eaglecrestcommunities.com
Aug 4, 2026
Full WordPress database dump from Eagle Crest Communities, a senior living/assisted living organization in La Crosse, Wisconsin. Contains housing applications with PII including full names, addresses, phone numbers, email addresses, dates of birth, and care level information. Also includes WordPress user accounts, form submissions, site configuration, security plugin logs (Wordfence), and audit logs.
Data found in this dataset
Source files
Expand any file to inspect its column headers and the LLM's field-mapping reasoning, recorded during ingestion.
eaglecrestcommunities__wp_gf_entry.csv0 rows
File structure
Format: CSV·Delimiter: Comma·Has header: yes·Quote: "
Notes: All columns are internal system fields (IDs, timestamps, status flags, IP addresses, user agents, payment/transaction data). No PII is present in the first 50 rows. Columns like 'ip' are explicitly excluded per rules (network identifiers are NOT physical addresses). 'created_by' is an internal user ID, not a username or personal identifier.
eaglecrestcommunities__wp_gf_entry_meta.csv122 columns0 rows
File structure
Format: CSV·Delimiter: Comma·Has header: yes·Quote: "
| Source column | Mapped field | Confidence | LLM assessment |
|---|---|---|---|
| 62 | suffix | high | [62] header '1.1' maps to suffix via pattern, values are 'Two', 'One' |
| 63 | suffix | high | [63] header '84.2' maps to suffix via pattern, values are 'Two', 'One' |
| 64 | firstName | high | [64] header '12.3', values are names like 'Winnie' |
| 65 | lastName | high | [65] header '12.6', values are surnames like 'Jaworski' |
| 66 | fullName | high | [66] header '13', values are full names like 'Winnie Jaworski' |
| 67 | address1 | high | [67] header '14.1', values are street addresses like '125 4th Street N, Suite 200' |
| 68 | city | high | [68] header '14.3', values are cities like 'La Crosse' |
| 69 | state | high | [69] header '14.4', values are states like 'Wisconsin' |
| 70 | zip | high | [70] header '14.5', values are ZIP codes like '54601' |
| 71 | country | high | [71] header '14.6', values are countries like 'United States' |
| 72 | skip | high | [72] header '17', values are phone numbers like '(608) 788-5020' |
| 73 | skip | high | [73] header '15', values contain '@' like 'winnie@vendiadvertising.com' |
| 74 | skip | high | [74] header '16', values are dates like '1992-08-28' |
| 75 | gender | high | [75] header '20.2', values are 'Female' |
| 78 | firstName | high | [78] header '88.3', values are names like 'Lydia' |
| 79 | lastName | high | [79] header '88.6', values are surnames like 'Jaworski' |
| 80 | fullName | high | [80] header '89', values are full names like 'Lydia' |
| 81 | address1 | high | [81] header '90.1', values are street addresses like '125 4th Street N, Suite 200' |
| 82 | city | high | [82] header '90.3', values are cities like 'La Crosse' |
| 83 | state | high | [83] header '90.4', values are states like 'Wisconsin' |
| 84 | zip | high | [84] header '90.5', values are ZIP codes like '54601' |
| 85 | country | high | [85] header '90.6', values are countries like 'United States' |
| 86 | skip | high | [86] header '91', values are phone numbers like '(608) 788-5020' |
| 87 | skip | high | [87] header '93', values contain '@' like 'lydia@vendiadvertising.com' |
| 88 | skip | high | [88] header '94', values are dates like '1994-09-05' |
| 90 | gender | high | [90] header '96.2', values are 'Female' |
| 155 | skip | high | [155] header '36', values are phone numbers like '(608) 788-5020' |
| 156 | suffix | high | [156] header '38.5', values are 'Friend' |
| 157 | firstName | high | [157] header '125.3', values are names like 'Lydia' |
| 158 | lastName | high | [158] header '125.6', values are surnames like 'Jaworski' |
| 159 | address1 | high | [159] header '126.1', values are street addresses like '125 4th St N, Suite 200' |
| 160 | city | high | [160] header '126.3', values are cities like 'La Crosse' |
| 161 | state | high | [161] header '126.4', values are states like 'Wisconsin' |
| 162 | zip | high | [162] header '126.5', values are ZIP codes like '54601' |
| 163 | country | high | [163] header '126.6', values are countries like 'United States' |
| 164 | skip | high | [164] header '127', values are phone numbers like '(608) 788-5020' |
| 165 | suffix | high | [165] header '129.3', values are 'Guardian' |
| 167 | suffix | high | [167] header '42.2', values are 'High acuity assisted living' |
| 172 | fullName | high | [172] header '63', values are full names like 'Winnie Jaworski' |
| 174 | skip | high | [174] header '64', values are dates like '2016-03-05' |
| 177 | suffix | high | [177] header '84.1', values are 'One' |
| 178 | firstName | high | [178] header '12.3', values are names like 'Test' |
| 179 | lastName | high | [179] header '12.6', values are surnames like 'Test' |
| 180 | address1 | high | [180] header '14.1', values are addresses like 'Test' |
| 181 | city | high | [181] header '14.3', values are cities like 'test' |
| 182 | state | high | [182] header '14.4', values are states like 'Wisconsin' |
| 183 | zip | high | [183] header '14.5', values are ZIP codes like 'tewt' |
| 184 | country | high | [184] header '14.6', values are countries like 'United States' |
| 185 | skip | high | [185] header '17', values are phone numbers like '(555) 555-5555' |
| 186 | skip | high | [186] header '16', values are dates like '1964-02-01' |
| 187 | gender | high | [187] header '20.1', values are 'Male' |
| 217 | firstName | high | [217] header '34.3', values are names like 'sdfgsgdf' |
| 218 | lastName | high | [218] header '34.6', values are surnames like 'sdfgsdfg' |
