Recently, while scrolling through tech news, I noticed that zero-trust architecture is becoming a hot topic. At first glance, the name sounds a bit intimidating: it basically means that no one—internal or external—gets default access to a system; everything requires verification. As a developer, you might think, “Wow, that sounds like a lot of complex verification logic!” And you’d be right. Every aspect—data structures, algorithms, and even hardware implementation—needs to be absolutely secure. This is the challenge of zero trust.
During my exploration of zero-trust systems, I noticed an interesting trend: Rust is not only popular in software development, but it’s also entering the high-assurance hardware design space. In this article, I’ll show you some real-world applications of Rust in zero-trust systems and hardware/software co-assurance, with some practical tools I’ve found useful along the way.
1. Why Zero Trust Requires High-Assurance Languages
The core idea of zero-trust architecture is simple: trust no one by default.
- Every communication requires identity verification
- All data access must be authorized
- Code and system components need rigorous verification
In practice, this means you have to “gatekeep” every component, especially data structures and cryptographic algorithms. A small mistake can create a critical security vulnerability.
Traditionally, high-performance systems are often built in C/C++. Performance is fine, but security vulnerabilities are rampant—most stem from memory management issues: out-of-bounds access, dangling pointers, uninitialized variables… all deadly in a zero-trust context.
This is where Rust shines.
2. What Makes Rust Special
Rust is a modern programming language with three key strengths:
Memory Safety & Type Safety
The compiler checks your memory usage, preventing many common bugs even if you’re careless.Near C/C++ Performance
No garbage collector slowing you down; the compiled binaries are highly efficient.Formal Verification Friendly
High-assurance systems benefit from Rust’s ease of formal analysis or automated verification.
For example, when experimenting with zero-trust systems, I needed to implement a circular queue, which could be used in software or mapped to hardware. In Rust, it looks like this:
#[derive(Copy, Clone)]
struct CQ {
front: usize,
rear: usize,
arr: [i64; CQ_SZ],
}
fn CQ_enqueue(value: i64, mut CObj: CQ) -> (u8, CQ) {
if CQ_isFull(CObj) {
return (CQ_FULL, CObj); // Don't enqueue if full
} else {
if CObj.front == CQ_SZ {
CObj.front = 0;
CObj.rear = 0;
} else if CObj.rear == CQ_MAX_NODE {
CObj.rear = 0;
} else {
CObj.rear += 1;
}
CObj.arr[CObj.rear] = value;
return (CQ_OK, CObj);
}
}
Notice the enqueue function: Rust’s type system and ownership rules prevent accidental out-of-bounds access, making the development experience much safer and smoother than C/C++.
3. Hardware/Software Co-Assurance and High-Assurance Systems
In zero-trust systems, software alone isn’t enough. In scenarios like aerospace, autonomous vehicles, and defense, hardware must also be secure.
Traditionally, developers used Algorithmic C or similar HLS (High-Level Synthesis) languages to write algorithms in a C subset, then synthesize them to hardware. But C inherits many security risks and is hard to formally verify.
Enter Restricted Algorithmic Rust (RAR):
- Inspired by Restricted Algorithmic C (RAC)
- Transpiles RAR code to RAC
- Uses existing hardware/software co-assurance toolchains to verify implementations
Simply put: write algorithms in Rust, run them as software, map them to hardware, and maintain strong safety guarantees.
4. RAR Example: High-Assurance Circular Queue
Implementing a circular queue in RAR looks similar to normal Rust but can be formally verified:
#[derive(Copy, Clone)]
struct CQ {
front: usize,
rear: usize,
arr: [i64; CQ_SZ],
}
fn CQ_hd(CObj: CQ) -> (u8, i64) {
if CQ_isEmpty(CObj) {
return (CQ_EMPTY, 0);
} else {
return (CQ_OK, CObj.arr[CObj.front]);
}
}
RAR code can be automatically converted to ACL2 for mathematical proofs:
(DEFUN CQ_HD (COBJ)
(IF1 (CQ_ISEMPTY COBJ)
(MV (BITS 254 7 0) (BITS 0 63 0))
(MV (BITS 0 7 0)
(AG (AG 'FRONT COBJ) (AG 'ARR COBJ)))))
This level of formal verification is almost impossible in traditional C/C++.
5. Crypto Primitives in Zero-Trust Systems
Zero-trust systems rely on data security, making cryptography essential. The research team ported the Monocypher crypto library to RAR, including:
- Blake2b hashing
- Symmetric encryption XChacha20 + Poly1305
- Public-key algorithm X25519
After porting, security is guaranteed without significant performance loss.
In short: writing zero-trust cryptography in Rust/RAR gives you type safety, memory safety, and high performance simultaneously.
6. Practical Takeaways for Developers
From a developer’s perspective:
Rust is approachable
Master ownership, borrowing, and basic type rules, and you can quickly write safe code.Hardware/software co-assurance works
The Plexi + RAC + ACL2 toolchain automatically maps software algorithms to hardware and enables formal verification.Modern development experience
Compared to C/C++, the compiler catches low-level bugs for you, boosting productivity.
If you want to quickly set up a similar experiment, consider using ServBay. I personally use it for Rust/HLS testing: deployment is easy, all data stays local, and it’s perfect for zero-trust prototype development.
7. Conclusion
- Zero-trust requires high assurance at every step
- Rust provides type safety, memory safety, and modern performance
- RAR allows Rust to be used for hardware/software co-assurance, ideal for high-security, low-latency systems
- Cryptography and data structures can be formally verified
- For developers, Rust + RAR + ServBay is a combination worth exploring
In summary, if you’re interested in zero-trust systems, embedded security, or high-assurance computing, Rust is no longer just a “software language”—it’s part of a complete hardware/software co-assurance ecosystem.
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