Carding Forum
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The project will help eliminate critical vulnerabilities.
DARPA is accelerating the transition to memory-safe programming languages with the TRACTOR project, which aims to automatically convert C code to Rust. This project develops machine learning tools to automate the translation of legacy C code to Rust.
Memory security is one of the main causes of vulnerabilities in large codebases. DARPA hopes that AI models will help translate programming languages to make software more secure.
Tech giants such as Google and Microsoft have been warning about issues related to memory security bugs for several years, and have called for the use of programming languages that do not require manual memory management, such as Rust. This has attracted the attention of government agencies such as the White House and the U.S. Cybersecurity and Infrastructure Agency (CISA), which now recommend using memory-safe programming languages, including Rust, C#, Go, Java, Python, and Swift.
Adherents of C and C++ argue that proper compliance with ISO standards and the use of testing tools can produce comparable results. However, DARPA believes that memory security issues in these languages remain relevant.
Rust, released in 2015, provides memory security and is suitable for system programming that requires high performance. The language has become popular thanks to initiatives such as the Prossimo project, which aims to rewrite mission-critical code, including the Network Time Protocol (NTP) daemon, in Rust to reduce security risks.
The TRACTOR project is also attracting attention in the private sector. For example, the company Code Metal, which is engaged in converting code for hardware, considers the DARPA project promising and timely. However, automated code translation remains a challenge, especially because of the features of working with pointers in C, which are prohibited in Rust.
DARPA will host an event for those who plan to submit proposals for the TRACTOR project on August 26, 2024. Participants must register before August 19 .
Source
DARPA is accelerating the transition to memory-safe programming languages with the TRACTOR project, which aims to automatically convert C code to Rust. This project develops machine learning tools to automate the translation of legacy C code to Rust.
Memory security is one of the main causes of vulnerabilities in large codebases. DARPA hopes that AI models will help translate programming languages to make software more secure.
Tech giants such as Google and Microsoft have been warning about issues related to memory security bugs for several years, and have called for the use of programming languages that do not require manual memory management, such as Rust. This has attracted the attention of government agencies such as the White House and the U.S. Cybersecurity and Infrastructure Agency (CISA), which now recommend using memory-safe programming languages, including Rust, C#, Go, Java, Python, and Swift.
Adherents of C and C++ argue that proper compliance with ISO standards and the use of testing tools can produce comparable results. However, DARPA believes that memory security issues in these languages remain relevant.
Rust, released in 2015, provides memory security and is suitable for system programming that requires high performance. The language has become popular thanks to initiatives such as the Prossimo project, which aims to rewrite mission-critical code, including the Network Time Protocol (NTP) daemon, in Rust to reduce security risks.
The TRACTOR project is also attracting attention in the private sector. For example, the company Code Metal, which is engaged in converting code for hardware, considers the DARPA project promising and timely. However, automated code translation remains a challenge, especially because of the features of working with pointers in C, which are prohibited in Rust.
DARPA will host an event for those who plan to submit proposals for the TRACTOR project on August 26, 2024. Participants must register before August 19 .
Source
