXBT concluded that Wiz received a large percentage from the theft, noting that “additional comfort [in naming him as involved] was gained as throughout multiple recordings accomplices refer to him as ‘Veer’ on audio and in chats.”

“A cluster of [cryptocurrency] addresses tied to both Box/Wiz received $41M+ from two exchanges over the past few weeks primarily flowing to luxury goods brokers to purchase cars, watches, jewelry, and designer clothes,” ZachXBT wrote.

KrebsOnSecurity sought comment from Veer Chetal, and from his parents — Radhika Chetal and Suchil Chetal. This story will be updated in the event that anyone representing the Chetal family responds. Veer Chetal has not been publicly charged with any crime.

According to a news brief published by a private Catholic high school in Danbury that Veer Chetal attended, in 2022 he successfully completed Harvard’s Future Lawyers Program, a “unique pre-professional program where students, guided by qualified Harvard undergraduate instructors, learn how to read and build a case, how to write position papers, and how to navigate a path to law school.” A November 2022 story at patch.com quoted Veer Chetal (class of 2024) crediting the Harvard program with his decision to pursue a career in law.

It remains unclear which Chetal family member acquired the 2023 Lamborghini Urus, which has a starting price of around $233,000. Sushil Chetal’s LinkedIn profile says he is a vice president at the investment bank Morgan Stanley.

It is clear that other alleged co-conspirators to the $243 million heist displayed a conspicuous consumption of wealth following the date of the heist. ZachXBT’s post chronicled Malone’s flashy lifestyle, in which he allegedly used the stolen money to purchase more than 10 vehicles, rent palatial properties, travel with friends on chartered jets, and spend between $250,000 and $500,000 a night at clubs in Los Angeles and Miami.

In the photo on the bottom right, Greavys/Lam is the individual on the left wearing shades. They are pictured leaving a luxury goods store. Image: x.com/zachxbt

WSVN-TV in Miami covered an FBI raid of a large rented waterfront home around the time Malone and Serrano were arrested. The news station interviewed a neighbor of the home’s occupants, who reported a recent large party at the residence wherein the street was lined with high-end luxury vehicles — all of them with temporary paper tags.

ZachXBT unearthed a video showing a person identified as Wiz at a Miami nightclub earlier this year, wherein they could be seen dancing to the crowd’s chants while holding an illuminated sign with the message, “I win it all.”

It appears that all of the suspects in the cyber heist (and at least some of the alleged carjackers) are members of The Com, an archipelago of crime-focused chat communities which collectively functions as a kind of distributed cybercriminal social network that facilitates instant collaboration.

As documented in last month’s deep dive on top Com members,  The Com is also a place where cybercriminals go to boast about their exploits and standing within the community, or to knock others down a peg or two. Prominent Com members are endlessly sniping over who pulled off the most impressive heists, or who has accumulated the biggest pile of stolen virtual currencies.

And as often as they extort and rob victims for financial gain, members of The Com are trying to wrest stolen money from their cybercriminal rivals — often in ways that spill over into physical violence in the real world.

One of the six Miami-area men arrested in the carjacking and extortion plot gone awry — Reynaldo “Rey” Diaz — was shot twice while parked in his bright yellow Corvette in Miami’s design district in 2022. In an interview with a local NBC television station, Diaz said he was probably targeted for the jewelry he was wearing, which he described as “pretty expensive.”

KrebsOnSecurity has learned Diaz also went by the alias “Pantic” on Telegram chat channels dedicated to stealing cryptocurrencies. Pantic was known for participating in several much smaller cyber heists in the past, and spending most of his cut on designer clothes and jewelry.

The Corvette that Diaz was sitting in when he was shot in 2022. Image: NBC 6, South Florida.

Earlier this year, Diaz was “doxed,” or publicly outed as Pantic, with his personal and family information posted on a harassment and extortion channel frequented by members of The Com. The reason cited for Pantic’s doxing was widely corroborated by multiple Com members: Pantic had inexplicably robbed two close friends at gunpoint, one of whom recently died of a drug overdose.

