Buffer Overflow Attack: Causes, Prevention and Detection

A buffer overflow attack occurs when a program writes more data into a fixed-size memory buffer than the buffer was allocated to hold. The extra bytes spill into adjacent memory locations, overwriting data, pointers or return addresses stored there. If an attacker controls the content of that overflow, a buffer overflow attack can be used to crash a service, corrupt data or redirect program execution towards code of the attacker’s choosing.

The vulnerability behind these attacks is covered by CWE-119, with related classifications including CWE-120, CWE-121 and CWE-122. It has been documented since the earliest large-scale internet worm outbreaks, including the Morris Worm. It remains on CISA’s list of vulnerability classes that manufacturers are urged to eliminate at the design stage, according to the February 2025 Secure by Design Alert on buffer overflow vulnerabilities, jointly published by CISA and the FBI. Decades after it was first weaponised, a buffer overflow attack is still a routine finding in penetration tests against C and C++ codebases, embedded firmware and legacy network services.

How a Buffer Overflow Attack Works

A buffer overflow is a fascinating but hazardous aspect of programming. Upon execution, a program allocates portions of memory called buffers in which to temporarily store data while it is processing information. These buffers are capable of holding all sorts of things, such as usernames, file paths or even network packets. In languages such as C and C++, in which programmers have to handle memory manually, it is important to make certain that any incoming data fits exactly within the buffer before it is written to it.

But if that important check is ignored or carried out incorrectly, a buffer overflow attack may take place. In this case, the attacker sends input which exceeds the buffer’s boundaries. This extra information can overflow and overwrite adjacent memory that may contain another variable, a saved register or even a return address which indicates where the program should go after a function has finished. If the attacker is able to alter this overwritten data, they might be able to redirect the program’s execution so as to run their own code.

Buffer overflows usually aim at two main sections of memory, the stack and the heap. The method by which they operate and the techniques employed to exploit them can differ greatly between these two areas, which is the reason why they are generally regarded as separate types of vulnerability.

Stack-Based Buffer Overflow Attack

A stack-based buffer overflow attack focuses on the call stack, which is the area of memory used to keep track of function calls, local variables and return addresses. Since the return address is stored right after the local buffers in the stack, it is possible for overflowing one of these buffers to cause the return address to be overwritten. CWE-121 describes this kind of vulnerability. Standard advice on secure coding has always recommended against using C functions such as strcpy() and gets() since these are the methods most frequently involved in such attacks in practice, as the functions copy data into a destination buffer without knowing anything about the actual size of that buffer.

Attacks of this type are more common than the other kind, mainly because the stack’s predictable arrangement makes it easier to exploit after an attacker has found a vulnerable function.

Heap-Based Buffer Overflow Attack

A heap-based buffer overflow attack instead focuses on memory that has been allocated dynamically at runtime, for example, using malloc() in C, this type of attack is covered by CWE-122. Rather than directly overwriting the return address, a heap-based buffer overflow attack usually corrupts the heap metadata, adjacent objects or function pointers stored on the heap, all of which the program later dereferences or executes. Since heap layouts are less predictable than those on the stack, exploitation generally requires more effort. Nevertheless, heap-based buffer overflow attacks are common in browsers, image parsers and other software which processes large quantities of untrusted, variable-length input.

Common Causes of Buffer Overflow Vulnerabilities

A buffer overflow vulnerability rarely stems from a single mistake. It is usually the product of a few recurring patterns:

  • Unsafe standard library functions: Functions such as strcpy(), strcat(), sprintf() and gets() do not adequately check whether the destination buffer is large enough for the data being copied into it. CWE-120 refers to this as the “classic” buffer overflow.
  • Missing or incorrect bounds checks: A developer may check the size of a buffer once and then reuse it later in the code without re-validating the length, particularly after the buffer has been resized or reused in a loop.
  • Off-by-one errors: These occur when loop conditions allow an index to reach the buffer’s size instead of stopping one element earlier. This can result in a byte being written past the allocated region, potentially corrupting adjacent memory.
  • Unsafe parsing of untrusted input: C and C++ give developers direct control over memory but do not provide built-in memory safety or automatic bounds enforcement. As a result, buffer overflow vulnerabilities are more commonly associated with code written in these languages than with memory-safe languages such as Rust, Go or Java.
  • Integer overflow in buffer size calculations: When an integer overflow affects the calculation of a buffer’s required size, a seemingly correct bounds check can still result in a buffer being allocated with less space than the amount of data intended to be stored.

These coding weaknesses can leave applications exposed to memory corruption, making it important to understand how buffer overflow vulnerabilities have been exploited in real-world attacks.

