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/* This Source Code Form is subject to the terms of the Mozilla Public
* License, v. 2.0. If a copy of the MPL was not distributed with this
/**
* Provides a class to import login-related data CSV files.
*/
const lazy = {};
ChromeUtils.defineESModuleGetters(lazy, {
CSV: "resource://gre/modules/CSV.sys.mjs",
LoginHelper: "resource://gre/modules/LoginHelper.sys.mjs",
});
/**
* All the CSV column names will be converted to lower case before lookup
* so they must be specified here in lower case.
*/
const FIELD_TO_CSV_COLUMNS = {
origin: ["url", "login_uri"],
username: ["username", "login_username"],
password: ["password", "login_password"],
httpRealm: ["httprealm"],
formActionOrigin: ["formactionorigin"],
guid: ["guid"],
timeCreated: ["timecreated"],
timeLastUsed: ["timelastused"],
timePasswordChanged: ["timepasswordchanged"],
};
export const ImportFailedErrorType = Object.freeze({
CONFLICTING_VALUES_ERROR: "CONFLICTING_VALUES_ERROR",
FILE_FORMAT_ERROR: "FILE_FORMAT_ERROR",
FILE_PERMISSIONS_ERROR: "FILE_PERMISSIONS_ERROR",
UNABLE_TO_READ_ERROR: "UNABLE_TO_READ_ERROR",
});
export class ImportFailedException extends Error {
constructor(errorType, message) {
super(message != null ? message : errorType);
this.errorType = errorType;
}
}
/**
* Provides an object that has a method to import login-related data CSV files
*/
export class LoginCSVImport {
/**
* Returns a map that has the csv column name as key and the value the field name.
*
* @returns {Map} A map that has the csv column name as key and the value the field name.
*/
static _getCSVColumnToFieldMap() {
let csvColumnToField = new Map();
for (let [field, columns] of Object.entries(FIELD_TO_CSV_COLUMNS)) {
for (let column of columns) {
csvColumnToField.set(column.toLowerCase(), field);
}
}
return csvColumnToField;
}
/**
* Builds a vanilla JS object containing all the login fields from a row of CSV cells.
*
* @param {object} csvObject
* An object created from a csv row. The keys are the csv column names, the values are the cells.
* @param {Map} csvColumnToFieldMap
* A map where the keys are the csv properties and the values are the object keys.
* @returns {object} Representing login object with only properties, not functions.
*/
static _getVanillaLoginFromCSVObject(csvObject, csvColumnToFieldMap) {
let vanillaLogin = Object.create(null);
for (let columnName of Object.keys(csvObject)) {
let fieldName = csvColumnToFieldMap.get(columnName.toLowerCase());
if (!fieldName) {
continue;
}
if (
typeof vanillaLogin[fieldName] != "undefined" &&
vanillaLogin[fieldName] !== csvObject[columnName]
) {
// Differing column values map to one property.
// e.g. if two headings map to `origin` we won't know which to use.
return {};
}
vanillaLogin[fieldName] = csvObject[columnName];
}
// Since `null` can't be represented in a CSV file and the httpRealm header
// cannot be an empty string, assume that an empty httpRealm means this is
// a form login and therefore null-out httpRealm.
if (vanillaLogin.httpRealm === "") {
vanillaLogin.httpRealm = null;
}
return vanillaLogin;
}
static _recordHistogramTelemetry(histogram, report) {
for (let reportRow of report) {
let { result } = reportRow;
if (result.includes("error")) {
histogram.add("error");
} else {
histogram.add(result);
}
}
}
/**
* Imports logins from a CSV file (comma-separated values file).
* Existing logins may be updated in the process.
*
* @param {string} filePath
* @returns {Object[]} An array of rows where each is mapped to a row in the CSV and it's import information.
*/
static async importFromCSV(filePath) {
let csvColumnToFieldMap = LoginCSVImport._getCSVColumnToFieldMap();
let csvFieldToColumnMap = new Map();
let csvString;
try {
csvString = await IOUtils.readUTF8(filePath, { encoding: "utf-8" });
} catch (ex) {
console.error(ex);
throw new ImportFailedException(
ImportFailedErrorType.FILE_PERMISSIONS_ERROR
);
}
let headerLine;
let parsedLines;
try {
let delimiter = filePath.toUpperCase().endsWith(".CSV") ? "," : "\t";
[headerLine, parsedLines] = lazy.CSV.parse(csvString, delimiter);
} catch {
throw new ImportFailedException(ImportFailedErrorType.FILE_FORMAT_ERROR);
}
if (parsedLines && headerLine) {
for (const columnName of headerLine) {
const fieldName = csvColumnToFieldMap.get(
columnName.toLocaleLowerCase()
);
if (fieldName) {
if (!csvFieldToColumnMap.has(fieldName)) {
csvFieldToColumnMap.set(fieldName, columnName);
} else {
throw new ImportFailedException(
ImportFailedErrorType.CONFLICTING_VALUES_ERROR
);
}
}
}
}
if (csvFieldToColumnMap.size === 0) {
throw new ImportFailedException(ImportFailedErrorType.FILE_FORMAT_ERROR);
}
if (
parsedLines[0] &&
(!csvFieldToColumnMap.has("origin") ||
!csvFieldToColumnMap.has("username") ||
!csvFieldToColumnMap.has("password"))
) {
// The username *value* can be empty but we require a username column to
// ensure that we don't import logins without their usernames due to the
// username column not being recognized.
throw new ImportFailedException(ImportFailedErrorType.FILE_FORMAT_ERROR);
}
let loginsToImport = parsedLines.map(csvObject => {
return LoginCSVImport._getVanillaLoginFromCSVObject(
csvObject,
csvColumnToFieldMap
);
});
let report = await lazy.LoginHelper.maybeImportLogins(loginsToImport);
for (const reportRow of report) {
if (reportRow.result === "error_missing_field") {
reportRow.field_name = csvFieldToColumnMap.get(reportRow.field_name);
}
}
// Record quantity and duration telemetry.
try {
let histogram = Services.telemetry.getHistogramById(
"PWMGR_IMPORT_LOGINS_FROM_FILE_CATEGORICAL"
);
this._recordHistogramTelemetry(histogram, report);
} catch (ex) {
console.error(ex);
}
LoginCSVImport.lastImportReport = report;
return report;
}
}