| 219 | fullName | high | [219] header '35.1', values are full names like 'sdfgsdfg' |
| 220 | address1 | high | [220] header '35.3', values are addresses like 'adfgsdfg' |
| 221 | city | high | [221] header '35.4', values are cities like 'Wisconsin' |
| 222 | state | high | [222] header '35.5', values are states like 'sdfgsdfg' |
| 223 | country | high | [223] header '35.6', values are countries like 'United States' |
| 224 | skip | high | [224] header '36', values are phone numbers like '(555) 555-5555' |
| 225 | suffix | high | [225] header '38.3', values are 'Guardian' |
| 226 | suffix | high | [226] header '42.1', values are 'Assisted living' |
| 227 | suffix | high | [227] header '52.1', values are 'Social activities' |
| 228 | suffix | high | [228] header '43.1', values are 'The Willows, La Crosse (private pay only)' |
| 229 | suffix | high | [229] header '44.2', values are '1BR' |
| 230 | suffix | high | [230] header '55.1', values are 'Yes' |
| 231 | suffix | high | [231] header '56', values are 'sdfgsdfg' |
| 232 | suffix | high | [232] header '57.1', values are 'Yes' |
| 233 | suffix | high | [233] header '59.1', values are 'Yes' |
| 234 | suffix | high | [234] header '60.1', values are 'Yes' |
| 235 | firstName | high | [235] header '63', values are names like 'sdfgsdfg' |
| 236 | fullName | high | [236] header '66.1', values are full names like 'Self' |
| 237 | skip | high | [237] header '64', values are dates like '2019-03-03' |
| 238 | suffix | high | [238] header '1.1', values are 'Ready list (Given availability of the right apartment/suite, I would be ready within 60 days)' |
| 239 | suffix | high | [239] header '84.2', values are 'Two' |
| 240 | firstName | high | [240] header '12.3', values are names like 'test' |
| 241 | lastName | high | [241] header '12.6', values are surnames like 'test' |
| 242 | address1 | high | [242] header '14.1', values are addresses like 'test' |
| 243 | city | high | [243] header '14.3', values are cities like 'test' |
| 244 | state | high | [244] header '14.4', values are states like 'Wisconsin' |
| 245 | zip | high | [245] header '14.5', values are ZIP codes like 'test' |
| 246 | country | high | [246] header '14.6', values are countries like 'United States' |
| 247 | skip | high | [247] header '17', values are phone numbers like '(555) 555-5555' |
| 248 | skip | high | [248] header '16', values are dates like '2018-04-02' |
| 249 | gender | high | [249] header '20.1', values are 'Male' |
| 250 | firstName | high | [250] header '88.3', values are names like 'test' |
| 251 | lastName | high | [251] header '88.6', values are surnames like 'ste' |
| 252 | fullName | high | [252] header '89', values are full names like 'test' |
| 253 | address1 | high | [253] header '90.1', values are addresses like 'test' |
| 254 | city | high | [254] header '90.3', values are cities like 'test' |
| 255 | state | high | [255] header '90.4', values are states like 'Wisconsin' |
| 256 | zip | high | [256] header '90.5', values are ZIP codes like 'test' |
| 257 | country | high | [257] header '90.6', values are countries like 'United States' |
| 258 | skip | high | [258] header '91', values are phone numbers like '(555) 555-5555' |
| 259 | skip | high | [259] header '94', values are dates like '2018-02-02' |
| 260 | gender | high | [260] header '96.1', values are 'Male' |
| 318 | firstName | high | [318] header '34.3', values are names like 'asdfasdf' |
| 319 | lastName | high | [319] header '34.6', values are surnames like 'asdfasdf' |
| 320 | fullName | high | [320] header '35.1', values are full names like 'asdfasdf' |
| 321 | address1 | high | [321] header '35.3', values are addresses like 'asdfasdf' |
| 322 | city | high | [322] header '35.4', values are cities like 'Wisconsin' |
| 323 | state | high | [323] header '35.5', values are states like 'asdfasdf' |
| 324 | country | high | [324] header '35.6', values are countries like 'United States' |
| 325 | skip | high | [325] header '36', values are phone numbers like '(555) 555-5555' |
| 326 | firstName | high | [326] header '125.3', values are names like 'asdfasdfasdf' |
| 327 | lastName | high | [327] header '125.6', values are surnames like 'asfdasfddsaf' |
| 328 | fullName | high | [328] header '126.1', values are full names like 'asdfdsasdaf' |
| 329 | address1 | high | [329] header '126.3', values are addresses like 'asdfdsa' |
| 330 | city | high | [330] header '126.4', values are cities like 'Wisconsin' |
| 331 | state | high | [331] header '126.5', values are states like 'fadsadsf' |
| 332 | country | high | [332] header '126.6', values are countries like 'United States' |
| 333 | skip | high | [333] header '127', values are phone numbers like '(555) 555-5555' |
| 334 | suffix | high | [334] header '42.2', values are 'High acuity assisted living' |
| 335 | suffix | high | [335] header '52.1', values are 'Social activities' |
| 336 | suffix | high | [336] header '45.1', values are 'Eagle Crest South, La Crosse (private pay only)' |
| 337 | suffix | high | [337] header '46.1', values are 'Studio' |
| 338 | suffix | high | [338] header '55.1', values are 'Yes' |
| 339 | suffix | high | [339] header '57.1', values are 'Yes' |
| 340 | suffix | high | [340] header '59.2', values are 'No' |
| 341 | suffix | high | [341] header '60.2', values are 'No' |
| 342 | firstName | high | [342] header '63', values are names like 'asdfasdf' |
| 343 | fullName | high | [343] header '66.1', values are full names like 'Self' |
| 344 | skip | high | [344] header '64', values are dates like '2018-01-02' |
Notes: 50 rows analyzed, 105 columns present. Mapped 105 PII columns (all appear to contain PII).
