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• What is PII ? Your introduction to personally identifiable information

  15 janvier 2020, par Joselyn Khor — Analytics Tips, Privacy, Security
  Most websites you visit collect information about you via tools like Google Analytics and Matomo – sometimes collecting personally identifiable information (PII).

  When it comes to PII, people are becoming more concerned about data privacy. Identifiable information can be used for illegal purposes like identity theft and fraud. 

  So how can you protect yourself as an innocent internet browser ? In the case of website owners – how do you protect users and your company from falling prey to privacy breaches ?

  

  As one of the most trusted analytics companies, we feel our readers would benefit from being as informed as possible about data privacy issues and PII. Learn what it means, and what you can do to keep yours or others’ information safe.

  Table of Contents

  What does PII stand for ?

  PII acronym

  PII is an acronym for personally identifiable information.

  PII definition

  Personally identifiable information (PII) is a term used predominantly in the United States.

  The appendix of OMB M-10-23 (Guidance for Agency Use of Third-Party Website and Applications) gives this definition for PII :

  “The term ‘personally identifiable information’ refers to information which can be used to distinguish or trace an individual’s identity, such as their name, social security number, biometric records, etc. alone, or when combined with other personal or identifying information which is linked or linkable to a specific individual, such as date and place of birth, mother’s maiden name, etc.”

  What can be considered personally identifiable information (PII) ? Some PII examples :

  • Full name/usernames
  • Home address/mailing address
  • Email address
  • Credit card numbers
  • Date of birth
  • Phone numbers
  • Login details

  • Precise locations
  • Account numbers
  • Passwords
  • Security codes (including biometric records)
  • Personal identification numbers
  • Driver license number
  • Get a more comprehensive list here

  What’s non-PII ?

  Anonymous information, or information that can’t be traced back to an individual, can be considered non-PII.

  Who is affected by the exploitation of PII ?

  Anyone can be affected by the exploitation of personal data, where you have identity theft, account fraud and account takeovers. When websites resort to illegally selling or sharing your data and compromising your privacy, the fear is falling victim to such fraudulent activity. 

  PII can also be an issue when employees have access to the database and the data is not encrypted. For example, anyone working in a bank can access your accounts ; anyone working at Facebook may be able to read your messages. This shows how privacy breaches can easily happen when employees have access to PII.

  Website owner’s responsibility for data privacy (PII and analytics)

  To respect your website visitor’s privacy, best practice is to avoid collecting PII whenever possible. If you work in an industry which requires people to disclose personal information (e.g. healthcare, security industries, public sector), then you must ensure this data is collected and handled securely. 

  

  The US National Institute of Standards and Technology states : “The likelihood of harm caused by a breach involving PII is greatly reduced if an organisation minimises the amount of PII it uses, collects, and stores. For example, an organisation should only request PII in a new form if the PII is absolutely necessary.” 

  How you’re held accountable remains up to the privacy laws of the country you’re doing business in. Make sure you are fully aware of the privacy and data protection laws that relate specifically to you. 

  To reduce the risk of privacy breaches, try collecting as little PII as you can ; purging it as soon as you can ; and making sure your IT security is updated and protected against security threats. 

  If you’re using data collection tools like web analytics, data may be tracked through features like User ID, custom variables, and custom dimensions. Sometimes they are also harder to identify when they are present, for example, in page URLs, page titles, or referrers URLs. So make sure you’re optimising your web analytics tools’ settings to ensure you’re asking your users for consent and respecting users’ privacy.

  If you’re using a GDPR compliant tool like Matomo, learn how you can stop processing such personal data

  PII, GDPR and businesses in the US/EU

  Because PII is broad, you may run into confusion when considering PII and GDPR (which applies in the EU). The General Data Protection Regulation (GDPR) provides more safeguards for user privacy.

  GDPR grants people in the EU more rights concerning their “personal data” (more on PII vs personal data below). In the EU the GDPR restricts the collection and processing of personal data. The repercussions are severe penalties and fines for privacy infringements. Businesses are required to handle this personal data carefully. You can be fined up to 4% of their yearly revenue for data breaches or non-compliance. 