Real-World Buffer Overflow Attack Examples

Buffer overflow attacks are not a theoretical concern for security teams. Several of the internet’s most disruptive incidents trace back to exactly this weakness class:

  • The Morris Worm exploited a buffer overflow in the Unix fingerd service, one of the earliest documented uses of the technique and a case study still referenced in university security courses.
  • Code Red exploited a buffer overflow in the Indexing Service, an ISAPI extension (idq.dll) installed by default alongside Microsoft’s IIS web server, spreading across an estimated hundreds of thousands of systems within days.
  • SQL Slammer exploited a stack-based buffer overflow in SQL Server 2000’s Resolution Service, a companion service that listened on UDP port 1434 rather than the database engine’s main query path, generating enough scanning traffic to degrade internet routing performance in parts of the world.

The pattern connecting all three incidents above is the same, unchecked input, an unmanaged memory language and a vulnerable function sitting on a network-facing input path.

Business Impact of a Buffer Overflow Attack

A buffer overflow attack creates a fairly short list of operational risks. Remote code execution lets an attacker run arbitrary code with the permissions of the affected process, sometimes extending to elevated privileges depending on how that process was configured. Even a failed exploitation attempt often crashes the target process, taking down a customer-facing service or a piece of internal infrastructure until someone restarts it. 

Where the buffer overflow attack corrupts memory holding session tokens, credentials or customer data, that data can be exposed or manipulated before the process crashes. And in regulated environments, an unpatched buffer overflow vulnerability touching HIPAA, GDPR or PCI DSS data creates its own compliance exposure, since these frameworks expect organisations to remediate known, exploitable weaknesses within a reasonable timeframe.

A single crashed customer-facing service or one exposed credential pulled from corrupted memory, is enough to trigger a full incident response process. Neither needs anything close to total system compromise to get expensive.

How to Prevent a Buffer Overflow Attack

Preventing a buffer overflow attack is best addressed at several layers, since no single control catches every variant.

Secure Coding Practices

The most durable fix is to stop the vulnerable pattern from being written in the first place. Established secure coding guidance for C recommends replacing unbounded functions like strcpy() with length-aware alternatives such as strncpy(), validating every buffer size before a copy operation and treating all externally supplied input as untrusted until it has been checked. Static application security testing (SAST) tools integrated into the CI/CD pipeline can flag many of these patterns automatically, before code reaches production.

Memory-Safe Languages

Where feasible, rewriting high-risk, network-facing components in a memory-safe language removes the buffer overflow attack surface at the language level rather than relying on developer discipline. Independent analyses of memory safety vulnerabilities and public commentary on systems programming have both pointed towards languages like Rust as a structural mitigation, since the language enforces bounds checking and ownership rules at compile time.

Runtime Protections

Where legacy C or C++ code cannot be rewritten in the short term, several operating system and compiler-level protections raise the cost of exploitation:

  • Address Space Layout Randomisation (ASLR) randomises the memory addresses of key program regions, making it harder for an attacker to predict where their injected code will land.
  • Data Execution Prevention (DEP/NX) marks memory regions used for data as non-executable, so code smuggled in through a buffer overflow attack cannot simply be run from the stack or heap.
  • Stack canaries place a known value between a buffer and the return address, so the program can detect that a stack-based buffer overflow attack has occurred before the corrupted return address is used.
  • Compiler hardening flags, such as GCC’s -fstack-protector and -D_FORTIFY_SOURCE, catch a meaningful share of classic buffer overflow patterns at compile time.

CWE’s own mitigation guidance is blunt about the limits here: most compiler and operating system protections cover only part of the problem. Secure coding, memory-safe rewrites and runtime protections work best layered together, not treated as substitutes for one another.

Buffer Overflow Risk in AI-Generated Code

AI coding assistants have introduced another consideration for buffer overflow risk within the SDLC. AI-generated code may contain known vulnerability patterns, particularly when code involves languages such as C that require developers to manage memory directly. Generated code can also require additional review to ensure that it follows secure coding practices across different models and development tasks. As organisations increasingly use AI coding assistants, reviewing the security of generated code can help identify potential weaknesses before they reach production. 

The potential risk is partly related to the code patterns available in the data used to develop language models. If generated suggestions reproduce unsafe memory-handling patterns, those suggestions may require additional validation before being incorporated into an application. For organisations adopting AI coding assistants, treating generated code as code that requires the same security review as other contributions can help reduce the possibility of buffer overflow vulnerabilities passing through the development process. The following SDLC adjustments can help address this risk:

  • Treat AI-generated code as untrusted input to the review process, not as a finished contribution. Every AI-suggested function that touches a buffer, a fixed-size array or a memory copy should get the same scrutiny as code written by a new, unvetted contributor.
  • Run SAST and memory-safety linters on every AI-generated commit, not just human-authored ones. Static analysis catches the classic unchecked-copy pattern regardless of who or what wrote it.
  • Add buffer-overflow-specific prompts and constraints to code generation workflows, such as requiring length-checked functions and explicit bounds validation. Prompting can help guide AI-generated code toward safer memory-handling practices, but generated code should still undergo appropriate security review and testing before being used in production.
  • Prefer AI-assisted development in memory-safe languages for new, network-facing components, so an imperfect suggestion from the model cannot introduce a classic buffer overflow attack at the language level.
  • Align the review gate with NIST’s Secure Software Development Framework (SSDF), which expects organisations to verify third-party and AI-assisted code against the same secure coding requirements applied to code written in-house, rather than granting it an exception because a human did not type it.