eaglecrestcommunities__wp_gf_form.csv0 rows
File structure
Format: CSV·Delimiter: Comma·Has header: yes·Quote: "
Notes: This file appears to be a list of content titles and metadata from a WordPress site. It contains no personal identifiable information (PII). The columns are: id, title, date_created, date_updated, is_active, is_trash. All values are generic content management data and do not map to any PII fields.
eaglecrestcommunities__wp_gf_form_meta.csv69 rows
File structure
Notes: Pre-LLM auto-detection: free-form text with visible emails / phones
eaglecrestcommunities__wp_gf_form_view.csv0 rows
File structure
Format: CSV·Delimiter: Comma·Has header: yes·Quote: "
Notes: This is a log file containing only form submission metadata: form IDs, timestamps, IP addresses, and submission counts. No PII fields (names, emails, addresses, etc.) are present in the visible columns. The 'ip' column contains IP addresses, but these are excluded by policy (network identifiers are not considered PII for this purpose). All columns map to internal IDs, timestamps, or counters — none qualify as personal PII under the defined field types.
eaglecrestcommunities__wp_options.csv3,599 rows
File structure
Notes: Unstructured fallback: no PII columns mapped, but the raw text carries emails
eaglecrestcommunities__wp_postmeta.csv0 rows
File structure
Format: CSV·Delimiter: Comma·Has header: yes·Quote: "
Notes: This file is a WordPress meta data dump (wp_postmeta table). It contains no PII fields. All columns represent metadata keys and values for WordPress posts, with no personal information such as names, addresses, emails, etc. Values are internal IDs, serialized PHP arrays, URLs, and other non-PII data.
eaglecrestcommunities__wp_posts.csv1,662 rows
File structure
Notes: Unstructured fallback: no PII columns mapped, but the raw text carries emails
eaglecrestcommunities__wp_redirection_404.csv782 rows
File structure
Notes: Unstructured fallback: no PII columns mapped, but the raw text carries emails
eaglecrestcommunities__wp_redirection_items.csv0 rows
File structure
Format: CSV·Delimiter: Comma·Has header: yes·Quote: "
Notes: This file contains WordPress redirect configuration data with no personal information. All columns are internal system fields (IDs, URLs, status codes, timestamps). No PII fields detected.
eaglecrestcommunities__wp_redirection_logs.csv825 rows
File structure
Notes: Unstructured fallback: no PII columns mapped, but the raw text carries emails
eaglecrestcommunities__wp_relevanssi.csv0 rows
File structure
Format: CSV·Delimiter: Comma·Has header: yes·Quote: "
Notes: No PII columns detected. All columns appear to be internal WordPress database tracking fields (doc, term, taxonomy, etc.) with no personal data. Values are all zeros or generic status codes.
eaglecrestcommunities__wp_relevanssi_stopwords.csv13 columns0 rows
File structure
Format: CSV·Delimiter: Comma·Has header: yes·Quote: "
| Source column | Mapped field | Confidence | LLM assessment |
|---|---|---|---|
| 0 | firstName | high | Column 0 header is 'first_name', values are common given names like 'John', 'Mary' |
| 1 | lastName | high | Column 1 header is 'last_name', values are common surnames like 'Smith', 'Johnson' |
| 2 | skip | high | Column 2 header is 'date_of_birth', values match date format like '1980-05-15' |
| 3 | skip | high | Column 3 header is 'phone_number', values are 10-digit numbers like '6505550199' |
| 4 | skip | high | Column 4 header is 'email_address', values contain '@' like 'john.smith@example.com' |
| 5 | address1 | high | Column 5 header is 'address_line_1', values are street addresses like '123 Main St' |
| 6 | city | high | Column 6 header is 'city', values are city names like 'La Crosse' |
| 7 | state | high | Column 7 header is 'state', values are state abbreviations like 'WI' |
| 8 | zip | high | Column 8 header is 'zip_code', values are 5-digit ZIP codes like '54601' |
| 9 | username | high | Column 9 header is 'user_login', values are usernames like 'johnsmith' |
| 10 | password | high | Column 10 header is 'user_pass', values appear to be hashed passwords |
| 11 | gender | high | Column 11 header is 'gender', values are 'M' or 'F' |
| 12 | suffix | medium | Column 12 header is 'suffix', values are generational suffixes like 'Jr', 'Sr' |
Notes: 12 PII columns identified. File appears to be a standard CSV export from a WordPress database with housing application data. Columns 0-8 contain applicant personal information, columns 9-12 contain WordPress user account details.
eaglecrestcommunities__wp_responsive_menu.csv0 rows
File structure
Notes: File is a WordPress configuration/settings dump (name/value pairs). No consistent columnar structure exists; values are configuration parameters and JSON strings, not PII. Contains no importable data rows.
eaglecrestcommunities__wp_rg_form.csv0 rows
File structure
Format: CSV·Delimiter: Comma·Has header: yes·Quote: "
Notes: This is a structured CSV file, but the visible columns (id, title, date_created, is_active, is_trash) contain only internal identifiers and timestamps. No PII is present in the first 50 rows. Additional rows may contain PII, but based on the header and sample values provided, no columns map to PII fields. The file appears to be a list of content types or post statuses, not user data.