  

  Although there isn’t an overarching data protection law in the US, there are hundreds of laws on both the federal and state levels to protect the personal data of US residents. US Congress has also enacted industry-specific statutes related to data privacy, and the state of California passed the California Consumer Privacy Act. 

  To be on the safe side, if you are using analytics, follow matters relating to “personal data” in the GDPR. It’s all-encompassing when it comes to protecting user privacy. GDPR rules still apply whenever an EU citizen visits any non EU site (that processes personal data).

  Personally identifiable information (PII) vs personal data

  PII and “personal data” aren’t used interchangeably. All personal data can be PII, but not all PII can be defined as personal data.

  The definition of “personal data” according to the GDPR :

  

  This means “personal data” encompasses a greater number of identifiers which include the online sphere. Examples include : IP addresses and URL names. As well as seemingly “innocent” data like height, job position, company etc. 

  What’s considered personal data depends on the context. If a piece of information can be combined with others to establish someone’s identity then that can be considered personal data. 

  Under GDPR, when processing personal data, you need explicit consent. You need to ensure you’re compliant according to GDPR definitions of “personal data” not just what’s considered “PII”.

  How Matomo deals with PII and personal data

  Although Matomo Analytics is a web analytics software that tracks user activity on your website, we take privacy and PII very seriously – on both our Cloud and On-Premise offerings. 

  If you’re using Matomo and would like to know how you can be fully GDPR compliant and protect user privacy, read more :
  

  • Learn how to not process any personally identifiable information – Anonymise IP addresses, user IDs, and order IDs
  • Matomo protects user privacy by talking the talk and walking the walk
  • Stay ahead of the GDPR with a privacy-respecting analytics platform
  • 11 ways Matomo helps you protect your visitor’s privacy

  Disclaimer

  We are not lawyers and don’t claim to be. The information provided here is to help give an introduction to issues you may encounter when dealing with PII. We encourage every business and website to take data privacy seriously and discuss these issues with your lawyer if you have any concerns. 

  Additional resources :

  • https://www.consumeraffairs.com/finance/identity-theft-statistics.html#identity-theft-trends-in-2019
  • https://ec.europa.eu/info/law/law-topic/data-protection_en
  • https://iclg.com/practice-areas/data-protection-laws-and-regulations/usa
  • https://www.csoonline.com/article/3215864/how-to-protect-personally-identifiable-information-pii-under-gdpr.html
  • https://ico.org.uk/for-organisations/guide-to-data-protection/guide-to-the-general-data-protection-regulation-gdpr/key-definitions/what-is-personal-data/

• PyQt6 6.7.0 - How to fix error : No QtMultimedia backends found

  4 février, par Belleroph0N

  Problem on Windows 10 and Windows 11 using Anaconda.

  


  Here is the full error message for PyQt6=6.7.0 :

  


  No QtMultimedia backends found. Only QMediaDevices, QAudioDevice, QSoundEffect, QAudioSink, and QAudioSource are available.
Failed to initialize QMediaPlayer "Not available"
Failed to create QVideoSink "Not available"


  


  Installed PyQt6 using a requirements file :

  


  PyQt6
PyQt6-WebEngine
requests
pyserial
pynput


  


  Here are a couple things I tried :

  


  

  1. Reroll version back to PyQt6=6.6.1. This results in an error as well : ImportError : DLL load failed while importing QtGui : The specified procedure could not be found.

  


  2. I thought that missing ffmpeg might be the issue so I installed it, but the issue persists.

  


  3. Tried the setup on Ubuntu (WSL2) and the issue disappears, but there is just a black screen and nothing gets displayed in the widget. (EDIT : Got this up and running, the problem was with differences in file paths in linux vs windows.)

  


  


  I am new to PyQt so any pointers will be helpful !