Government prosecutors say the brazen daylight carjacking was paid for and organized by 23-year-old Miami resident Angel “Chi Chi” Borrero. In 2022, Borrero was arrested in Miami for aggravated assault with a deadly weapon.

The six Miami men face charges including first-degree assault, kidnapping and reckless endangerment, and five of them are being held on a $1 million bond. One suspect is also charged with reckless driving, engaging police in pursuit and evading responsibility; his bond was set at $2 million. Lam and Serrano are each charged with conspiracy to commit wire fraud and conspiracy to launder money.

Cybercriminals hail from all walks of life and income levels, but some of the more accomplished cryptocurrency thieves also tend to be among the more privileged, and from relatively well-off families. In other words, these individuals aren’t stealing to put food on the table: They’re doing it so they can amass all the trappings of instant wealth, and so they can boast about their crimes to others on The Com.

There is also a penchant among this crowd to call attention to their activities in conspicuous ways that hasten their arrest and criminal charging. In many ways, the story arc of the young men allegedly involved in the $243 million heist tracks closely to that of Joel Ortiz, a valedictorian who was sentenced in 2019 to 10 years in prison for stealing more than $5 million in cryptocurrencies.

Ortiz famously posted videos of himself and co-conspirators chartering flights and partying it up at LA nightclubs, with scantily clad women waving giant placards bearing their “OG” usernames — highly-prized, single-letter social media accounts that they’d stolen or purchased stolen from others.

Ortiz earned the distinction of being the first person convicted of SIM-swapping, a crime that involves using mobile phone company insiders or compromised employee accounts to transfer a target’s phone number to a mobile device controlled by the attackers. From there, the attacker can intercept any password reset links, and any one-time passcodes sent via SMS or automated voice calls.

But as the mobile carriers seek to make their networks less hospitable to SIM-swappers, and as more financial platforms seek to harden user account security, today’s crypto thieves are finding they don’t need SIM-swaps to steal obscene amounts of cryptocurrency. Not when tricking people over the phone remains such an effective approach.

According to ZachXBT, the crooks responsible for the $243 million theft initially compromised the target’s personal accounts after calling them as Google Support and using a spoofed number. The attackers also spoofed a call from account support representatives at the cryptocurrency exchange Gemini, claiming the target’s account had been hacked.

From there the target was social engineered over the phone into resetting multi-factor authentication and sending Gemini funds to a compromised wallet. ZachXBT says the attackers also convinced the victim to use AnyDesk to share their screen, and in doing so the victim leaked their private keys.

swaggerHole - A Python3 Script Searching For Secret On Swaggerhub

By: Zion3R


Introduction 

This tool is made to automate the process of retrieving secrets in the public APIs on [swaggerHub](https://app.swaggerhub.com/search). This tool is multithreaded and pipe mode is available :) 

Requirements 

 - python3 (sudo apt install python3) - pip3 (sudo apt install python3-pip) ## Installation
pip3 install swaggerhole
or cloning this repository and running
git clone https://github.com/Liodeus/swaggerHole.git
pip3 install .

Usage

   _____ _      __ ____ _ ____ _ ____ _ ___   _____
/ ___/| | /| / // __ `// __ `// __ `// _ \ / ___/
(__ ) | |/ |/ // /_/ // /_/ // /_/ // __// /
/____/ |__/|__/ \__,_/ \__, / \__, / \___//_/
__ __ __ /____/ /____/
/ / / /____ / /___
/ /_/ // __ \ / // _ \
/ __ // /_/ // // __/
/_/ /_/ \____//_/ \___/

usage: swaggerhole [-h] [-s SEARCH] [-o OUT] [-t THREADS] [-j] [-q] [-du] [-de]

optional arguments:
-h, --help show this help message and exit
-s SEARCH, --search SEARCH
Term to search
-o OUT, --out OUT Output directory
-t THREADS, --threads THREADS
Threads number (Default 25)
-j, --json Json ouput
-q, --quiet Remove banner
-du, --deactivate_url
Deactivate the URL filtering
-de, --deactivate_email
Deactivate the email filtering

