* ssh(1): expand the StrictHostKeyChecking option with two new settings. The first "accept-new" will automatically accept hitherto-unseen keys but will refuse connections for changed or invalid hostkeys. This is a safer subset of the current behaviour of StrictHostKeyChecking=no. The second setting "off", is a synonym for the current behaviour of StrictHostKeyChecking=no: accept new host keys, and continue connection for hosts with incorrect hostkeys. A future release will change the meaning of StrictHostKeyChecking=no to the behaviour of "accept-new". bz#2400
The scheme flooding vulnerability allows an attacker to determine which applications you have installed. In order to generate a 32-bit cross-browser device identifier, a website can test a list of 32 popular applications and check if each is installed or not. On average, the identification process takes a few seconds and works across desktop Windows, Mac and Linux operating systems.
被擋下後再打都會失敗，所以需要一個方式重設 flag，而內建的 Chrome PDF Viewer 剛好可以重設 flag：
The built-in Chrome PDF Viewer is an extension, so every time your browser opens a PDF file it resets the scheme flood protection flag. Opening a PDF file before opening a custom URL makes the exploit functional.
Every time you navigate to an unknown URL scheme, Firefox will show you an internal page with an error. This internal page has a different origin than any other website, so it is impossible to access it because of the Same-origin policy limitation. On the other hand, a known custom URL scheme will be opened as about:blank, whose origin will be accessible from the current website.
You are not authorized to access bug #225769. To see this bug, you must first log in to an account with the appropriate permissions.
另外，雖然 Tor Browser 底層是 Firefox，但因為有改變預設值，所以攻擊者也得換方法：
Tor Browser is based on the Firefox source code, so the Same-origin policy trick was used here as well. But because Tor Browser does not show pop-ups, we used the same-origin policy trick with iframe elements instead.
The team also alerted us to a class of attacks that were enabled by Privacy Badger’s learning. Essentially, since Privacy Badger adapts its behavior based on the way that sites you visit behave, a dedicated attacker could manipulate the way Privacy Badger acts: what it blocks and what it allows. In theory, this can be used to identify users (a form of fingerprinting) or to extract some kinds of information from the pages they visit. This is similar to the set of vulnerabilities that Safari’s Intelligent Tracking Prevention feature disclosed and patched late last year.
所以現在變成會固定更新 pre-train ruleset 了：
From now on, Privacy Badger will rely solely on its “Badger Sett” pre-trained list of tracking domains to perform blocking by default. Furthermore, Privacy Badger’s tracker database will be refreshed periodically with the latest pre-trained definitions. This means, moving forward, all Privacy Badgers will default to relying on the same learned list of trackers for blocking.
We want to build features that users want, so a subset of users may get a sneak peek at new functionality being tested before it’s launched to the world at large. A list of field trials that are currently active on your installation of Chrome will be included in all requests sent to Google. This Chrome-Variations header (X-Client-Data) will not contain any personally identifiable information, and will only describe the state of the installation of Chrome itself, including active variations, as well as server-side experiments that may affect the installation.
The variations active for a given installation are determined by a seed number which is randomly selected on first run. If usage statistics and crash reports are disabled, this number is chosen between 0 and 7999 (13 bits of entropy). If you would like to reset your variations seed, run Chrome with the command line flag “--reset-variation-state”. Experiments may be further limited by country (determined by your IP address), operating system, Chrome version and other parameters.
但因為這個預設值開啟的關係，就算關掉後也足以把使用者再分類到另外一個區塊，仍然具有高度辨識性，不是你 Google 說無法辨識就算數。
另外如果看 source code 裡的說明：
// Note the criteria for attaching client experiment headers:
// 1. We only transmit to Google owned domains which can evaluate
// experiments.
// 1a. These include hosts which have a standard postfix such as:
// *.doubleclick.net or *.googlesyndication.com or
// exactly www.googleadservices.com or
// international TLD domains *.google. or *.youtube..
// 2. Only transmit for non-Incognito profiles.
// 3. For the X-Client-Data header, only include non-empty variation IDs.
You are affected by this fingerprinting attack if you are using any iOS devices with the iOS version below 12.2, including the latest iPhone XS, iPhone XS Max, and iPhone XR. You are also likely to be affected if you are using a Pixel 2/3 device, although we hypothesise the generated fingerprint has less entropy and is unlikely to be globally unique. A SensorID can be generated by both apps and mobile websites and requires no user interaction.
目前 iPhone 升級到 12.2 之後可以緩解這個問題，Android 看起來還不清楚...
