Known data leaks
Identifying all data breaches is impossible, although organizations are now required to notify their communities (customers, patients, employees, etc.) when it happens. Leaks (or breaches in English) are generally due to human error or hacking of computer systems. The results presented here come from haveibeenpwned.com ( was I auctioned off on the dark web ...), a reference in the field, which searches the hidden web for us. All these data are for sale on the web ...
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breach logo
Leak title
breach Title
Domain name
breach Domain
Date of the leak
breach Date
Volume
Number
Data types
breach Data
Description
breach Description
Connections
breach Links
It's your data and anyone can use it
On the web, we find everything we want to buy, our data is no exception. From our identities to our political opinions, including our bank card numbers, our accounts and passwords, our photos, our medical records, or even our sexual preferences. The list is long and in English.
Index | Data |
|---|---|
1 | Account balances |
2 | Address book contacts |
3 | Age groups |
4 | Ages |
5 | Apps installed on devices |
6 | Astrological signs |
7 | Audio recordings |
8 | Auth tokens |
9 | Avatars |
10 | Bank account numbers |
11 | Beauty ratings |
12 | Biometric data |
13 | Bios |
14 | Browser user agent details |
15 | Browsing histories |
16 | Buying preferences |
17 | Car ownership statuses |
18 | Career levels |
19 | Cellular network names |
20 | Charitable donations |
21 | Chat logs |
22 | Credit card CVV |
23 | Credit cards |
24 | Credit status information |
25 | Customer feedback |
26 | Customer interactions |
27 | Dates of birth |
28 | Deceased date |
29 | Deceased statuses |
30 | Device information |
31 | Device serial numbers |
32 | Device usage tracking data |
33 | Drinking habits |
34 | Driver's licenses |
35 | Drug habits |
36 | Eating habits |
37 | Education levels |
38 | Email addresses |
39 | Email messages |
40 | Employers |
41 | Employment statuses |
42 | Encrypted keys |
43 | Ethnicities |
44 | Family members' names |
45 | Family plans |
46 | Family structure |
47 | Financial investments |
48 | Financial transactions |
49 | Fitness levels |
50 | Genders |
51 | Geographic locations |
52 | Government issued IDs |
53 | Health insurance information |
54 | Historical passwords |
55 | Home loan information |
56 | Home ownership statuses |
57 | Homepage URLs |
58 | IMEI numbers |
59 | IMSI numbers |
60 | Income levels |
61 | Instant messenger identities |
62 | IP addresses |
63 | Job applications |
64 | Job titles |
65 | Licence plates |
66 | Living costs |
67 | Login histories |
68 | MAC addresses |
69 | Marital statuses |
70 | Mnemonic phrases |
71 | Mothers maiden names |
72 | Names |
73 | Nationalities |
74 | Net worths |
75 | Nicknames |
76 | Occupations |
77 | Parenting plans |
78 | Partial credit card data |
79 | Partial dates of birth |
80 | Passport numbers |
81 | Password hints |
82 | Password strengths |
83 | Passwords |
84 | Payment histories |
85 | Payment methods |
86 | Personal descriptions |
87 | Personal health data |
88 | Personal interests |
89 | Phone numbers |
90 | Photos |
91 | Physical addresses |
92 | Physical attributes |
93 | PINs |
94 | Places of birth |
95 | Political donations |
96 | Political views |
97 | Private messages |
98 | Professional skills |
99 | Profile photos |
100 | Purchases |
101 | Purchasing habits |
102 | Races |
103 | Recovery email addresses |
104 | Relationship statuses |
105 | Religions |
106 | Reward program balances |
107 | Salutations |
108 | School grades (class levels) |
109 | Security questions and answers |
110 | Sexual fetishes |
111 | Sexual orientations |
112 | Smoking habits |
113 | SMS messages |
114 | Social connections |
115 | Social media profiles |
116 | Social security numbers |
117 | Spoken languages |
118 | Spouses names |
119 | Support tickets |
120 | Survey results |
121 | Taxation records |
122 | Time zones |
123 | Travel habits |
124 | User statuses |
125 | User website URLs |
126 | Usernames |
127 | Utility bills |
128 | Vehicle details |
129 | Website activity |
130 | Work habits |
131 | Years of professional experience |