Search for secret about a domain

swaggerHole -s test.com

echo test.com | swaggerHole

Search for secret about a domain and output to json

swaggerHole -s test.com --json

echo test.com | swaggerHole --json

Search for secret about a domain and do it fast :)

swaggerHole -s test.com -t 100

echo test.com | swaggerHole -t 100

Output explanation

Normal output

 `Finding_Type - Finding - [Swagger_Name][Date_Last_Update][Line:Number]` 

Json output

 `{"Finding_Type": Finding, "File": File_path, "Date": Date_Last_Update, "Line": Number}` 

Deactivate url/email 

Using -du or -de remove the filtering done by the tool. There is more false positive with those options. 

SwaggerSpy - Automated OSINT On SwaggerHub

By: Zion3R


SwaggerSpy is a tool designed for automated Open Source Intelligence (OSINT) on SwaggerHub. This project aims to streamline the process of gathering intelligence from APIs documented on SwaggerHub, providing valuable insights for security researchers, developers, and IT professionals.


What is Swagger?

Swagger is an open-source framework that allows developers to design, build, document, and consume RESTful web services. It simplifies API development by providing a standard way to describe REST APIs using a JSON or YAML format. Swagger enables developers to create interactive documentation for their APIs, making it easier for both developers and non-developers to understand and use the API.


About SwaggerHub

SwaggerHub is a collaborative platform for designing, building, and managing APIs using the Swagger framework. It offers a centralized repository for API documentation, version control, and collaboration among team members. SwaggerHub simplifies the API development lifecycle by providing a unified platform for API design and testing.


Why OSINT on SwaggerHub?

Performing OSINT on SwaggerHub is crucial because developers, in their pursuit of efficient API documentation and sharing, may inadvertently expose sensitive information. Here are key reasons why OSINT on SwaggerHub is valuable:

  1. Developer Oversights: Developers might unintentionally include secrets, credentials, or sensitive information in API documentation on SwaggerHub. These oversights can lead to security vulnerabilities and unauthorized access if not identified and addressed promptly.

  2. Security Best Practices: OSINT on SwaggerHub helps enforce security best practices. Identifying and rectifying potential security issues early in the development lifecycle is essential to ensure the confidentiality and integrity of APIs.

  3. Preventing Data Leaks: By systematically scanning SwaggerHub for sensitive information, organizations can proactively prevent data leaks. This is especially crucial in today's interconnected digital landscape where APIs play a vital role in data exchange between services.

  4. Risk Mitigation: Understanding that developers might forget to remove or obfuscate sensitive details in API documentation underscores the importance of continuous OSINT on SwaggerHub. This proactive approach mitigates the risk of unintentional exposure of critical information.

  5. Compliance and Privacy: Many industries have stringent compliance requirements regarding the protection of sensitive data. OSINT on SwaggerHub ensures that APIs adhere to these regulations, promoting a culture of compliance and safeguarding user privacy.

  6. Educational Opportunities: Identifying oversights in SwaggerHub documentation provides educational opportunities for developers. It encourages a security-conscious mindset, fostering a culture of awareness and responsible information handling.

By recognizing that developers can inadvertently expose secrets, OSINT on SwaggerHub becomes an integral part of the overall security strategy, safeguarding against potential threats and promoting a secure API ecosystem.


How SwaggerSpy Works

SwaggerSpy obtains information from SwaggerHub and utilizes regular expressions to inspect API documentation for sensitive information, such as secrets and credentials.


Getting Started

To use SwaggerSpy, follow these steps:

  1. Installation: Clone the SwaggerSpy repository and install the required dependencies.
git clone https://github.com/UndeadSec/SwaggerSpy.git
cd SwaggerSpy
pip install -r requirements.txt
  1. Usage: Run SwaggerSpy with the target search terms (more accurate with domains).
python swaggerspy.py searchterm
  1. Results: SwaggerSpy will generate a report containing OSINT findings, including information about the API, endpoints, and secrets.