Defending Against Buffer Overflow Attacks with XDR, Firewalls and YARA Rules

Secure coding and memory-safe rewrites reduce how often a buffer overflow vulnerability reaches production. Defensive security products are what catch exploitation attempts against the vulnerabilities that get through anyway and organisations already running XDR, next-generation firewalls or YARA-based detection have several levers available.

  • Network-based intrusion prevention: Next-generation firewalls built on signature-based intrusion prevention engines ship with rules written specifically to catch buffer overflow attack patterns in transit, such as rules that flag an abnormally long URI in an HTTP request or oversized packets in protocols like SSH, both common entries in publicly maintained intrusion detection rule sets. Pointing these IPS signature sets at internet-facing services gives a security team a layer that blocks known exploitation patterns before they reach the vulnerable application.
  • Endpoint exploit prevention: Many endpoint protection platforms include a dedicated exploit prevention engine that groups memory corruption techniques, including stack and heap buffer overflows, integer overflows and use-after-free conditions, into a protected process list and blocks the technique itself rather than waiting for a known malware signature. This kind of behavioural, technique-level blocking matters because it can stop a buffer overflow attack against a vulnerability that has not yet been assigned a CVE.
  • XDR correlation: A single buffer overflow attack rarely stays isolated to one host. XDR platforms add value by correlating a crashed or anomalous process on an endpoint with related network telemetry, such as an unusual outbound connection immediately following the crash and surfacing that correlated chain as one incident instead of several disconnected alerts. That correlation shortens the time a security team needs to confirm whether an exploitation attempt actually succeeded.
  • YARA rules for pattern-based detection: YARA rules are well suited to catching the byte-level artefacts of a buffer overflow attack, such as known shellcode sequences, NOP sled patterns used to pad an exploit’s landing zone or the specific payload signatures tied to a public exploit for a named CVE. Threat hunting and EDR teams typically pair YARA rules against memory dumps or suspicious files with the vendor’s built-in exploit prevention engine, since YARA catches artefacts the vendor’s own signatures have not yet been updated to cover, particularly for a newly published proof-of-concept.

Fixing the underlying buffer overflow vulnerability in the code is still the actual fix. These controls buy time and visibility while a vendor patch is pending, which is exactly the role layered defence is meant to play in a security programme.

Detecting a Buffer Overflow Attack in Production

Prevention reduces the attack surface, but detection matters for the vulnerabilities that slip through. Fuzz testing, which feeds a program large volumes of malformed and oversized input, remains one of the most effective ways to surface buffer overflow vulnerabilities before release. In production, a web application firewall can block many exploitation attempts against web-facing services, while endpoint detection and response tooling can flag the anomalous process behaviour, such as an unexpected child process or a jump to non-executable memory, that often follows a successful buffer overflow attack.

Security teams evaluating third-party software should also treat CWE-119, CWE-120, CWE-121 and CWE-122 classifications in a vendor’s CVE history as a meaningful signal. A vendor with a recurring pattern of buffer overflow vulnerabilities across releases is telling security teams something about the maturity of its secure development lifecycle, independent of any single CVE’s severity score.

Conclusion

Buffer overflow attacks remain a significant security concern because a simple memory-handling error can lead to crashes, data corruption or arbitrary code execution. Although secure coding practices, memory-safe languages, compiler hardening and runtime protections can reduce exposure, no single control addresses every risk. Fuzz testing, SAST, endpoint protection, network monitoring and layered detection can help identify or block exploitation attempts before they develop into larger incidents.

As software increasingly incorporates third-party components and AI-generated code, addressing buffer overflow risk requires security to be considered throughout the software development lifecycle. Treating externally supplied and AI-generated code as untrusted, validating memory operations, prioritising memory-safe development and maintaining timely patching can reduce the likelihood of these vulnerabilities reaching production. A layered approach that combines secure development with runtime and detection controls provides a stronger foundation for reducing the impact of a buffer overflow attack.

SECNORA helps organisations find buffer overflow and other memory-safety vulnerabilities before attackers do – testing your codebase and network-facing services through manual penetration testing and secure code review. Talk to our team.

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