Miguel Ojeda, who wrote the particle gas pedal software for the Large Hadron Collider and worked on security for programming languages, will reportedly be writing parts of the Linux kernel in Rust. Google will pay for the contract through the nonprofit organization Internet Security Research Group.

Adding modules written in Rust to the Linux kernel is expected to reduce the likelihood of vulnerabilities caused by insecure memory handling. At the time of its release in 1991, Linux was written in C, a language which is more vulnerable than modern programming languages. Linux kernel creator Linus Torvalds has said he is ready for a change if the value of using Rust for Linux is proven. So far, Ojeda has proposed 13 changes, which are necessary to run Rust modules on Linux.

Google thanked the Linux community programmers who are working on this project. “The community has already done and continues to do a great job of adding Rust support to the Linux kernel,” Google said in a statement.

As for the Rust language, it was developed by Mozilla, but is currently being developed by the nonprofit Rust Foundation. It pays special attention to secure memory handling. Microsoft’s security division stated back in 2019 that “Rust represents the best alternative to C and C++.”

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The new product is called GitHub Copilot. The tool uses source code uploaded to the GitHub code-sharing service, which Microsoft acquired in 2018. Open AI, an artificial intelligence research startup, participated in the implementation. Microsoft invested $1 billion in it in the summer of 2019.

Researchers at Microsoft and several other companies have been trying for decades to teach computers to write their own code. GitHub Copilot is a big step in that direction. The product relies on a large amount of code in many programming languages and Azure’s enormous computing power. Nat Friedman, CEO of GitHub, says GitHub Copilot can almost completely replace a programmer’s partner. The tool looks at existing code and comments on it, as well as the location of the cursor, and suggests adding one or more lines depending on the context. As the programmer accepts or rejects the suggestions, the model learns and becomes much more sophisticated and intelligent over time.

Friedman says the GitHub Copilot significantly speeds up programming. Hundreds of developers on GitHub, he says, have already appreciated the product’s capabilities and don’t shut it down all day long.

Experts point out that the main advantage of GitHub Copilot is that it saves the programmer from having to study piles of documentation, thereby saving precious hours. Copilot is reported to work best with JavaScript, Python and TypeScript at the moment. The tool will initially appear in Microsoft Visual Studio Code, a free open-source product, before the company plans to include it in a commercial version of Visual Studio.

Open AI co-founder Greg Brockman says the Codex model behind GitHub’s Copilot is a descendant of the powerful GPT-3 model, which the company’s experts have trained on many terabytes of publicly available code. Copilot, according to GitHub staff, has a number of security mechanisms built in, giving confidence that the product will generate high-quality code. Microsoft reportedly plans to release a version of the product in the future that companies can train to understand their own programming styles. For now, Microsoft offers a service that is only trained on code stored in publicly available repositories.

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The rules will begin to apply to all developers who agree to participate in the program. Detailed registration instructions and forms can be found on the Google website. Under the terms, developers will be required to deduct a 15% commission (instead of 30%) until their products have earned one million dollars within a year. If that happens, the company will raise the fee to the standard 30%. The offer applies to companies, not individual apps. If there are multiple linked accounts, the amount will be calculated from the income of all accounts. Once that barrier is reached, the fee will change for everyone.

The rules will take effect July 1, 2021. Due to the fact that they start in the middle of the year, the total barrier will be reduced to $500 thousand.

In addition, the IT-giant has launched a support program called Play Media Experience, which will reduce the commission to 15% for developers of media products and services. Only those who meet a number of criteria will be allowed to participate in the program:

• Provide access to media files that are not created by users;
• Have more than 100 thousand downloads in Play Market;
• A quality interface and a high rating in the store;
• High rating of the developer account;
• Integration of Google platforms: Android TV, Google TV, and others.

There are certain content requirements for participants:

• Books. Premium books, audiobooks and comics. Support for WearOS and Android Auto. Optimization for tablets and folding devices;
• Video. Movies, shows, live sports broadcasts. Support for Android TV, Google TV, and Google Cast with multi-platform playback is required;
• Audio. Premium music and subscription option. Support for Android Auto, Google Cast, Wear OS and Android TV, with playback across platforms.

Google did not give a launch date for the latter. The company also promised to reveal the changes for game developers at a special conference from July 12 to 13

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According to Qichacha analysts, China now has 439,000 registered AI-related companies. In 2020, the number of new organizations in the field of AI was 172 thousand, and in the first half of 2021 such organizations were registered another 153 thousand. Thus, the growth of registrations for the year was 150.8%, and the year is not over yet!

The transition from 2019 to 2020 showed an increase in the number of new AI companies in China at 292.8%, and 2021 promises to be even more “fruitful” for the field of AI in China.

The issue of finance is extremely interesting. Most Chinese AI companies declare quite large share capital. Apparently, local investors are willing and invest a lot of money in AI development. For example, companies with registered capital of less than 1 million yuan ($155,000) account for only 24% of the registered companies, while those with registered capital between 1 and 5 million yuan account for 39%, and those with capital over 5 million yuan (from $755,000 and more) account for 37%.

It is also interesting to note that the most AI companies in China are registered in three neighboring provinces on the southeast coast of the country: Guangdong, Jiangsu and Zhejiang. There are 64,000, 50,000 and 40,000 AI companies in each, respectively. Programmers have always been drawn to the south and to the sea, which in the case of Chinese regional development programs is further supported by subsidies for provincial economic development.

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Among the exotic programming languages for writing malware are Go (Golang), D (DLang), Nim and Rust. As a rule, these languages are used to create malicious software aimed at large organizations and which exploits weaknesses in the protection of the corporate infrastructure. We are talking about malware that implements multi-stage, carefully planned and organized cyber-attacks.

Once on the victim’s computer, these software modules bypass traditional defenses to later download, decode and launch remote access Trojans, most often Remcos and NanoCore, as well as Cobalt Strike beacons.

In some cases, when the cybercriminals have sufficient resources, non-standard languages for these purposes are used not only for the modules performing the initial attack, but also for the whole malware package. The Go language is of particular interest to attackers. It is used by hackers on an almost regular basis for all major platforms.

According to the authors of the study, new or unusual programming languages make it difficult to decompile malware, circumvent defenses that use signature-based detection tools with relative ease, and simplify cross-platform compatibility of attacks. The code base of such malware itself is an additional level of disguise. Their developers, in fact, do not have to make any extra effort; the effectiveness of the attack is increased simply by the fact that one of these programming languages is used.

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