R/data_classes.R
data_classes.RdGet list of classes of data that have been exposed in breaches
data_classes(verbose = TRUE, agent = NULL)
| verbose | whether to message about http errors and re-tries |
|---|---|
| agent | agent to be used as header in calls, by default "HIBPwned R pkg". # nolint |
Data.frame containing data class details
Note that the package uses memoise
(https://github.com/r-lib/memoise)
with no timeout argument
so that results are cached inside an active R session.
data_classes()#> [1] "Account balances" "Address book contacts" #> [3] "Age groups" "Ages" #> [5] "Apps installed on devices" "Astrological signs" #> [7] "Audio recordings" "Auth tokens" #> [9] "Avatars" "Bank account numbers" #> [11] "Beauty ratings" "Biometric data" #> [13] "Bios" "Browser user agent details" #> [15] "Browsing histories" "Buying preferences" #> [17] "Car ownership statuses" "Career levels" #> [19] "Cellular network names" "Charitable donations" #> [21] "Chat logs" "Credit card CVV" #> [23] "Credit cards" "Credit status information" #> [25] "Customer feedback" "Customer interactions" #> [27] "Dates of birth" "Deceased date" #> [29] "Deceased statuses" "Device information" #> [31] "Device usage tracking data" "Drinking habits" #> [33] "Drug habits" "Eating habits" #> [35] "Education levels" "Email addresses" #> [37] "Email messages" "Employers" #> [39] "Employment statuses" "Ethnicities" #> [41] "Family members' names" "Family plans" #> [43] "Family structure" "Financial investments" #> [45] "Financial transactions" "Fitness levels" #> [47] "Genders" "Geographic locations" #> [49] "Government issued IDs" "Health insurance information" #> [51] "Historical passwords" "Home loan information" #> [53] "Home ownership statuses" "Homepage URLs" #> [55] "IMEI numbers" "IMSI numbers" #> [57] "Income levels" "Instant messenger identities" #> [59] "IP addresses" "Job titles" #> [61] "MAC addresses" "Marital statuses" #> [63] "Names" "Nationalities" #> [65] "Net worths" "Nicknames" #> [67] "Occupations" "Parenting plans" #> [69] "Partial credit card data" "Passport numbers" #> [71] "Password hints" "Passwords" #> [73] "Payment histories" "Payment methods" #> [75] "Personal descriptions" "Personal health data" #> [77] "Personal interests" "Phone numbers" #> [79] "Photos" "Physical addresses" #> [81] "Physical attributes" "PINs" #> [83] "Political donations" "Political views" #> [85] "Private messages" "Professional skills" #> [87] "Profile photos" "Purchases" #> [89] "Purchasing habits" "Races" #> [91] "Recovery email addresses" "Relationship statuses" #> [93] "Religions" "Reward program balances" #> [95] "Salutations" "School grades (class levels)" #> [97] "Security questions and answers" "Sexual fetishes" #> [99] "Sexual orientations" "Smoking habits" #> [101] "SMS messages" "Social connections" #> [103] "Social media profiles" "Social security numbers" #> [105] "Spoken languages" "Support tickets" #> [107] "Survey results" "Time zones" #> [109] "Travel habits" "User statuses" #> [111] "User website URLs" "Usernames" #> [113] "Utility bills" "Vehicle details" #> [115] "Website activity" "Work habits" #> [117] "Years of birth" "Years of professional experience"