eaglecrestcommunities__wp_rg_form_meta.csv37 rows
File structure
Notes: Pre-LLM auto-detection: free-form text with visible emails / phones
eaglecrestcommunities__wp_rg_form_view.csv0 rows
File structure
Format: CSV·Delimiter: Comma·Has header: yes·Quote: "
Notes: This is a WordPress form submissions log containing only internal IDs, form IDs, timestamps, and submission counts. No PII fields present. All columns are internal tracking identifiers or timestamps which must be skipped per exclusion rules.
eaglecrestcommunities__wp_rg_lead.csv0 rows
File structure
Format: CSV·Delimiter: Comma·Has header: yes·Quote: "
Notes: All columns contain internal system identifiers, timestamps, IP addresses, or status flags. No PII fields are present in this dataset. Columns like 'ip' are network identifiers (explicitly excluded), and all others are internal IDs, timestamps, or status codes.
eaglecrestcommunities__wp_rg_lead_detail.csv125 columns0 rows
File structure
Format: CSV·Delimiter: Comma·Has header: yes·Quote: "
| Source column | Mapped field | Confidence | LLM assessment |
|---|---|---|---|
| 62 | fullName | high | [62] field_number 1.1 maps to fullName via context: contains full names like 'Winnie Jaworski' |
| 63 | suffix | high | [63] field_number 84.2 maps to suffix via context: contains values like 'Two', 'One' indicating name suffix |
| 64 | firstName | high | [64] field_number 12.3 maps to firstName via context: contains first names like 'Winnie', 'Lydia', 'Test' |
| 65 | lastName | high | [65] field_number 12.6 maps to lastName via context: contains last names like 'Jaworski', 'Test' |
| 66 | address1 | high | [66] field_number 14.1 maps to address1 via context: contains street addresses like '125 4th Street N, Suite 200' |
| 67 | city | high | [67] field_number 14.3 maps to city via context: contains city names like 'La Crosse', 'test' |
| 68 | state | high | [68] field_number 14.4 maps to state via context: contains state names like 'Wisconsin', 'test' |
| 69 | zip | high | [69] field_number 14.5 maps to zip via context: contains ZIP codes like '54601', 'tewt' |
| 70 | country | high | [70] field_number 14.6 maps to country via context: contains country names like 'United States' |
| 71 | skip | high | [71] field_number 17 maps to phone via context: contains phone numbers like '(608) 788-5020', '(555) 555-5555' |
| 72 | skip | high | [72] field_number 16 maps to email via context: contains email addresses like 'winnie@vendiadvertising.com', 'lydia@vendiadvertising.com' |
| 73 | skip | high | [73] field_number 15 maps to dob via context: contains dates of birth like '1992-08-28', '1994-09-05', '1964-02-01', '2018-04-02', '2018-02-02', '2019-03-03', '2018-01-02', '2016-03-05' |
| 75 | gender | high | [75] field_number 20.2 maps to gender via context: contains gender values like 'Female' |
| 78 | firstName | high | [78] field_number 88.3 maps to firstName via context: contains first names like 'Lydia', 'Test', 'asdfasdf', 'asdfasdfasdf' |
| 79 | lastName | high | [79] field_number 88.6 maps to lastName via context: contains last names like 'Jaworski', 'ste', 'asfdasfddsaf', 'asfdasfddsaf' |
| 80 | fullName | high | [80] field_number 89 maps to fullName via context: contains full names like 'Lydia', 'asdfasdfasdf' |
| 81 | address1 | high | [81] field_number 90.1 maps to address1 via context: contains street addresses like '125 4th Street N, Suite 200', 'asdfdsasdaf' |
| 82 | city | high | [82] field_number 90.3 maps to city via context: contains city names like 'La Crosse', 'asdfdsa' |
| 83 | state | high | [83] field_number 90.4 maps to state via context: contains state names like 'Wisconsin' |
| 84 | zip | high | [84] field_number 90.5 maps to zip via context: contains ZIP codes like '54601', 'test' |
| 85 | country | high | [85] field_number 90.6 maps to country via context: contains country names like 'United States' |
| 86 | skip | high | [86] field_number 91 maps to phone via context: contains phone numbers like '(608) 788-5020', '(555) 555-5555' |
| 87 | skip | high | [87] field_number 93 maps to email via context: contains email addresses like 'lydia@vendiadvertising.com' |
| 88 | skip | high | [88] field_number 94 maps to dob via context: contains dates of birth like '1994-09-05', '2018-02-02', '2019-03-03', '2018-01-02' |
| 90 | gender | high | [90] field_number 96.2 maps to gender via context: contains gender values like 'Female', 'Male' |
| 148 | firstName | high | [148] field_number 34.3 maps to firstName via context: contains first names like 'Winnie', 'sdfgsgdf', 'asdfasdf', 'asdfasdf' |
| 149 | lastName | high | [149] field_number 34.6 maps to lastName via context: contains last names like 'Jaworski', 'sdfgsdfg', 'asdfasdf', 'asdfasdf' |
| 150 | address1 | high | [150] field_number 35.1 maps to address1 via context: contains street addresses like '125 4th St N, Suite 200', 'asdfasdf', 'asdfasdf' |
| 151 | city | high | [151] field_number 35.3 maps to city via context: contains city names like 'La Crosse', 'adfgsdfg', 'asdfdsa' |
| 152 | state | high | [152] field_number 35.4 maps to state via context: contains state names like 'Wisconsin' |
| 153 | zip | high | [153] field_number 35.5 maps to zip via context: contains ZIP codes like '54601', 'sdfgsdfg', 'fadsadsf' |
| 154 | country | high | [154] field_number 35.6 maps to country via context: contains country names like 'United States' |
| 155 | skip | high | [155] field_number 36 maps to phone via context: contains phone numbers like '(608) 788-5020', '(555) 555-5555' |
| 157 | firstName | high | [157] field_number 125.3 maps to firstName via context: contains first names like 'Lydia', 'asdfasdfasdf' |
| 158 | lastName | high | [158] field_number 125.6 maps to lastName via context: contains last names like 'Jaworski', 'asfdasfddsaf' |
| 159 | address1 | high | [159] field_number 126.1 maps to address1 via context: contains street addresses like '125 4th St N, Suite 200', 'asdfdsasdaf' |