攻擊的方式是透過手機在出場前會使用外部的校正工具，找出手機內 sensor 所偵測到的值與實際值的差異，然後把這些資訊燒到韌體裡，當呼叫 API 時就可以修正給出比較正確的值。
而因為這些校正資訊幾乎每一隻手機都不一樣，而且不會因為重裝而變更 (即使 factory reset)，加上還可以跨 app 與 web 追蹤，就成為這次攻擊的目標：
In the context of mobile devices, the main benefit of per-device calibration is that it allows more accurate attitude estimation.
In general, it is difficult to create a unique fingerprint for iOS devices due to strict sandboxing and device homogeneity. However, we demonstrated that our approach can produce globally unique fingerprints for iOS devices from an installed app -- around 67 bits of entropy for the iPhone 6S. Calibration fingerprints generated by a website are less unique (~42 bits of entropy for the iPhone 6S), but they are orthogonal to existing fingerprinting techniques and together they are likely to form a globally unique fingerprint for iOS devices.
We have not observed any change in the SensorID of our test devices in the past half year. Our dataset includes devices running iOS 9/10/11/12. We have tested compass calibration, factory reset, and updating iOS (up until iOS 12.1); the SensorID always stays the same. We have also tried measuring the sensor data at different locations and under different temperatures; we confirm that these factors do not change the SensorID either.
To mitigate this calibration fingerprint attack, vendors can add uniformly distributed random noise to ADC outputs before calibration is applied. Alternatively, vendors could round the sensor outputs to the nearest multiple of the nominal gain. Please refer to our paper for more details. In addition, we recommend privacy-focused mobile browsers add an option to disable the access to motion sensors via JavaScript. This could help protect Android devices and iOS devices that no longer receive updates from Apple.
According to a Facebook spokesperson, Facebook workers will have to review full, uncensored versions of nude images first, volunteered by the user, to determine if malicious posts by other users qualify as revenge porn.
Until now, one of the most popular headless browser was PhantomJS. Since it is built on the Qt framework, it exhibits many differences compared to most popular browsers. As presented in this post, it is possible to detect it using some browser fingerprinting techniques.
但從 Google Chrome 59 以後因為支援 Headless，使得大多數的判斷的失效：
Since version 59, Google released a headless version of its Chrome browser. Unlike PhantomJS, it is based on a vanilla Chrome, and not on an external framework, making its presence more difficult to detect.
Record 1 minute from someone's voice and Lyrebird can compress her/his voice's DNA into a unique key. Use this key to generate anything with its corresponding voice.
To halt the activity, Uber engineers assigned a persistent identity to iPhones with a small piece of code, a practice called “fingerprinting.” Uber could then identify an iPhone and prevent itself from being fooled even after the device was erased of its contents.
There was one problem: Fingerprinting iPhones broke Apple’s rules. Mr. Cook believed that wiping an iPhone should ensure that no trace of the owner’s identity remained on the device.
而 Uber 的搞法是針對蘋果總部所在地點屏蔽這個功能：
So Mr. Kalanick told his engineers to “geofence” Apple’s headquarters in Cupertino, Calif., a way to digitally identify people reviewing Uber’s software in a specific location. Uber would then obfuscate its code for people within that geofenced area, essentially drawing a digital lasso around those it wanted to keep in the dark. Apple employees at its headquarters were unable to see Uber’s fingerprinting.
然後被蘋果工程師抓到，於是 Tim Cook 把人叫來喝咖啡：
The ruse did not last. Apple engineers outside of Cupertino caught on to Uber’s methods, prompting Mr. Cook to call Mr. Kalanick to his office.
Using an email digest service it owns named Unroll.me, Slice collected its customers’ emailed Lyft receipts from their inboxes and sold the anonymized data to Uber. Uber used the data as a proxy for the health of Lyft’s business. (Lyft, too, operates a competitive intelligence team.)
I worked for a company that nearly acquired unroll.me. At the time, which was over three years ago, they had kept a copy of every single email of yours that you sent or received while a part of their service. Those emails were kept in a series of poorly secured S3 buckets. A large part of Slice buying unroll.me was for access to those email archives. Specifically, they wanted to look for keyword trends and for receipts from online purchases.
The founders of unroll.me were pretty dishonest, which is a large part of why the company I worked for declined to purchase the company. As an example, one of the problems was how the founders had valued and then diluted equity shares that employees held. To make a long story short, there weren't any circumstances in which employees who held options or an equity stake would see any money.
I hope you weren't emailed any legal documents or passwords written in the clear.
