What is a buffer overflow?
A buffer overflow is a well-known type of memory corruption vulnerability. When a program tries to write more data into a buffer (a temporary storage space) than it was allocated, the excess data “overflows,” overwriting adjacent memory locations.
This isn't a new flaw; buffer overflows have been around for decades. But they remain a dangerous and relevant threat, even in modern applications and systems. In the cloud, buffer overflow attacks can target services like web APIs or applications running in containers.
Two out-of-bounds access vulnerabilities CWE Top 25 Most Dangerous Software Weaknesses list for 2024: CWE-787 (Out-of-bounds Write) and CWE-125 (Out-of-bounds Read). Not every vulnerability is actually exploited in the wild, of course. But a recent buffer overflow zero-day vulnerability wound up compromising nearly 50,000 Cisco firewalls.
Buffer overflow vulnerabilities are usually a result of flawed coding practices—specifically, when a programmer fails to properly perform bounds checking. This issue is especially common in older languages like C and C++, which don't automatically prevent a program from writing past the buffer's end.
That means it’s your responsibility to mitigate buffer overflow vulnerabilities. After all, the shared responsibility model stipulates that you’re responsible for your own code, images, and configurations and for patching your own compute like VMs, containers, and functions. Since a buffer overflow vulnerability is in your code, the cloud provider isn't responsible for securing your apps.
So how do you keep yourself safe? Secure coding practices paired with context-based prioritization. Given the volume of security alerts, it’s essential to prioritize remediation based on identity and exposure context (aka real risk). For instance, an internet-exposed service that has an out-of-bounds write in a library and is running with an overprivileged role represents a much higher risk than a similar flaw in a service that’s only accessible internally.
This context is what separates a manageable workload from security chaos. As we’ll explore in this blog post, a major part of keeping your environment secure from buffer overflow vulnerabilities includes choosing tools to automate and streamline security processes and prioritization.
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How buffer overflow attacks work
A buffer overflow attack starts when an attacker sends oversized input that causes a program to write data beyond a buffer's end. Once this succeeds, the attacker can send an overflow payload designed to hijack the application's execution flow.
In classic exploits, this payload has two parts: the malicious code (often called shellcode) that the attacker wants to execute and a modified return address. When the oversized input is processed, the data overwrites the program's original return address with the new one supplied in the payload. This ultimately redirects the program's execution to the attacker's shellcode, resulting in remote code execution (RCE).
Modern exploits frequently avoid direct shellcode injection to evade defenses like data execution prevention (DEP), which marks memory regions as non-executable; and address space layout randomization (ASLR), which randomizes the location of key memory areas.
To get around this, attackers use more advanced techniques like code-reuse attacks in an attempt to compromise modern applications. Code-reuse attacks work by chaining together small, existing code snippets (gadgets) from the program's memory or libraries. Common variants include Return-Oriented Programming (ROP) and Jump-Oriented Programming (JOP), which bypass DEP by executing legitimate code sequences in malicious order. Related techniques may exist depending on the platform and toolchain, but ROP and JOP represent the most widely documented approaches.
Why do you need defense in depth?
Because modern attacks are so complex and designed to bypass individual controls like DEP and ASLR, no single set of controls yields a "complete defense" against these evolving threats. A defense-in-depth strategy is required. This means implementing layers of control, starting with choosing memory-safe languages like Rust or Go and using safer APIs when working in C/C++ (avoiding functions like strcpy()). You should also use compiler hardening techniques like stack canaries and integrate tools for fuzzing and sanitizers (like ASan) in the build process.
Deploying with least-privilege runtime hardening also minimizes the damage of an exploit. With least privilege in place, even if an attacker achieves RCE, their ability to escalate privileges or pivot easily to other systems is severely limited.
Finally, because attackers will always find new zero-day vulnerabilities and bypass techniques, continuous detection and response ensures that security teams can quickly spot and contain anomalous behavior, completing the security loop.
Compliance control mapping
| Framework | Relevant controls | Buffer overflow prevention alignment |
|---|---|---|
| ISO 27001 | A.14.2 (Secure development), A.8.28 (Secure coding) | SAST/DAST in SDLC, code review, hardening flags |
| SOC 2 | CC7.1 (Change management), CC7.2 (System monitoring) | Pipeline gates, runtime monitoring, vulnerability management |
| NIST SP 800-53 | SA-11 (Developer testing), SI-10 (Information input validation) | Fuzzing, sanitizers, bounds checking, input validation |
| CIS Benchmarks | Linux/container hardening sections | ASLR/DEP enablement, minimal capabilities, read-only filesystems |
Types of buffer overflow attacks in modern environments
Buffer overflow attacks generally fall into three main categories: stack-based, heap-based, and integer overflows. Understanding these attack types is essential for effective defense.