| 160 | city | high | [160] field_number 126.3 maps to city via context: contains city names like 'La Crosse', 'asdfdsa' |
| 161 | state | high | [161] field_number 126.4 maps to state via context: contains state names like 'Wisconsin' |
| 162 | zip | high | [162] field_number 126.5 maps to zip via context: contains ZIP codes like '54601', 'fadsadsf' |
| 163 | country | high | [163] field_number 126.6 maps to country via context: contains country names like 'United States' |
| 164 | skip | high | [164] field_number 127 maps to phone via context: contains phone numbers like '(608) 788-5020', '(555) 555-5555' |
| 172 | fullName | high | [172] field_number 63 maps to fullName via context: contains full names like 'Winnie Jaworski' |
| 173 | suffix | high | [173] field_number 66.1 maps to suffix via context: contains values like 'Self', 'Guardian' |
| 174 | skip | high | [174] field_number 64 maps to dob via context: contains dates of birth like '2016-03-05', '2019-03-03', '2018-01-02' |
| 175 | fullName | high | [175] field_number 1.1 maps to fullName via context: contains full names like 'Ready list (Given availability of the right apartment/suite, I would be ready within 60 days)' |
| 176 | suffix | high | [176] field_number 84.1 maps to suffix via context: contains values like 'One', 'Two' |
| 177 | firstName | high | [177] field_number 12.3 maps to firstName via context: contains first names like 'Test', 'test', 'asdfasdf' |
| 178 | lastName | high | [178] field_number 12.6 maps to lastName via context: contains last names like 'Test', 'test', 'asdfasdf' |
| 179 | address1 | high | [179] field_number 14.1 maps to address1 via context: contains street addresses like 'Test' |
| 180 | city | high | [180] field_number 14.3 maps to city via context: contains city names like 'test' |
| 181 | state | high | [181] field_number 14.4 maps to state via context: contains state names like 'Wisconsin' |
| 182 | zip | high | [182] field_number 14.5 maps to zip via context: contains ZIP codes like 'tewt' |
| 183 | country | high | [183] field_number 14.6 maps to country via context: contains country names like 'United States' |
| 184 | skip | high | [184] field_number 17 maps to phone via context: contains phone numbers like '(555) 555-5555' |
| 185 | skip | high | [185] field_number 16 maps to dob via context: contains dates of birth like '1964-02-01', '2018-04-02' |
| 187 | gender | high | [187] field_number 20.1 maps to gender via context: contains gender values like 'Male' |
| 217 | firstName | high | [217] field_number 34.3 maps to firstName via context: contains first names like 'sdfgsgdf', 'asdfasdf', 'asdfasdf' |
| 218 | lastName | high | [218] field_number 34.6 maps to lastName via context: contains last names like 'sdfgsdfg', 'asdfasdf', 'asddfasdf' |
| 219 | address1 | high | [219] field_number 35.1 maps to address1 via context: contains street addresses like 'asdfasdf', 'asdfasdf' |
| 220 | city | high | [220] field_number 35.3 maps to city via context: contains city names like 'adfgsdfg', 'asdfdsa' |
| 221 | state | high | [221] field_number 35.4 maps to state via context: contains state names like 'Wisconsin' |
| 222 | zip | high | [222] field_number 35.5 maps to zip via context: contains ZIP codes like 'sdfgsdfg', 'fadsadsf' |
| 223 | country | high | [223] field_number 35.6 maps to country via context: contains country names like 'United States' |
| 224 | skip | high | [224] field_number 36 maps to phone via context: contains phone numbers like '(555) 555-5555' |
| 225 | suffix | high | [225] field_number 38.3 maps to suffix via context: contains values like 'Guardian' |
| 226 | suffix | high | [226] field_number 42.1 maps to suffix via context: contains values like 'Assisted living', 'High acuity assisted living' |
| 227 | suffix | high | [227] field_number 52.1 maps to suffix via context: contains values like 'Social activities' |
| 228 | address1 | high | [228] field_number 45.1 maps to address1 via context: contains street addresses like 'The Willows, La Crosse (private pay only)' |
| 231 | firstName | high | [231] field_number 56 maps to firstName via context: contains first names like 'sdfgsdfg' |
| 232 | gender | high | [232] field_number 57.1 maps to gender via context: contains gender values like 'Yes', 'No' |
| 233 | gender | high | [233] field_number 59.1 maps to gender via context: contains gender values like 'Yes', 'No' |
| 234 | gender | high | [234] field_number 60.1 maps to gender via context: contains gender values like 'Yes', 'No' |
| 235 | firstName | high | [235] field_number 63 maps to firstName via context: contains first names like 'sdfgsdfg', 'asdfasdf' |
| 236 | suffix | high | [236] field_number 66.1 maps to suffix via context: contains values like 'Self', 'Guardian' |
| 237 | skip | high | [237] field_number 64 maps to dob via context: contains dates of birth like '2019-03-03', '2018-01-02' |
| 238 | fullName | high | [238] field_number 1.1 maps to fullName via context: contains full names like 'Ready list (Given availability of the right apartment/suite, I would be ready within 60 days)' |
| 239 | suffix | high | [239] field_number 84.2 maps to suffix via context: contains values like 'Two' |
| 240 | firstName | high | [240] field_number 12.3 maps to firstName via context: contains first names like 'test', 'asdfasdf' |
| 241 | lastName | high | [241] field_number 12.6 maps to lastName via context: contains last names like 'test', 'asdfasdf' |
| 242 | address1 | high | [242] field_number 14.1 maps to address1 via context: contains street addresses like 'test' |
| 243 | city | high | [243] field_number 14.3 maps to city via context: contains city names like 'test' |
| 244 | state | high | [244] field_number 14.4 maps to state via context: contains state names like 'Wisconsin' |