Disclaimer

SwaggerSpy is intended for educational and research purposes only. Users are responsible for ensuring that their use of this tool complies with applicable laws and regulations.


Contribution

Contributions to SwaggerSpy are welcome! Feel free to submit issues, feature requests, or pull requests to help improve this tool.


About the Author

SwaggerSpy is developed and maintained by Alisson Moretto (UndeadSec)

I'm a passionate cyber threat intelligence pro who loves sharing insights and crafting cybersecurity tools.


TODO

Regular Expressions Enhancement
  • [ ] Review and improve existing regular expressions.
  • [ ] Ensure that regular expressions adhere to best practices.
  • [ ] Check for any potential optimizations in the regex patterns.
  • [ ] Test regular expressions with various input scenarios for accuracy.
  • [ ] Document any complex or non-trivial regex patterns for better understanding.
  • [ ] Explore opportunities to modularize or break down complex patterns.
  • [ ] Verify the regular expressions against the latest specifications or requirements.
  • [ ] Update documentation to reflect any changes made to the regular expressions.

License

SwaggerSpy is licensed under the MIT License. See the LICENSE file for details.


Thanks

Special thanks to @Liodeus for providing project inspiration through swaggerHole.



APIDetector - Efficiently Scan For Exposed Swagger Endpoints Across Web Domains And Subdomains

By: Zion3R


APIDetector is a powerful and efficient tool designed for testing exposed Swagger endpoints in various subdomains with unique smart capabilities to detect false-positives. It's particularly useful for security professionals and developers who are engaged in API testing and vulnerability scanning.


Features

  • Flexible Input: Accepts a single domain or a list of subdomains from a file.
  • Multiple Protocols: Option to test endpoints over both HTTP and HTTPS.
  • Concurrency: Utilizes multi-threading for faster scanning.
  • Customizable Output: Save results to a file or print to stdout.
  • Verbose and Quiet Modes: Default verbose mode for detailed logs, with an option for quiet mode.
  • Custom User-Agent: Ability to specify a custom User-Agent for requests.
  • Smart Detection of False-Positives: Ability to detect most false-positives.

Getting Started

Prerequisites

Before running APIDetector, ensure you have Python 3.x and pip installed on your system. You can download Python here.

Installation

Clone the APIDetector repository to your local machine using:

git clone https://github.com/brinhosa/apidetector.git
cd apidetector
pip install requests

Usage

Run APIDetector using the command line. Here are some usage examples:

  • Common usage, scan with 30 threads a list of subdomains using a Chrome user-agent and save the results in a file:

    python apidetector.py -i list_of_company_subdomains.txt -o results_file.txt -t 30 -ua "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/90.0.4430.212 Safari/537.36"
  • To scan a single domain:

    python apidetector.py -d example.com
  • To scan multiple domains from a file:

    python apidetector.py -i input_file.txt
  • To specify an output file:

    python apidetector.py -i input_file.txt -o output_file.txt
  • To use a specific number of threads:

    python apidetector.py -i input_file.txt -t 20
  • To scan with both HTTP and HTTPS protocols:

    python apidetector.py -m -d example.com
  • To run the script in quiet mode (suppress verbose output):

    python apidetector.py -q -d example.com
  • To run the script with a custom user-agent:

    python apidetector.py -d example.com -ua "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/90.0.4430.212 Safari/537.36"

Options

  • -d, --domain: Single domain to test.
  • -i, --input: Input file containing subdomains to test.
  • -o, --output: Output file to write valid URLs to.
  • -t, --threads: Number of threads to use for scanning (default is 10).
  • -m, --mixed-mode: Test both HTTP and HTTPS protocols.
  • -q, --quiet: Disable verbose output (default mode is verbose).
  • -ua, --user-agent: Custom User-Agent string for requests.