Stack-based buffer overflow attacks
This is the most common type of buffer overflow attack. It targets local variables, meaning data stored on the program's call stack.
CVE-2025-32756 is a recent stack-based buffer overflow attack example in several Fortinet products. This threat received a CVSS score of 9.8 due to its critical nature: A remote, unauthenticated adversary can execute arbitrary code simply by submitting a malformed HTTP request to the affected system.
Heap-based overflow attacks
In this kind of attack, a threat actor seeks to corrupt the heap metadata, enabling them to control how memory is allocated and potentially leading to arbitrary code execution. Because these attacks target dynamically allocated memory, they’re generally more complex to carry out than stack-based attacks.
One example of a heap-based buffer overflow vulnerability is CVE-2023-38545 in cURL, which also received a CVSS score of 9.8. This vulnerability occurs during the SOCKS5 proxy handshake when a hostname exceeds the size of a dynamically allocated buffer on the heap. This can crash the program or, in some cases, enable RCE.
Integer overflow attacks
Attackers can use this third method to trigger a buffer overflow by abusing logic checks. An integer variable is assigned a value that is too large, causing an overflow that makes the integer value wrap around (or roll over) to a small, unexpected number. This tricks the program's logic into allocating a buffer that is too small for an upcoming copy operation. The subsequent copy—of an unexpectedly large value—then causes the buffer to overflow.
A notable example is CVE-2025-49710, an integer overflow found in the OrderedHashTable component of Firefox's JavaScript engine. This flaw was also assigned a CVSS score of 9.8.
How do buffer overflow vulnerabilities impact cloud applications?
There are two main areas of concern when it comes to buffer overflow vulnerabilities. First, many legacy applications are inherently susceptible to buffer overflow attacks because of the older languages they were coded in. Second, modern cloud-native apps create massive scale and visibility challenges, even when they’re coded in a more secure language.
Many legacy applications written in C or C++ are simply hoisted into the cloud in a “lift-and-shift” operation, bringing their vulnerabilities right along with them. As we’ve seen, these languages are susceptible to buffer overflows because they lack built-in bounds checking, meaning they won’t automatically stop the program from writing past the buffer's end like modern languages like Rust and Go do.
Because of the scale and distributed nature of the cloud, these vulnerabilities can vastly enlarge the overall cloud attack surface. A single memory-safety bug in a shared library can instantly affect thousands of applications and services, introducing severe vulnerabilities to core components. For instance, a buffer overflow in a container runtime can be exploited to achieve a container escape, or a vulnerability in a cloud control plane API could be used for privilege escalation. That’s why you need to focus on hardening your images, runtimes, and orchestrator settings to reduce the blast radius.
Remember: According to the shared responsibility model, these flaws, which affect workload and host isolation within the customer environment, are your responsibility alone (breaches of the cloud provider's control planes are rare and are handled by the providers themselves).
Finally, these types of flaws introduce significant compliance and regulatory concerns. An unpatched, high-severity vulnerability like a buffer overflow can seriously impact your ability to stay compliant with regulatory mandates like PCI DSS, HIPAA, and FedRAMP.
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Buffer overflow prevention and mitigation strategies
It’s essential to take a layered, strategic approach to mitigating buffer overflows. Defense in depth focuses on three main areas: secure coding practices, compiler and OS defenses, and network-based defenses.
Secure coding practices
CISA and the FBI recently called buffer overflow vulnerabilities "unforgivable defects" and warned developers to use secure coding practices to eliminate these vulnerabilities. Here are a few ways to achieve this:
Shift security left to prevent vulnerabilities from ever getting into your code base.
Adopt memory-safe languages like Rust or Go that have built-in protections. Rust, for example, enforces strict memory safety rules at compile time. Go automatically manages memory and performs bounds checks on array and slice access.
If you must use C or C++ (such as for legacy apps), prioritize size-aware functions for all copy operations. Avoid insecure functions like strcpy() and use alternatives like snprintf(), strnlen(), and memmove() with validated lengths.
Enable compiler hardening flags, including -fstack-protector-strong, -D_FORTIFY_SOURCE=2, and PIE/RELRO. For advanced checks, consider Control-flow integrity (CFI), such as Clang CFI.
Beyond manual coding checks, implement code-to-cloud guardrails. This means integrating security checks into your developer workflows using IDE/PR checks, pipeline policies, and image signing enforcement.
Further best practices for secure coding include implementing static/dynamic analysis and fuzzing with sanitizers (like ASan, UBSan, and MSan) in your CI/CD pipeline.