| 245 | zip | high | [245] field_number 14.5 maps to zip via context: contains ZIP codes like 'test' |
| 246 | country | high | [246] field_number 14.6 maps to country via context: contains country names like 'United States' |
| 247 | skip | high | [247] field_number 17 maps to phone via context: contains phone numbers like '(555) 555-5555' |
| 248 | skip | high | [248] field_number 16 maps to dob via context: contains dates of birth like '2018-04-02' |
| 250 | gender | high | [250] field_number 20.1 maps to gender via context: contains gender values like 'Male' |
| 253 | firstName | high | [253] field_number 88.3 maps to firstName via context: contains first names like 'test', 'asdfasdf', 'asdfasdfasdf' |
| 254 | lastName | high | [254] field_number 88.6 maps to lastName via context: contains last names like 'ste', 'asfdasfddsaf', 'asfdasfddsaf' |
| 255 | address1 | high | [255] field_number 90.1 maps to address1 via context: contains street addresses like 'test', 'asdfdsasdaf', 'asdfdsasdaf' |
| 256 | city | high | [256] field_number 90.3 maps to city via context: contains city names like 'test', 'asdfdsa' |
| 257 | state | high | [257] field_number 90.4 maps to state via context: contains state names like 'Wisconsin' |
| 258 | zip | high | [258] field_number 90.5 maps to zip via context: contains ZIP codes like 'test', 'fadsadsf' |
| 259 | country | high | [259] field_number 90.6 maps to country via context: contains country names like 'United States' |
| 260 | skip | high | [260] field_number 91 maps to phone via context: contains phone numbers like '(555) 555-5555' |
| 261 | skip | high | [261] field_number 94 maps to dob via context: contains dates of birth like '2018-02-02' |
| 263 | gender | high | [263] field_number 96.1 maps to gender via context: contains gender values like 'Male' |
| 318 | firstName | high | [318] field_number 34.3 maps to firstName via context: contains first names like 'asdfasdf', 'asdfasdf', 'asdfasdf' |
| 319 | lastName | high | [319] field_number 34.6 maps to lastName via context: contains last names like 'asdfasdf', 'asdfasdf', 'asddfasdf' |
| 320 | address1 | high | [320] field_number 35.1 maps to address1 via context: contains street addresses like 'asdfasdf', 'asdfasdf', 'asdfasdf' |
| 321 | city | high | [321] field_number 35.3 maps to city via context: contains city names like 'asdfasdf', 'asdfdsa', 'asdfdsa' |
| 322 | state | high | [322] field_number 35.4 maps to state via context: contains state names like 'Wisconsin' |
| 323 | zip | high | [323] field_number 35.5 maps to zip via context: contains ZIP codes like 'asdfasdf', 'fadsadsf' |
| 324 | country | high | [324] field_number 35.6 maps to country via context: contains country names like 'United States' |
| 325 | skip | high | [325] field_number 36 maps to phone via context: contains phone numbers like '(555) 555-5555' |
| 326 | firstName | high | [326] field_number 125.3 maps to firstName via context: contains first names like 'asdfasdfasdf', 'asdfdsasdaf', 'asdfdsasdaf' |
| 327 | lastName | high | [327] field_number 125.6 maps to lastName via context: contains last names like 'asfdasfddsaf', 'fadsadsf' |
| 328 | address1 | high | [328] field_number 126.1 maps to address1 via context: contains street addresses like 'asdfdsasdaf', 'asdfdsasdaf' |
| 329 | city | high | [329] field_number 126.3 maps to city via context: contains city names like 'asdfdsa', 'asdfdsa' |
| 330 | state | high | [330] field_number 126.4 maps to state via context: contains state names like 'Wisconsin' |
| 331 | zip | high | [331] field_number 126.5 maps to zip via context: contains ZIP codes like 'fadsadsf' |
| 332 | country | high | [332] field_number 126.6 maps to country via context: contains country names like 'United States' |
| 333 | skip | high | [333] field_number 127 maps to phone via context: contains phone numbers like '(555) 555-5555' |
| 334 | suffix | high | [334] field_number 42.2 maps to suffix via context: contains values like 'High acuity assisted living' |
| 335 | suffix | high | [335] field_number 52.1 maps to suffix via context: contains values like 'Social activities' |
| 336 | address1 | high | [336] field_number 45.1 maps to address1 via context: contains street addresses like 'Eagle Crest South, La Crosse (private pay only)' |
| 337 | suffix | high | [337] field_number 46.1 maps to suffix via context: contains values like 'Studio', '1BR' |
| 338 | gender | high | [338] field_number 55.1 maps to gender via context: contains gender values like 'Yes', 'No' |
| 339 | gender | high | [339] field_number 57.1 maps to gender via context: contains gender values like 'Yes', 'No' |
| 340 | gender | high | [340] field_number 59.2 maps to gender via context: contains gender values like 'No' |
| 341 | gender | high | [341] field_number 60.2 maps to gender via context: contains gender values like 'No' |
| 342 | firstName | high | [342] field_number 63 maps to firstName via context: contains first names like 'asdfasdf', 'asdfasdf' |
| 343 | suffix | high | [343] field_number 66.1 maps to suffix via context: contains values like 'Self', 'Guardian' |
| 344 | skip | high | [344] field_number 64 maps to dob via context: contains dates of birth like '2018-01-02' |
| 345 | id | high | [345] header is 'id', values are sequential integers (10,6) - this is an internal identifier, not PII |
Notes: Total columns: 345 (0-based indexing), PII columns: 97. This is a WordPress form submission data dump from Eagle Crest Communities containing housing applications with PII including full names, addresses, phone numbers, email addresses, dates of birth, and care level information. Some fields appear to be duplicated across multiple submissions (e.g., address1 appears in fields 66, 81, 150, 219, 255, 320, 328). Gender fields appear in multiple formats (Yes/No, Male/Female). Suffix fields contain care level information (e.g., 'Studio', '1BR', 'High acuity assisted living').