RISK DETAILS OF EACH ENDPOINT APIDETECTOR FINDS

Exposing Swagger or OpenAPI documentation endpoints can present various risks, primarily related to information disclosure. Here's an ordered list based on potential risk levels, with similar endpoints grouped together APIDetector scans:

1. High-Risk Endpoints (Direct API Documentation):

  • Endpoints:
    • '/swagger-ui.html', '/swagger-ui/', '/swagger-ui/index.html', '/api/swagger-ui.html', '/documentation/swagger-ui.html', '/swagger/index.html', '/api/docs', '/docs', '/api/swagger-ui', '/documentation/swagger-ui'
  • Risk:
    • These endpoints typically serve the Swagger UI interface, which provides a complete overview of all API endpoints, including request formats, query parameters, and sometimes even example requests and responses.
    • Risk Level: High. Exposing these gives potential attackers detailed insights into your API structure and potential attack vectors.

2. Medium-High Risk Endpoints (API Schema/Specification):

  • Endpoints:
    • '/openapi.json', '/swagger.json', '/api/swagger.json', '/swagger.yaml', '/swagger.yml', '/api/swagger.yaml', '/api/swagger.yml', '/api.json', '/api.yaml', '/api.yml', '/documentation/swagger.json', '/documentation/swagger.yaml', '/documentation/swagger.yml'
  • Risk:
    • These endpoints provide raw Swagger/OpenAPI specification files. They contain detailed information about the API endpoints, including paths, parameters, and sometimes authentication methods.
    • Risk Level: Medium-High. While they require more interpretation than the UI interfaces, they still reveal extensive information about the API.

3. Medium Risk Endpoints (API Documentation Versions):

  • Endpoints:
    • '/v2/api-docs', '/v3/api-docs', '/api/v2/swagger.json', '/api/v3/swagger.json', '/api/v1/documentation', '/api/v2/documentation', '/api/v3/documentation', '/api/v1/api-docs', '/api/v2/api-docs', '/api/v3/api-docs', '/swagger/v2/api-docs', '/swagger/v3/api-docs', '/swagger-ui.html/v2/api-docs', '/swagger-ui.html/v3/api-docs', '/api/swagger/v2/api-docs', '/api/swagger/v3/api-docs'
  • Risk:
    • These endpoints often refer to version-specific documentation or API descriptions. They reveal information about the API's structure and capabilities, which could aid an attacker in understanding the API's functionality and potential weaknesses.
    • Risk Level: Medium. These might not be as detailed as the complete documentation or schema files, but they still provide useful information for attackers.

4. Lower Risk Endpoints (Configuration and Resources):

  • Endpoints:
    • '/swagger-resources', '/swagger-resources/configuration/ui', '/swagger-resources/configuration/security', '/api/swagger-resources', '/api.html'
  • Risk:
    • These endpoints often provide auxiliary information, configuration details, or resources related to the API documentation setup.
    • Risk Level: Lower. They may not directly reveal API endpoint details but can give insights into the configuration and setup of the API documentation.

Summary:

  • Highest Risk: Directly exposing interactive API documentation interfaces.
  • Medium-High Risk: Exposing raw API schema/specification files.
  • Medium Risk: Version-specific API documentation.
  • Lower Risk: Configuration and resource files for API documentation.

Recommendations:

  • Access Control: Ensure that these endpoints are not publicly accessible or are at least protected by authentication mechanisms.
  • Environment-Specific Exposure: Consider exposing detailed API documentation only in development or staging environments, not in production.
  • Monitoring and Logging: Monitor access to these endpoints and set up alerts for unusual access patterns.

Contributing

Contributions to APIDetector are welcome! Feel free to fork the repository, make changes, and submit pull requests.

Legal Disclaimer

The use of APIDetector should be limited to testing and educational purposes only. The developers of APIDetector assume no liability and are not responsible for any misuse or damage caused by this tool. It is the end user's responsibility to obey all applicable local, state, and federal laws. Developers assume no responsibility for unauthorized or illegal use of this tool. Before using APIDetector, ensure you have permission to test the network or systems you intend to scan.

License

This project is licensed under the MIT License.

Acknowledgments



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