Page 1 of 5
The NSA finally admitted to buying bulk data on Americans from data brokers, in response to a query by Senator Wyden.
This is almost certainly illegal, although the NSA maintains that it is legal until it’s told otherwise.
Here are Wyden’s press release and some news articles.
When you get a push notification on your Apple or Google phone, those notifications go through Apple and Google servers. Which means that those companies can spy on them—either for their own reasons or in response to government demands.
Sen. Wyden is trying to get to the bottom of this:
In a statement, Apple said that Wyden’s letter gave them the opening they needed to share more details with the public about how governments monitored push notifications.
“In this case, the federal government prohibited us from sharing any information,” the company said in a statement. “Now that this method has become public we are updating our transparency reporting to detail these kinds of requests.”
Google said that it shared Wyden’s “commitment to keeping users informed about these requests.”
The Department of Justice did not return messages seeking comment on the push notification surveillance or whether it had prevented Apple of Google from talking about it.
Wyden’s letter cited a “tip” as the source of the information about the surveillance. His staff did not elaborate on the tip, but a source familiar with the matter confirmed that both foreign and U.S. government agencies have been asking Apple and Google for metadata related to push notifications to, for example, help tie anonymous users of messaging apps to specific Apple or Google accounts.
The Intercept has a long article on the insecurity of photo cropping:
One of the hazards lies in the fact that, for some of the programs, downstream crop reversals are possible for viewers or readers of the document, not just the file’s creators or editors. Official instruction manuals, help pages, and promotional materials may mention that cropping is reversible, but this documentation at times fails to note that these operations are reversible by any viewers of a given image or document.
[…]
Uncropped versions of images can be preserved not just in Office apps, but also in a file’s own metadata. A photograph taken with a modern digital camera contains all types of metadata. Many image files record text-based metadata such as the camera make and model or the GPS coordinates at which the image was captured. Some photos also include binary data such as a thumbnail version of the original photo that may persist in the file’s metadata even after the photo has been edited in an image editor.
Long and interesting interview with Signal’s new president, Meredith Whittaker:
WhatsApp uses the Signal encryption protocol to provide encryption for its messages. That was absolutely a visionary choice that Brian and his team led back in the day - and big props to them for doing that. But you can’t just look at that and then stop at message protection. WhatsApp does not protect metadata the way that Signal does. Signal knows nothing about who you are. It doesn’t have your profile information and it has introduced group encryption protections. We don’t know who you are talking to or who is in the membership of a group. It has gone above and beyond to minimize the collection of metadata.
WhatsApp, on the other hand, collects the information about your profile, your profile photo, who is talking to whom, who is a group member. That is powerful metadata. It is particularly powerful—and this is where we have to back out into a structural argument for a company to collect the data that is also owned by Meta/Facebook. Facebook has a huge amount, just unspeakable volumes, of intimate information about billions of people across the globe.
It is not trivial to point out that WhatsApp metadata could easily be joined with Facebook data, and that it could easily reveal extremely intimate information about people. The choice to remove or enhance the encryption protocols is still in the hands of Facebook. We have to look structurally at what that organization is, who actually has control over these decisions, and at some of these details that often do not get discussed when we talk about message encryption overall.
I am a fan of Signal and I use it every day. The one feature I want, which WhatsApp has and Signal does not, is the ability to easily export a chat to a text file.
Bunnie Huang has created a Plausibly Deniable Database.
Most security schemes facilitate the coercive processes of an attacker because they disclose metadata about the secret data, such as the name and size of encrypted files. This allows specific and enforceable demands to be made: “Give us the passwords for these three encrypted files with names A, B and C, or else…”. In other words, security often focuses on protecting the confidentiality of data, but lacks deniability.
A scheme with deniability would make even the existence of secret files difficult to prove. This makes it difficult for an attacker to formulate a coherent demand: “There’s no evidence of undisclosed data. Should we even bother to make threats?” A lack of evidence makes it more difficult to make specific and enforceable demands.
[…]
Precursor is a device we designed to keep secrets, such as passwords, wallets, authentication tokens, contacts and text messages. We also want it to offer plausible deniability in the face of an attacker that has unlimited access to a physical device, including its root keys, and a set of “broadly known to exist” passwords, such as the screen unlock password and the update signing password. We further assume that an attacker can take a full, low-level snapshot of the entire contents of the FLASH memory, including memory marked as reserved or erased. Finally, we assume that a device, in the worst case, may be subject to repeated, intrusive inspections of this nature.
We created the PDDB (Plausibly Deniable DataBase) to address this threat scenario. The PDDB aims to offer users a real option to plausibly deny the existence of secret data on a Precursor device. This option is strongest in the case of a single inspection. If a device is expected to withstand repeated inspections by the same attacker, then the user has to make a choice between performance and deniability. A “small” set of secrets (relative to the entire disk size, on Precursor that would be 8MiB out of 100MiB total size) can be deniable without a performance impact, but if larger (e.g. 80MiB out of 100MiB total size) sets of secrets must be kept, then archived data needs to be turned over frequently, to foil ciphertext comparison attacks between disk imaging events.
I have been thinking about this sort of thing for many, many years. (Here’s my analysis of one such system.) I have come to realize that the threat model isn’t as simple as Bunnie describes. The goal is to prevent “rubber-hose cryptanalysis,” simply beating the encryption key out of someone. But while a deniable database or file system allows the person to plausibly say that there are no more keys to beat out of them, the perpetrators can never be sure. The value of a normal, undeniable encryption system is that the perpetrators will know when they can stop beating the person—the person can undeniably say that there are no more keys left to reveal.