eaglecrestcommunities__wp_term_relationships.csv0 rows
File structure
Format: CSV·Delimiter: Comma·Has header: yes·Quote: "
Notes: This file is a simple term relationship table with only numeric IDs and taxonomy relationships. No PII fields are present. All columns are internal identifiers and taxonomy references, which must be skipped per exclusion rules.
eaglecrestcommunities__wp_term_taxonomy.csv0 rows
File structure
Format: CSV·Delimiter: Comma·Has header: yes·Quote: "
Notes: This is a taxonomy table from a WordPress database dump. Contains only taxonomy terms and descriptions, no PII fields present. All columns are internal taxonomy identifiers, names, and descriptive text.
eaglecrestcommunities__wp_termmeta.csv0 rows
File structure
Format: CSV·Delimiter: Comma·Has header: yes·Quote: "
Notes: This is a WordPress meta table dump with no actual PII columns. All fields are internal WordPress metadata IDs, term IDs, and feature image references. No personal information is present in this sample.
eaglecrestcommunities__wp_terms.csv0 rows
File structure
Format: CSV·Delimiter: Comma·Has header: yes·Quote: "
Notes: This file contains taxonomy/term data from WordPress (categories/tags). No personal identifiable information (PII) is present. Columns represent term IDs, names, slugs, grouping, and ordering — all internal site structure. No mapping to PII fields required.
eaglecrestcommunities__wp_usermeta.csv1 column11 rows
File structure
Format: CSV·Delimiter: Comma·Has header: yes·Quote: "
| Source column | Mapped field | Confidence | LLM assessment |
|---|---|---|---|
| 3 | low | [3] meta_value contains email addresses when meta_key='nickname' (e.g. cj@vendiadvertising.com), but also contains non-PII values for other meta_keys — EAV table requires unpivoting |
Notes: WordPress wp_usermeta EAV table. PII is encoded as meta_key/meta_value pairs, not dedicated columns. meta_key='nickname' holds email, 'first_name' holds firstName, 'last_name' holds lastName — all in the same meta_value column (index 3). Standard column mapping cannot fully capture this; EAV unpivoting is required. Only email is confidently visible in the sample; first_name and last_name rows are empty in these 50 rows.
eaglecrestcommunities__wp_users.csv4 columns11 rows
File structure
Format: CSV·Delimiter: Comma·Has header: yes·Quote: "
| Source column | Mapped field | Confidence | LLM assessment |
|---|---|---|---|
| 1 | username | high | header "user_login" resolves to PII field "username" |
| 2 | password | high | header "user_pass" resolves to PII field "password" |
| 4 | high | header "user_email" resolves to PII field "email" | |
| 9 | fullName | high | header "display_name" resolves to PII field "fullName" |
Notes: Heuristic auto-detection: header-named PII columns confirmed by data conformance
eaglecrestcommunities__wp_wfBlockedIPLog.csv0 rows
File structure
Format: CSV·Delimiter: Comma·Has header: yes·Quote: "
Notes: This file contains WordPress security logs (Wordfence) showing IP addresses, country codes, block counts, timestamps, and block types. No PII is present; all columns are system/internal identifiers, network data, or security metadata. Per exclusion rules, IP addresses are skipped. No personal data (names, emails, addresses, etc.) is visible.
eaglecrestcommunities__wp_wfConfig.csv0 rows
File structure
Format: CSV·Delimiter: Comma·Has header: yes·Quote: "
Notes: This is a WordPress wp_options / Wordfence configuration table dump. All rows are key-value configuration pairs (name, val, autoload) — internal plugin settings, security scan flags, hex-encoded configuration blobs, and system metadata. There are no PII columns in this file. The 'name' column contains configuration key names and 'val' contains hex-encoded configuration values; neither represents personal information fields like names, emails, addresses, or dates of birth.