Compiler and OS defenses
Stack canaries are a key compiler mitigation that detects stack smashing attempts.
A canary is a small, randomly generated value that the compiler places on the stack just before the function's return address. Before the function returns, the program checks this canary value. If the value has been altered or corrupted—which is exactly what a buffer overflow payload attempts to do—the program immediately terminates itself, stopping the attacker in their tracks.
Enable stack canaries with flags like -fstack-protector-strong and combine with address space layout randomization (ASLR), data execution prevention (DEP/NX), Relocation Read-Only (RELRO), and FORTIFY_SOURCE for defense in depth.
Network-based defenses
Network-based defense mechanisms include configuring a web application firewall (WAF) to inspect HTTP requests and block inputs that are oversized or appear suspicious. You can also monitor network traffic for known attack signatures with an intrusion detection/prevention system (IDS/IPS).
Keep in mind that these approaches have major limitations and can’t reliably prevent the exploitation of buffer overflow vulnerabilities. Attackers are highly adept at crafting sophisticated payloads, like ROP chains, that easily bypass signature blacklists and simple input size checks.
Security teams should never substitute perimeter or WAF controls for remediation in code and proper host hardening. Treat network controls as complementary safeguards that add detection and delay, not as primary fixes for memory safety vulnerabilities. Your WAF and IDS/IPS can be useful tripwires that flag anomalous behavior and buy you time for incident response. But your best solution, hands-down, remains at the application level: in your images, your runtime environment, and your source code.
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Strategies to detect and manage buffer overflow vulnerabilities at scale
Vulnerabilities are unavoidable. For example, almost 50% of AI-generated code contains vulnerabilities. That’s why you need automated, continuous processes in place to spot problems quickly and accurately. Strategies to detect and manage buffer overflow flaws at scale demand a combination of static analysis in the pipeline and ongoing runtime visibility.
Static analysis (SAST)
SAST tools, or code scanning, are your first line of defense in the pipeline. These tools scan source code without executing it, looking for risky functions and poor memory allocation patterns that could indicate a potential buffer overflow vulnerability. One quick note: While SAST is crucial for shifting security left, the results often require manual review to reduce false positives.
Dynamic analysis (DAST)
DAST tools test a running application for vulnerabilities by providing malicious input. Since they test live code, they're great at finding overflows that are only triggered under specific, real-world conditions.
Fuzz testing is a particularly useful form of DAST that automatically generates unexpected, boundary-testing inputs, stressing the application and finding buffer overflow vulnerabilities.
DAST complements SAST: The two work at different stages of the SDLC to strengthen your code security.
Software composition analysis (SCA)
SCA tools automatically identify all open-source and third-party components in your codebase, then cross-reference these with public vulnerability databases for known issues. This is a crucial part of supply-chain security because it finds vulnerabilities in code you didn't write yourself.
SCA solutions quickly identify whether any included library, including indirect dependencies, has a known buffer overflow vulnerability, helping you patch issues before they become a production headache.
Vulnerability management
Once you’ve identified buffer overflow vulnerabilities, you need a disciplined system to track, prioritize, and remediate them. Your team needs to focus on real risk, which means prioritizing public-facing applications and critical services first.
To do this effectively at scale, you need a solution that offers complete coverage of your code and cloud configuration. Agentless scanning simplifies this by giving you instant, continuous visibility across all workloads—VMs, containers, and serverless functions—without the friction of managing agents.
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Wiz's approach to buffer overflow vulnerability management
Preventing buffer overflow attacks in the cloud requires moving beyond simple lists of CVEs. It takes tools like Wiz that give you full visibility and context.
Wiz is a cloud native application protection platform that combines the precision of code security with the essential context of cloud posture to help you find and fix vulnerabilities quickly and effectively.
Wiz brings together multiple approaches to help you take control of buffer overflow risks:
Agentless scanning quickly identifies known buffer overflow CVEs across all cloud workloads, including hybrid and multi-cloud, with minimal performance impact.
Wiz’s full code-to-cloud view unifies SAST/SCA results with runtime posture for end-to-end risk mapping.
Runtime context lets you pinpoint toxic combinations that expose buffer overflow vulnerabilities to exploitation.
Simplified visibility and risk management delivers consistent security across all containers, serverless functions, and VMs.
Finally, Wiz prioritizes vulnerabilities based on real exposure paths and impact: public reachability, exploitable code paths, access to sensitive data, and privilege context. This approach reduces alert fatigue by focusing remediation on vulnerabilities that attackers can actually exploit, rather than chasing every CVE regardless of risk.
Don't let a simple coding error compromise your cloud. Get a demo today to see how Wiz can protect your entire environment—from code to cloud to runtime.
