According to the complaint against him, Al-Azhari allegedly visited a dark web site that hosts “unofficial propaganda and photographs related to ISIS” multiple times on May 14, 2019. In virtue of being a dark web site—­that is, one hosted on the Tor anonymity network—­it should have been difficult for the site owner’s or a third party to determine the real IP address of any of the site’s visitors.

Yet, that’s exactly what the FBI did. It found Al-Azhari allegedly visited the site from an IP address associated with Al-Azhari’s grandmother’s house in Riverside, California. The FBI also found what specific pages Al-Azhari visited, including a section on donating Bitcoin; another focused on military operations conducted by ISIS fighters in Iraq, Syria, and Nigeria; and another page that provided links to material from ISIS’s media arm. Without the FBI deploying some form of surveillance technique, or Al-Azhari using another method to visit the site which exposed their IP address, this should not have been possible...

The findings, which NJIT researchers will present at the Usenix Security Symposium in Boston next month, show how an attacker who tricks someone into loading a malicious website can determine whether that visitor controls a particular public identifier, like an email address or social media account, thus linking the visitor to a piece of potentially personal data.

When you visit a website, the page can capture your IP address, but this doesn’t necessarily give the site owner enough information to individually identify you. Instead, the hack analyzes subtle features of a potential target’s browser activity to determine whether they are logged into an account for an array of services, from YouTube and Dropbox to Twitter, Facebook, TikTok, and more. Plus the attacks work against every major browser, including the anonymity-focused Tor Browser...

Within a few years of Bitcoin’s arrival, academic security researchers — and then companies like Chainalysis — began to tear gaping holes in the masks separating Bitcoin users’ addresses and their real-world identities. They could follow bitcoins on the blockchain as they moved from address to address until they reached one that could be tied to a known identity. In some cases, an investigator could learn someone’s Bitcoin addresses by transacting with them, the way an undercover narcotics agent might conduct a buy-and-bust. In other cases, they could trace a target’s coins to an account at a cryptocurrency exchange where financial regulations required users to prove their identity. A quick subpoena to the exchange from one of Chainalysis’ customers in law enforcement was then enough to strip away any illusion of Bitcoin’s anonymity...

Grouping these servers under the KAX17 umbrella, Nusenu says this threat actor has constantly added servers with no contact details to the Tor network in industrial quantities, operating servers in the realm of hundreds at any given point.

The actor’s servers are typically located in data centers spread all over the world and are typically configured as entry and middle points primarily, although KAX17 also operates a small number of exit points...

Abstract: Recently, generative adversarial networks (GANs) have achieved stunning realism, fooling even human observers. Indeed, the popular tongue-in-cheek website http://thispersondoesnotexist.com, taunts users with GAN generated images that seem too real to believe. On the other hand, GANs do leak information about their training data, as evidenced by membership attacks recently demonstrated in the literature. In this work, we challenge the assumption that GAN faces really are novel creations, by constructing a successful membership attack of a new kind. Unlike previous works, our attack can accurately discern samples sharing the same identity as training samples without being the same samples. We demonstrate the interest of our attack across several popular face datasets and GAN training procedures. Notably, we show that even in the presence of significant dataset diversity, an over represented person can pose a privacy concern...

Monsignor Jeffrey Burrill was general secretary of the US Conference of Catholic Bishops (USCCB), effectively the highest-ranking priest in the US who is not a bishop, before records of Grindr usage obtained from data brokers was correlated with his apartment, place of work, vacation home, family members’ addresses, and more.

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The data that resulted in Burrill’s ouster was reportedly obtained through legal means. Mobile carriers sold­ — and still sell — ­location data to brokers who aggregate it and sell it to a range of buyers, including advertisers, ...

The news starkly demonstrates not only the inherent power of location data, but how the chance to wield that power has trickled down from corporations and intelligence agencies to essentially any sort of disgruntled, unscrupulous, or dangerous individual. A growing market of data brokers that collect and sell data from countless apps has made it so that anyone with a bit of cash and effort can figure out which phone in a so-called anonymized dataset belongs to a target, and abuse that information...

I found out that I can visit Waze from any web browser at waze.com/livemap so I decided to check how are those driver icons implemented. What I found is that I can ask Waze API for data on a location by sending my latitude and longitude coordinates. Except the essential traffic information, Waze also sends me coordinates of other drivers who are nearby. What caught my eyes was that identification numbers (ID) associated with the icons were not changing over time. I decided to track one driver and after some time she really appeared in a different place on the same road...