Back in October 2018, a bombshell rocked the tech industry when Bloomberg reported that some motherboards made by Supermicro had malicious components on them that were used to spy or interfere with the operation of the board, and that these motherboards were found on servers used by Amazon and Apple. This is at least in part because some clients have asked Supermicro (and other manufacturers) to move out of China because of security concerns. A few days after the report about Supermicro, they published another separate accusation, this time claiming that the motherboards had Ethernet connectors with malicious hardware inside of them.

But, with Hyper-Threading enabled, users could execute code, such as by visiting a website or running an Android app, that exploits MDS to read sensitive memory contents. Users and customers who process particularly sensitive data on their Chrome OS devices are nonetheless advised to disable Hyper-Threading as a measure of caution. However, uncacheable memory does still move through the store buffers, fill buffers, and load ports;allowing data stored in UC regions to still be leaked via the mechanisms described above.

Attacks on the SHA-1 hashing algorithm just got a lot more dangerous last week with the discovery of a cheap “chosen-prefix collision attack,” a more practical version of the SHA-1 collision attack first carried out by Google two years ago. Two years ago, academics from Google and CWI produced two files that had the same SHA-1 hash, in the world’s first ever SHA-1 collision attack — known as “SHAttered.” Image: Google
SHA-1 chosen-prefix attacks

But last week, a team of academics from France and Singapore has taken the SHAttered research one step further by demonstrating a SHA-1 “chosen-prefix” collision attack, in a new research paper titled “From Collisions to Chosen-Prefix Collisions – Application to Full SHA-1.”

After all, it’s not Customs and Border Protection collecting your facial recognition data directly — it’s the airlines — and they pass it on to the government. A sign allowing U.S. citizens to opt-out of facial scans (Image: Twitter/Juli Lyskawa)

If you’re a U.S. citizen, you can opt out by telling an officer or airline employee at the time of a facial recognition scan. Facial recognition data collected by the airlines on U.S. citizens is stored by Customs and Border Protection for between 12 hours and two weeks, and 75 years for non-citizens.

Sisense announced today that it has acquired Periscope Data to create what it is calling a complete data science and analytics platform for customers. Periscope CEO Harry Glaser says that as his company built a company around advanced analytics and predictive modeling, he saw a growing opportunity around operationalizing these insights across an organization, something he could do much more quickly in combination with Sisense. This is going to drive transformation inside our customers that’s really great for them and turns them into data-driven companies,” Glaser said.

Already in March 2018, it was shown by researchers from Graz University of Technology that an attacker can leak data using Meltdown that is not stored in the L1 cache but in one of the line fill buffers. This proof-of-concept, already described in the Meltdown paper, served as the foundation for subsequent research of these buffers. Now these buffers have been exploited with ZombieLoad and RIDL.

RIDL (Rogue In-Flight Data Load) shows attackers can exploit MDS vulnerabilities to mount practical attacks and leak sensitive data in real-world settings. By analyzing the impact on the CPU pipeline, we developed a variety of practical exploits leaking in-flight data from different internal CPU buffers (such as Line-Fill Buffers and Load Ports), used by the CPU while loading or storing data from memory. We show that attackers who can run unprivileged code on machines with recent Intel CPUs – whether using shared cloud computing resources, or using JavaScript on a malicious website or advertisement – can steal data from other programs running on the same machine, across any security boundary: other applications, the operating system kernel, other VMs (e.g., in the cloud), or even secure (SGX) enclaves.

Your processor resurrects your private browsing-history and other sensitive data. The ZombieLoad attack allows stealing sensitive data and keys while the computer accesses them. While programs normally only see their own data, a malicious program can exploit the fill buffers to get hold of secrets currently processed by other running programs.

Security researchers have found a new class of vulnerabilities in Intel chips which, if exploited, can be used to steal sensitive information directly from the processor.,

The bugs are reminiscent of Meltdown and Spectre, which exploited a weakness in speculative execution, an important part of how modern processors work. Daniel Gruss, one of the researchers who discovered the latest round of chip flaws, said it works “just like” it PCs and can read data off the processor. Intel has released microcode to patch vulnerable processors, including Intel Xeon, Intel Broadwell, Sandy Bridge, Skylake and Haswell chips, Intel Kaby Lake, Coffee Lake, Whiskey Lake and Cascade Lake chips are affected, and all Atom and Knights processors.

We calculated a series of numbers related to standard television homes, compared them to Netflix-only homes and found an interesting trend with regard to how many commercials a streaming-only household can save their children from having to watch:

A study conducted by the University of Michigan found that kids 2-5 spend an average of 32 hours per week in front of a television set. Children 6-11 spend 28 hours in front of a television set (there are some who believe the decrease between brackets is likely due to the slightly older kids now transitioning to phone time). While we couldn’t find any specific data on whether or not a child in a home with standard television versus Netflix-only options watches more YouTube, we’re willing to bet the numbers are probably fairly equal.