  


  Edit : Here is generic code (taken from here) that gives the same error :

  


  from PyQt6.QtGui import QIcon, QFont
from PyQt6.QtCore import QDir, Qt, QUrl, QSize
from PyQt6.QtMultimedia import QMediaPlayer
from PyQt6.QtMultimediaWidgets import QVideoWidget
from PyQt6.QtWidgets import (QApplication, QFileDialog, QHBoxLayout, QLabel, QStyleFactory,
        QPushButton, QSizePolicy, QSlider, QStyle, QVBoxLayout, QWidget, QStatusBar)


class VideoPlayer(QWidget):

    def __init__(self, parent=None):
        super(VideoPlayer, self).__init__(parent)

        self.mediaPlayer = QMediaPlayer()

        btnSize = QSize(16, 16)
        videoWidget = QVideoWidget()

        openButton = QPushButton("Open Video")   
        openButton.setToolTip("Open Video File")
        openButton.setStatusTip("Open Video File")
        openButton.setFixedHeight(24)
        openButton.setIconSize(btnSize)
        openButton.setFont(QFont("Noto Sans", 8))
        openButton.setIcon(QIcon.fromTheme("document-open", QIcon("D:/_Qt/img/open.png")))
        openButton.clicked.connect(self.abrir)

        self.playButton = QPushButton()
        self.playButton.setEnabled(False)
        self.playButton.setFixedHeight(24)
        self.playButton.setIconSize(btnSize)
        self.playButton.setIcon(self.style().standardIcon(QStyle.StandardPixmap.SP_MediaPlay))
        self.playButton.clicked.connect(self.play)

        self.positionSlider = QSlider(Qt.Orientation.Horizontal)
        self.positionSlider.setRange(0, 0)
        self.positionSlider.sliderMoved.connect(self.setPosition)

        self.statusBar = QStatusBar()
        self.statusBar.setFont(QFont("Noto Sans", 7))
        self.statusBar.setFixedHeight(14)

        controlLayout = QHBoxLayout()
        controlLayout.setContentsMargins(0, 0, 0, 0)
        controlLayout.addWidget(openButton)
        controlLayout.addWidget(self.playButton)
        controlLayout.addWidget(self.positionSlider)

        layout = QVBoxLayout()
        layout.addWidget(videoWidget)
        layout.addLayout(controlLayout)
        layout.addWidget(self.statusBar)

        self.setLayout(layout)

        #help(self.mediaPlayer)
        self.mediaPlayer.setVideoOutput(videoWidget)
        self.mediaPlayer.playbackStateChanged.connect(self.mediaStateChanged)
        self.mediaPlayer.positionChanged.connect(self.positionChanged)
        self.mediaPlayer.durationChanged.connect(self.durationChanged)
        self.mediaPlayer.errorChanged.connect(self.handleError)
        self.statusBar.showMessage("Ready")

    def abrir(self):
        fileName, _ = QFileDialog.getOpenFileName(self, "Select Media",
                ".", "Video Files (*.mp4 *.flv *.ts *.mts *.avi)")

        if fileName != '':
            self.mediaPlayer.setSource(QUrl.fromLocalFile(fileName))
            self.playButton.setEnabled(True)
            self.statusBar.showMessage(fileName)
            self.play()

    def play(self):
        if self.mediaPlayer.playbackState() == QMediaPlayer.PlaybackState.PlayingState:
            self.mediaPlayer.pause()
        else:
            self.mediaPlayer.play()

    def mediaStateChanged(self, state):
        if self.mediaPlayer.playbackState() == QMediaPlayer.PlaybackState.PlayingState:
            self.playButton.setIcon(
                    self.style().standardIcon(QStyle.StandardPixmap.SP_MediaPause))
        else:
            self.playButton.setIcon(
                    self.style().standardIcon(QStyle.StandardPixmap.SP_MediaPlay))

    def positionChanged(self, position):
        self.positionSlider.setValue(position)

    def durationChanged(self, duration):
        self.positionSlider.setRange(0, duration)

    def setPosition(self, position):
        self.mediaPlayer.setPosition(position)

    def handleError(self):
        self.playButton.setEnabled(False)
        self.statusBar.showMessage("Error: " + self.mediaPlayer.errorString())

if __name__ == '__main__':
    import sys
    app = QApplication(sys.argv)
    player = VideoPlayer()
    player.setWindowTitle("Player")
    player.resize(900, 600)
    player.show()
    sys.exit(app.exec())