A January 2021 FBI document outlines what types of data and metadata can be lawfully obtained by the FBI from messaging apps. Rolling Stone broke the story and it’s been written about elsewhere.
I don’t see a lot of surprises in the document. Lots of apps leak all sorts of metadata: iMessage and WhatsApp seem to be the worst. Signal protects the most metadata. End-to-end encrypted message content can be available if the user uploads it to an unencrypted backup server.
EDITED TO ADD (12/13): Here’s a more legible copy of the text.
Really interesting research:
“Exploitation and Sanitization of Hidden Data in PDF Files”
Abstract: Organizations publish and share more and more electronic documents like PDF files. Unfortunately, most organizations are unaware that these documents can compromise sensitive information like authors names, details on the information system and architecture. All these information can be exploited easily by attackers to footprint and later attack an organization. In this paper, we analyze hidden data found in the PDF files published by an organization. We gathered a corpus of 39664 PDF files published by 75 security agencies from 47 countries. We have been able to measure the quality and quantity of information exposed in these PDF files. It can be effectively used to find weak links in an organization: employees who are running outdated software. We have also measured the adoption of PDF files sanitization by security agencies. We identified only 7 security agencies which sanitize few of their PDF files before publishing. Unfortunately, we were still able to find sensitive information within 65% of these sanitized PDF files. Some agencies are using weak sanitization techniques: it requires to remove all the hidden sensitive information from the file and not just to remove the data at the surface. Security agencies need to change their sanitization methods.
Short summary: no one is doing great.
A group of researchers set up a telephony honeypot and tracked robocall behavior:
NCSU researchers said they ran 66,606 telephone lines between March 2019 and January 2020, during which time they said to have received 1,481,201 unsolicited calls—even if they never made their phone numbers public via any source.
The research team said they usually received an unsolicited call every 8.42 days, but most of the robocall traffic came in sudden surges they called “storms” that happened at regular intervals, suggesting that robocallers operated using a tactic of short-burst and well-organized campaigns.
In total, the NCSU team said it tracked 650 storms over 11 months, with most storms being of the same size.
Note that this is “announced,” so we don’t know when it’s actually going to be implemented.
Facebook today announced new features for Messenger that will alert you when messages appear to come from financial scammers or potential child abusers, displaying warnings in the Messenger app that provide tips and suggest you block the offenders. The feature, which Facebook started rolling out on Android in March and is now bringing to iOS, uses machine learning analysis of communications across Facebook Messenger’s billion-plus users to identify shady behaviors. But crucially, Facebook says that the detection will occur only based on metadata—not analysis of the content of messages—so that it doesn’t undermine the end-to-end encryption that Messenger offers in its Secret Conversations feature. Facebook has said it will eventually roll out that end-to-end encryption to all Messenger chats by default.
That default Messenger encryption will take years to implement.
More:
Facebook hasn’t revealed many details about how its machine-learning abuse detection tricks will work. But a Facebook spokesperson tells WIRED the detection mechanisms are based on metadata alone: who is talking to whom, when they send messages, with what frequency, and other attributes of the relevant accounts—essentially everything other than the content of communications, which Facebook’s servers can’t access when those messages are encrypted. “We can get pretty good signals that we can develop through machine learning models, which will obviously improve over time,” a Facebook spokesperson told WIRED in a phone call. They declined to share more details in part because the company says it doesn’t want to inadvertently help bad actors circumvent its safeguards.
The company’s blog post offers the example of an adult sending messages or friend requests to a large number of minors as one case where its behavioral detection mechanisms can spot a likely abuser. In other cases, Facebook says, it will weigh a lack of connections between two people’s social graphs—a sign that they don’t know each other—or consider previous instances where users reported or blocked a someone as a clue that they’re up to something shady.
One screenshot from Facebook, for instance, shows an alert that asks if a message recipient knows a potential scammer. If they say no, the alert suggests blocking the sender, and offers tips about never sending money to a stranger. In another example, the app detects that someone is using a name and profile photo to impersonate the recipient’s friend. An alert then shows the impersonator’s and real friend’s profiles side-by-side, suggesting that the user block the fraudster.
Details from Facebook
EDITED TO ADD (7/1): This entry has been translated into Spanish.
The New York Times is reporting on the NSA’s phone metadata program, which the NSA shut down last year:
A National Security Agency system that analyzed logs of Americans’ domestic phone calls and text messages cost $100 million from 2015 to 2019, but yielded only a single significant investigation, according to a newly declassified study.
Moreover, only twice during that four-year period did the program generate unique information that the F.B.I. did not already possess, said the study, which was produced by the Privacy and Civil Liberties Oversight Board and briefed to Congress on Tuesday.
[…]
The privacy board, working with the intelligence community, got several additional salient facts declassified as part of the rollout of its report. Among them, it officially disclosed that the system has gained access to Americans’ cellphone records, not just logs of landline phone calls.
It also disclosed that in the four years the Freedom Act system was operational, the National Security Agency produced 15 intelligence reports derived from it. The other 13, however, contained information the F.B.I. had already collected through other means, like ordinary subpoenas to telephone companies.
The report cited two investigations in which the National Security Agency produced reports derived from the program: its analysis of the Pulse nightclub mass shooting in Orlando, Fla., in June 2016 and of the November 2016 attack at Ohio State University by a man who drove his car into people and slashed at them with a machete. But it did not say whether the investigations into either of those attacks were connected to the two intelligence reports that provided unique information not already in the possession of the F.B.I.
This program is legal due to the USA FREEDOM Act, which expires on March 15. Congress is currently debating whether to extend the authority, even though the NSA says it’s not using it now.
Sidebar photo of Bruce Schneier by Joe MacInnis.