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One free scan finds every outdated or missing driver and matches the right update for your exact hardware.Free scan · exact hardware matchMemory-safe programming uses language and runtime rules to prevent invalid memory operations, such as reading or writing beyond a buffer or using an object after its memory has been freed. Preventing these errors removes an important class of vulnerabilities, but it does not make software secure by itself: logic flaws, authorization mistakes, insecure configuration, and vulnerable dependencies still require attention.
What memory safety means
Programs use memory to store data and the objects they work with. Memory safety is about controlling how software accesses that memory and manages its lifetime. A memory-safe language or runtime restricts operations that could read, change, or reuse memory incorrectly.
This is one part of software correctness and security, not a synonym for either. A program can be memory-safe and still make the wrong decision, grant access to the wrong user, or rely on an insecure dependency.
Which vulnerabilities can memory-safe programming prevent?
Buffer overflows
A buffer is a region of memory intended to hold data. A buffer overflow happens when code reads or writes beyond that region’s valid bounds. Depending on the program and conditions, the result can be a crash, corrupted state, exposed information, or an opportunity to alter execution.
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Use-after-free and double-free
A use-after-free occurs when code continues to use an object after its storage has been released. A double-free happens when software attempts to release the same memory more than once. Both can leave a program in an unsafe state and may be exploitable.
Uninitialized memory
Using memory before it has been given a valid value can cause unpredictable behavior or expose data that should not be available. The exact consequences depend on how the software uses the memory and what information it contains.
The NSA has warned that poor memory management can allow malicious actors to access sensitive information or achieve unauthorized code execution. In its November 10, 2022 release, the NSA reported that Microsoft and Google each said memory-safety issues were behind around 70 percent of their vulnerabilities. That is a figure attributed to those companies, not a universal estimate for all software. Read the NSA release.
How languages enforce memory safety
Different languages use different mechanisms. Some check array bounds at runtime or manage object lifetimes automatically. Rust uses ownership and borrowing rules to enforce many memory-safety conditions at compile time. NIST says Rust’s model provides compile-time memory and thread safety without requiring a garbage collector, and that Rust makes unsafe operations explicit. The word “memory-safe” therefore does not mean every language uses a garbage collector or a Rust-style borrow checker.
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Fix the driver behind crashes, sound loss and screen glitchesFind Drivers →Repair Windows errors before they cause bigger problemsFix Now →A 2025 NSA/CISA information sheet lists Ada, C#, Delphi/Object Pascal, Go, Java, Python, Ruby, Rust, and Swift as examples of memory-safe languages. Their designs and protections differ; the relevant question for a project is what operations its language, runtime, and toolchain actually constrain. See the NSA/CISA information sheet.
Memory safety is not an absolute guarantee across every part of a program. For example, Rust includes an explicit unsafe mode, and software may interact with code written in other languages. Such boundaries need deliberate review and testing. NIST’s overview discusses Rust, Ada, safer language subsets, and approaches for avoiding classes of software weaknesses. NIST: Safer Languages.
What memory-safe programming does not prevent
Memory-safe languages target defects caused by invalid memory access or management. They do not automatically prevent flawed business logic, broken access controls, insecure defaults, or vulnerabilities in third-party components. Nor does selecting a language eliminate the need to test code, review changes, manage dependencies, and configure systems securely.
The NSA recommends using memory-safe languages when possible, alongside hardening measures such as compiler settings, tools, and operating-system configuration. NIST’s Secure Software Development Framework (SSDF) provides a broader set of practices for integrating security into a software life cycle, reducing vulnerabilities, and limiting the impact of exploitation. Read NIST SP 800-218, SSDF Version 1.1.
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How teams can adopt memory-safe practices
Prioritize the components with the greatest exposure
Inventory software that parses complex files, processes untrusted input, handles network requests, or runs with high privileges. Consider known defects and the likely impact of a memory error when choosing where to focus first.
Choose an approach that fits the project
For new code, consider a memory-safe language or a safer subset supported by the project’s platform and tools. Assess performance needs, interoperability with existing components, available staff skills, and any unsafe or foreign-function boundaries. A language’s label alone does not settle whether a particular system is protected.
Plan legacy transitions in stages
Replacing an established system all at once may be impractical. Teams can prioritize high-risk components, build skills and tooling, and plan a sequence for introducing safer code while maintaining the existing product. CISA’s 2023 roadmap resource is intended to help manufacturers plan and publish transitions to memory-safe languages; it is a planning aid, not a claim that migration is immediate or cost-free. CISA: The Case for Memory Safe Roadmaps.
Keep broader defenses in place
During adoption and afterward, continue code review, testing, dependency management, and hardening. Language choice can prevent some defects at their source; secure development practices address the wider set of ways software can fail.
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