  


  The videos I want to play are in the same folder as this .py file.
The conda env (python 3.9.2) I am working on has the following packages :

  


  certifi                     2024.6.2
charset-normalizer          3.3.2
idna                        3.7
pip                         24.0
pynput                      1.7.6
PyQt6                       6.7.0
PyQt6-Qt6                   6.7.1
PyQt6-sip                   13.6.0
PyQt6-WebEngine             6.7.0
PyQt6-WebEngine-Qt6         6.7.1
PyQt6-WebEngineSubwheel-Qt6 6.7.1
pyserial                    3.5
requests                    2.31.0
setuptools                  69.5.1
six                         1.16.0
urllib3                     2.2.1
wheel                       0.43.0


  


  PS : MacOS seems to have the same issue.

  


• ffmpeg Command in Docker with Rust Tokio Closes Warp Server Connection (curl 52 Error)

  3 juin 2024, par user762345

  I’m encountering an issue where executing an ffmpeg concatenation command through Rust’s Tokio process in a Docker container causes subsequent HTTP requests to fail. The error occurs exclusively after running the ffmpeg command and making immediate requests, resulting in a “curl 52 empty response from server” error with the connection being closed. Notably, this issue does not occur when running the same setup outside of Docker. Additionally, if no HTTP requests are made after the ffmpeg command, the curl 52 error does not occur.

  


  Here is the verbose curl output of my minimum reproducible example (see below).

  


  curl -v "http://localhost:3030"
*   Trying 127.0.0.1:3030...
* Connected to localhost (127.0.0.1) port 3030 (#0)
> GET / HTTP/1.1
> Host: localhost:3030
> User-Agent: curl/8.1.2
> Accept: */*
> 
* Empty reply from server
* Closing connection 0
curl: (52) Empty reply from server


  


  Here are Docker logs from my minimum reproducible example (see below). The wav files are concatenated successfully, then the container appears to rebuild.

  


  [2024-06-03T05:26:58Z INFO  minimal_docker_webserver_post_error] Starting server on 0.0.0.0:3030
[2024-06-03T05:26:58Z INFO  warp::server] Server::run; addr=0.0.0.0:3030
[2024-06-03T05:26:58Z INFO  warp::server] listening on http://0.0.0.0:3030
[2024-06-03T05:27:07Z INFO  minimal_docker_webserver_post_error] WAV files concatenated successfully
[Running 'cargo run']
    Finished `dev` profile [unoptimized + debuginfo] target(s) in 0.06s
     Running `target/debug/minimal_docker_webserver_post_error`
[2024-06-03T05:27:08Z INFO  minimal_docker_webserver_post_error] Starting server on 0.0.0.0:3030
[2024-06-03T05:27:08Z INFO  warp::server] Server::run; addr=0.0.0.0:3030
[2024-06-03T05:27:08Z INFO  warp::server] listening on http://0.0.0.0:3030


  


  What I have tried :
I tried using different web frameworks (Warp, Actix-web) and request crates (reqwest, ureq). I also tried running the setup outside of Docker, which worked as expected without any issues. Additionally, I tried running the setup in Docker without making any HTTP requests after the ffmpeg command, and the connection closed successfully without errors. I also tried posting to httpbin with a minimal request, but the issue persisted.

