ObscureIQ | DogeQuest: Where the Data Came From
Casework · Groundtruth · Public briefing

DogeQuest.
Where the data came from.

In March 2025 a site published the names, home addresses, phone numbers, employers and vehicle details of roughly 1,700 Tesla owners and people connected to DOGE, then moved to the dark web. The public question was who was behind it. The useful question was where the data came from, because that decided who else was exposed. The firm answered it: one 2021 breach of a parking app, matched at 98.2 percent, enriched with broker data.

People tagged1,700Roughly, in the published set. 23 records target DOGE staff and their families directly.
Matched to the source98.2%1,647 of the doxed Tesla owners matched the 2021 ParkMobile breach on email and phone.
At very high risk150+Federal and military personnel, executives, officials, advisors. Named and warned rather than guessed at.
Released
2 April 2025, ObscureIQ briefing to the public
Question
Where did the targeting data originate
Method
Cross-reference against known breach corpora
Confidence
High
01 · The backstory

A doxxing site, then a dark web address.

DogeQuest (dogeque.st) began on the surface web as a doxxing operation against Tesla owners and people affiliated with Elon Musk's Department of Government Efficiency. It later moved most of its personal data operation to the dark web, rebranded as DogeQuest Unleashed.

What it published

  • Names
  • Home addresses
  • Phone numbers
  • LinkedIn handles
  • Employer and job title
  • Vehicle registration details

What it said it was for

Pressure on anyone associated with Tesla or with Musk's government initiatives, by exposing their private information. The firm's threat model reads the intent as less about inciting violence than about instilling fear: if owning a Tesla becomes synonymous with personal risk, that hurts the company more effectively than a protest or an attack on a charging station. The collateral damage to individual owners is the likely and potentially severe consequence.

02 · The finding

One parking app breach, matched at 98.2 percent.

The investigation identified the 2021 ParkMobile breach as the source of the Tesla owner data. ParkMobile is a parking payment app used across US cities; in March 2021 a third-party software vulnerability exposed about 21 million accounts, with emails, phone numbers, licence plates and vehicle nicknames, and hashed passwords. Sold on dark web forums at first, the data later became freely available.

Step 1

The corpus

A database of 21.9 million records from the 2021 ParkMobile breach was obtained and loaded.

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Step 2

The tell

Every record where "Tesla" or a proxy word appeared in the vehicle nickname field was extracted: 74,349 of them. The nickname was how the operators found Tesla owners.

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Step 3

The match

Emails and phone numbers in the DogeQuest set were compared against those records. 1,647 matched: 98.2 percent of every Tesla owner doxed.

Every sample analysed from DogeQuest matched the ParkMobile breach on email, phone and vehicle details. The linkage is a reminder that an innocuous service provider, breached through a third-party integration, can become a targeting list four years later.

03 · The enrichment

The breach had no addresses. The brokers did.

ParkMobile's data carried emails, phones, vehicle details and hashed passwords. It did not carry home addresses, job titles, employers, LinkedIn or X handles. Those came from data brokers, most likely scraped or stolen from people-search sites rather than bought fresh.

What the records show

Scraped, not bought

Many DogeQuest records are less enriched than a commercial broker service would have made them. The operators understood data but not the broker ecosystem, or did not want the transaction traced.

What the firm tested

How far it could go

The firm purchased commercial data to see how easily the profiles could be extended, and was able to expand the profiles on virtually all 1,700 people substantially: more contact information, employment detail, and more.

The implication

From a list to an attack

Breached data paired with broker data expands what an attacker holds on each person. With effort, passwords, authentication tokens or cookies follow, and the threat reaches government systems, not only the individuals.

04 · Who was exposed

Not a list of Tesla owners. A list of people with positions.

About 1,700 people are tagged in the set. 23 records specifically target DOGE employees, their families and their connections. The firm identified more than 150 people at very high risk: DOGE staff and families, US military and federal agency personnel, executives at major technology and financial firms, policy think tanks, health officials, federal contractors and IMF advisors.

A random sample of organisations with people in the set

Bank of the WestUBSPwCVerizonSpyCloudOracleBerkshire PartnersAtlantic CouncilTargeted VictoryCiscoCitiDellGoogleMontrose EnvironmentalMorgan StanleyOneNation

Specific examples, identities withheld

US military operationsExposed: Email, phone, LinkedIn username, home address, employer, job title
Veterans AffairsExposed: Email, phone, LinkedIn username, home address, employer, job title, X account
Social Security Administration executiveExposed: Home address
FBI executiveExposed: Email, phone, home address
Lawrence Livermore National LaboratoryExposed: Withheld
US Office of Government EthicsExposed: Withheld
Staffer for a member of CongressExposed data on record
Instructor, army.milExposed data on record
IMF advisorExposed data on record
United Nations consultantExposed data on record

