Appen 2020 Data Breach
ObscureIQ Breach Intelligence
Low SeverityWebsite / service breach
Appen AI Training Data Company Breach (2020): 5.9 Million User Accounts Including Passwords & Employer Exposed
AI data services company.
Verified by ObscureIQ Intelligence
17/100Breach Risk Index
3Data Value
25Market Recency
584dSince Breach
Breach Intelligence Summary
Entity: Appen · Actor: Unknown · Sources: 8 references
Attack: Unknown
Profile: Company · AI data services company · Online platform · Australia
Timeline: Breach (2020-06-22) · Indexed (Dec 01, 2024) · Year (2020)
Exposure: 5.9M records · 6 fields: Email Address, Employer, Full Name, IP Address, Password, Phone Number
Status: Confirmed
Executive Summary
In June 2020, the AI training-data company Appen suffered a data breach affecting almost 5.9 million users, later sold online. Exposed data included names, email addresses, and passwords stored as bcrypt hashes, with some records also containing phone numbers, employers, and IP addresses.
ObscureIQ assessment: Primary risks include password reuse, account compromise, and targeted phishing of contractors or workforce participants. Employer-linked fields can also help attackers build more convincing employment-themed scams.
Breach Impact
Bcrypt hashing limits password recovery, so the main exposure is the identity/contact set (name, email, phone, employer), useful for phishing and profiling of a workforce of data annotators.
About Appen
Appen is an AI training-data company that provides labeled datasets and human-annotation services used to build and improve machine-learning models.
Why They Hold Your Data
AI training data companies collect contributor and contractor account data, including names, emails, passwords, IP addresses, phone numbers, and employer-linked information used to manage distributed labor and annotation work.
Recent Developments
Appen continued operating as an AI data provider. The breached data was sold online after the incident.
Data Points Exposed
6 verified field types
Email Address
Employer
Full Name High
IP Address
Password Critical
Phone Number
Field names are shown in full for clarity and search visibility. Canonical machine keys are emitted only in this page’s structured data.
Exploitation & Downstream Threats
Threat Activity:Moderate
Primary downstream threats:
- Credential stuffing against reused passwords across other platforms
- SIM swap attacks where phone numbers are present
- Targeted phishing campaigns using exposed email addresses
- Employment-based social engineering using job and employer data
Threat vectors:
- Phishing, credential stuffing & account takeover
- Business Email Compromise seeding
- Name-based social engineering
- Geolocation & account flagging
- Credential stuffing & account takeover
- SIM swapping, vishing & SMS phishing
Recommended Actions
If you believe your information may be included:
Change Reused Passwords
Update this account and anywhere you reused the password; use a manager.
Enable MFA Everywhere
Turn on multi-factor authentication on email first, then financial accounts.
Report & Recover
If you spot misuse, start an official recovery plan and report fraud.
Frequently Asked Questions
What happened in the Appen breach?▾
In June 2020, the AI training-data company Appen suffered a data breach affecting almost 5.9 million users, later sold online. Exposed data included names, email addresses, and passwords stored as bcrypt hashes, with some records also containing phone numbers, employers, and IP addresses.
What data was exposed?▾
Verified fields include Email Address, Employer, Full Name, IP Address, Password, Phone Number.
What should I do if I was affected?▾
Change reused passwords, enable MFA, and (if identity or financial data is involved) freeze your credit and monitor your accounts.
Sources & References
Every claim on this page is traceable. This breach draws on:
Breach Index
Breach Index
Cross-source
9ghz
Cross-source
BreachForums_Official_Index
Cross-source
Dehashed
Cross-source
Keeper
Cross-source
leakfind
ObscureIQ Intelligence
ObscureIQ proprietary analysis
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