  


  Minimum reproducible example :

  


  main.rs

  


  use warp::Filter;&#xA;use reqwest::Client;&#xA;use std::convert::Infallible;&#xA;use log::{info, error};&#xA;use env_logger;&#xA;use tokio::process::Command;&#xA;&#xA;#[tokio::main]&#xA;async fn main() {&#xA;    std::env::set_var("RUST_LOG", "debug");&#xA;    env_logger::init();&#xA;&#xA;    let route = warp::path::end()&#xA;        .and_then(handle_request);&#xA;&#xA;    info!("Starting server on 0.0.0.0:3030");&#xA;    warp::serve(route)&#xA;        .run(([0, 0, 0, 0], 3030))&#xA;        .await;&#xA;}&#xA;&#xA;async fn handle_request() -> Result<impl infallible="infallible"> {&#xA;    let client = Client::new();&#xA;&#xA;    let output = Command::new("ffmpeg")&#xA;        .args(&amp;[&#xA;            "y",&#xA;            "-i", "concat:/usr/src/minimal_docker_webserver_post_error/file1.wav|/usr/src/minimal_docker_webserver_post_error/file2.wav",&#xA;            "-c", "copy",&#xA;            "/usr/src/minimal_docker_webserver_post_error/combined.wav"&#xA;        ])&#xA;        .output()&#xA;        .await;&#xA;&#xA;    match output {&#xA;        Ok(output) => {&#xA;            if output.status.success() {&#xA;                info!("WAV files concatenated successfully");&#xA;            } else {&#xA;                error!("Failed to concatenate WAV files: {:?}", output);&#xA;                return Ok(warp::reply::with_status("Failed to concatenate WAV files", warp::http::StatusCode::INTERNAL_SERVER_ERROR));&#xA;            }&#xA;        },&#xA;        Err(e) => {&#xA;            error!("Failed to execute ffmpeg: {:?}", e);&#xA;            return Ok(warp::reply::with_status("Failed to execute ffmpeg", warp::http::StatusCode::INTERNAL_SERVER_ERROR));&#xA;        }&#xA;    }&#xA;&#xA;    // ISSUE: Connection closes with curl: (52) Empty reply from server&#xA;    match client.get("https://httpbin.org/get").send().await {&#xA;        Ok(response) => info!("GET request successful: {:?}", response),&#xA;        Err(e) => error!("GET request failed: {:?}", e),&#xA;    }&#xA;&#xA;    match client.post("https://httpbin.org/post")&#xA;        .body("field1=value1&amp;field2=value2")&#xA;        .send().await {&#xA;        Ok(response) => info!("POST request successful: {:?}", response),&#xA;        Err(e) => error!("POST request failed: {:?}", e),&#xA;    }&#xA;&#xA;    Ok(warp::reply::with_status("Request handled", warp::http::StatusCode::OK))&#xA;}&#xA;</impl>

  


  FFMPEG command to generate the two wav files for concatenation

  


  ffmpeg -f lavfi -i "sine=frequency=1000:duration=5" file1.wav && ffmpeg -f lavfi -i "sine=frequency=500:duration=5" file2.wav


  


  Dockerfile

  


  # Use the official Rust image as the base image
FROM rust:latest

# Install cargo-watch
RUN cargo install cargo-watch

# Install ffmpeg
RUN apt-get update && apt-get install -y ffmpeg

# Set the working directory inside the container
WORKDIR /usr/src/minimal_docker_webserver_post_error

# Copy the Cargo.toml and Cargo.lock files
COPY Cargo.toml Cargo.lock ./

# Copy the source code
COPY src ./src

# Copy wav files
COPY file1.wav /usr/src/minimal_docker_webserver_post_error/file1.wav
COPY file2.wav /usr/src/minimal_docker_webserver_post_error/file2.wav

# Install dependencies
RUN cargo build --release

# Expose the port that the application will run on
EXPOSE 3030

# Set the entry point to use cargo-watch
CMD ["cargo", "watch", "-x", "run"]


  


  Cargo.toml

  


  [package]
name = "minimal_docker_webserver_post_error"
version = "0.1.0"
edition = "2021"

# See more keys and their definitions at https://doc.rust-lang.org/cargo/reference/manifest.html

[dependencies]
warp = "0.3"
reqwest = { version = "0.12.4", features = ["json"] }
tokio = { version = "1", features = ["full"] }
log = "0.4"
env_logger = "0.11.3"


  


  Making the request to the warp server

  


  curl -v "http://localhost:3030"