eaglecrestcommunities__wp_wfCrawlers.csv0 rows
File structure
Notes: free-form text with embedded IPs, not structured columns
eaglecrestcommunities__wp_wfFileMods.csv36 rows
File structure
Notes: Unstructured fallback: no PII columns mapped, but the raw text carries emails
eaglecrestcommunities__wp_wfHits.csv2,093 rows
File structure
Notes: Unstructured fallback: no PII columns mapped, but the raw text carries emails
eaglecrestcommunities__wp_wfIssues.csv0 rows
File structure
Format: CSV·Delimiter: Comma·Has header: yes·Quote: "
Notes: This is a WordPress security plugin log (Wordfence) containing internal tracking IDs, timestamps, and plugin status messages. No PII fields are present. Columns are: id (internal record ID), time (timestamp), lastUpdated (timestamp), status (string status), type (plugin event type), severity (numeric level), ignoreP (hash), ignoreC (hash), shortMsg (message snippet), longMsg (detailed message), data (serialized plugin data). All columns are internal system data or encrypted hashes — no personal information exposed.
eaglecrestcommunities__wp_wfKnownFileList.csv36 rows
File structure
Notes: The provided data is a list of file paths and IDs from a WordPress database dump, not a structured dataset containing PII. Each line represents a file entry (id,path) and does not contain any personal information such as names, addresses, emails, etc. Therefore, there are no PII columns to map.
eaglecrestcommunities__wp_wfLiveTrafficHuman.csv3 columns0 rows
File structure
Format: CSV·Delimiter: Comma·Has header: yes·Quote: "
| Source column | Mapped field | Confidence | LLM assessment |
|---|---|---|---|
| 0 | skip | high | column contains internal IP addresses, not physical addresses |
| 1 | skip | high | column contains cryptographic hashes, not passwords or usernames |
| 2 | skip | high | column contains Unix timestamps, not dates of birth |
Notes: This is a WordPress security log (Wordfence) containing IP addresses, cryptographic hashes, and timestamps. No PII fields are present in this dataset.
eaglecrestcommunities__wp_wfLogins.csv1 column105 rows
File structure
Format: CSV·Delimiter: Comma·Has header: yes·Quote: "
| Source column | Mapped field | Confidence | LLM assessment |
|---|---|---|---|
| 5 | username | high | [5] column 'username', values include 'admin', 'shop', 'test' |
Notes: Only username column contains PII. Other columns are internal IDs, timestamps, status flags, IP addresses, and user agents which are excluded by rules.
eaglecrestcommunities__wp_wfNotifications.csv0 rows
File structure
Format: CSV·Delimiter: Comma·Has header: yes·Quote: "
Notes: This file contains WordPress security plugin logs and update notifications. It consists of site identifiers, timestamps, categories, and HTML links to admin pages. No PII is present — all entries are system-generated alerts about Wordfence scans and plugin/theme updates. The values are static strings and site IDs, not personal data.
eaglecrestcommunities__wp_wfReverseCache.csv0 rows
File structure
Format: CSV·Delimiter: Comma·Has header: yes·Quote: "
Notes: This file contains Wordfence security plugin IP/host logs (crawler/bot entries from Google). All three columns are non-PII: IP (hex-encoded network addresses), host (bot hostnames), and lastUpdate (Unix timestamps). No personal PII is present.
eaglecrestcommunities__wp_wfStatus.csv0 rows
File structure
Format: CSV·Delimiter: Comma·Has header: yes·Quote: "
Notes: The provided data is a log file from Wordfence security scanning, not a delimited dataset containing PII. It records scan timestamps, file counts, and system performance metrics. No personal information (names, emails, addresses, etc.) is present in these structured log entries. The format is CSV but contains no PII fields.
eaglecrestcommunities__wp_wfls_settings.csv0 rows
File structure
Format: CSV·Delimiter: Comma·Has header: yes·Quote: "
Notes: This is a WordPress configuration/options table dump (wp_options). All rows are site settings key-value pairs, not user PII. No personal identifiable information is present in this structured data.
eaglecrestcommunities__wp_wow_mwp.csv2 rows
File structure
Notes: The file appears to be a serialized PHP array dump (likely from a WordPress options table) rather than structured CSV data. It contains configuration parameters for a popup modal rather than user PII. No consistent columnar structure exists — all rows are different key-value pairs within a serialized string. While this is a database dump from Eagle Crest Communities, this particular file does not contain any actual resident PII records.
eaglecrestcommunities__wp_wsal_metadata.csv38,013 rows
File structure
Notes: Unstructured fallback: no PII columns mapped, but the raw text carries emails
eaglecrestcommunities__wp_wsal_occurrences.csv0 rows
File structure
Format: CSV·Delimiter: Comma·Has header: yes·Quote: "
Notes: This is a log table with only numeric IDs, timestamps, and status flags. No PII present. Columns: id (internal ID), site_id (internal ID), alert_id (internal ID), created_on (timestamp), is_read (flag), is_migrated (flag).
eaglecrestcommunities__wp_wsal_options.csv0 rows
File structure
Format: CSV·Delimiter: Comma·Has header: yes·Quote: "
Notes: This file contains WordPress site options (wp_options table dump) with no personal identifiable information. All values are system configuration strings, hashes, and serialized arrays of plugin settings. No PII fields detected.
eaglecrestcommunities__wp_yoast_seo_links.csv0 rows
File structure
Format: CSV·Delimiter: Comma·Has header: yes·Quote: "
Notes: This file appears to be a list of URLs and internal/external links, not containing any personal identifiable information (PII). The columns represent IDs, URLs, post IDs, target post IDs, and types of links. There are no fields that map to PII such as names, addresses, emails, phone numbers, dates of birth, etc. Therefore, no columns are mapped to PII fields.
eaglecrestcommunities__wp_yoast_seo_meta.csv0 rows
File structure
Format: CSV·Delimiter: Comma·Has header: yes·Quote: "
Notes: This is a WordPress database dump showing only internal link counts and object IDs. No PII fields are present in this sample.