Job titles that indicate government work, among many more

State and federal government

  • Account manager, State of California
  • Assistant state coordinator, Florida
  • County and district clerk
  • Division chief, capital projects
  • Executive assistant administrator for enterprise support
  • Director, enterprise cloud solutions
  • Presidential Innovation Fellow
  • Senior manager, public policy
  • Vice president and general manager, public sector

Defense and national security

  • Branch head
  • Diplomatic correspondent
  • Investigator in chief
  • Telecommunication specialist

Judiciary and legal

  • General counsel
  • Assistant general counsel, SVP
  • Partner, litigation; chair of white collar and government investigations
  • Co-chair, appellate practice
  • Attorney, public sector
  • Board member

Think tanks, health, advisory

  • Nonresident senior fellow
  • Vice president, smart cities
  • Pulmonary and critical care
  • EVP, US life sciences
  • Senior advisor
  • Principal, expert witness
05 · The threat model

Low odds for any one owner. Not low for the ones with profiles.

The risk to any one individual may be low, given how many Tesla owners there are. The harm could be severe, and the risk rises with profile and net worth. Giving the site airtime plays into its narrative; leaving owners unaware of their exposure is worse.

Assets at risk

  • Physical safety
  • Property, the vehicle first
  • Digital security, further exploitation of what is exposed
  • Reputation and privacy

Threat actors

  • Anti-Musk extremists
  • Mischief-motivated hackers and trolls
  • Political or ideological actors
  • Collateral: disgruntled neighbours, criminal opportunists

Vulnerabilities

  • Raw owner data exposed without masking
  • Proximity: owners easily identified within close range of someone motivated or unstable
  • No mitigation protocols; owners unaware and unprepared
  • Amplification as the data is copied to forums

Five scenarios

Scenario 01

Physical confrontation or violence

Actor. Local anti-Tesla activist or extremist

Action. Identifies a nearby owner from the site and confronts or assaults them.

Impact. Severe injury or death, legal consequences for the attacker, widespread fear.

Scenario 02

Vandalism or property damage

Actor. Anti-Tesla individual or disgruntled neighbour

Action. Finds the owner's address and damages the vehicle, the home or other property.

Impact. Property damage, insurance claims, potential escalation.

Scenario 03

Swatting or false reporting

Actor. Troll or online harasser

Action. Uses the doxxed address to file false police reports.

Impact. A police response at the door, potential harm, trauma, reputational damage.

Scenario 04

Burglary or theft

Actor. Criminal opportunist

Action. Uses the doxxed information to target owners for car theft or burglary.

Impact. Financial loss, safety risk, ongoing fear.

Scenario 05

Online harassment and doxxing escalation

Actor. Hackers or trolls

Action. Amplifies the exposure by linking further personal information: social media, family data.

Impact. Sustained harassment, privacy erosion, mental distress.

Likelihood and impact, a typical owner

Threat scenarioLikelihoodImpactRisk
Physical violenceLowHighModerate
Vandalism, property damageModerateMediumModerate
Swatting, false reportingLowHighModerate
Burglary, theftModerateMediumModerate
Online harassment, doxxingHighLow to mediumHigh

Likelihood and impact, a high-profile owner

Threat scenarioLikelihoodImpactRisk
Physical violenceModerateCatastrophicHigh
Vandalism, property damageModerate to highMedium to highHigh
Swatting, false reportingModerateHighHigh
Burglary, theftModerate to highHighHigh
Online harassment, doxxingModerate to highMedium to highHigh
Kidnapping or extortionLowCatastrophicHigh
Stalking and surveillanceModerateMediumHigh
07 · Recommendations

What the briefing asked for.

For high-risk officials

Digital executive protection

A comprehensive threat surface assessment; proactive mitigation of identified and emerging threats; removal of exposed personal information from data brokers; continuous dark web monitoring for compromise and leaks; monitoring of social platforms, forums, extremist sites and comment sections for threats, doxxing attempts and indicators of compromise.

Obscurity DEP →
For organisations

Mandatory cyber security and privacy training, together

Data privacy: how to manage sensitive personal data, with practical examples of how personal data is used to compromise an organisation. Account security: unique passwords, multi-factor authentication on official and personal accounts, the risk of reuse, and recognising phishing and social engineering aimed at either. The combination works better than either alone: an employee who can see the privacy impact on themselves applies the security principles to company data.

Tactical Privacy Training →
Sources and coverage

The briefing, the reporting, the video.

Bring us the thing that escalated.

Groundtruth answers who is behind it and where it came from, and delivers the finding in a form counsel can file on. The DogeQuest briefing is what that looks like when it is published; client matters never are.

The site was the story.
The source was the finding.