Weakness · High

CWE-125: Out-of-bounds Read

What it is

The product reads data past the end, or before the beginning, of the intended buffer.

17 exploited in the wildMITRE CWE 4.19.1

Severity (our rating): High
Likelihood of exploit: Not rated by MITRE
Introduced during: Implementation
Exploited in the wild: 17 known exploited CVEs

What an attacker can do

Read Memory (Confidentiality)
Bypass Protection Mechanism (Confidentiality)
DoS: Crash, Exit, or Restart (Availability)
Varies by Context (Other)

How to prevent it

Implementation

Assume all input is malicious. Use an "accept known good" input validation strategy, i.e., use a list of acceptable inputs that strictly conform to specifications. Reject any input that does not strictly conform to specifications, or transform it into something that does. When performing input validation, consider all potentially relevant properties, including length, type of input, the full range of acceptable values, missing or extra inputs, syntax, consistency across related fields, and conformance to business rules. As an example of business rule logic, "boat" may be syntactically valid because it only contains alphanumeric characters, but it is not valid if the input is only expected to contain colors such as "red" or "blue." Do not rely exclusively on looking for malicious or malformed inputs. This is likely to miss at least one undesirable input, especially if the code's environment changes. This can give attackers enough room to bypass the intended validation. However, denylists can be useful for detecting potential attacks or determining which inputs are so malformed that they should be rejected outright. To reduce the likelihood of introducing an out-of-bounds read, ensure that you validate and ensure correct calculations for any length argument, buffer size calculation, or offset. Be especially careful of relying on a sentinel (i.e. special character such as NUL) in untrusted inputs.

Architecture and Design

Use a language that provides appropriate memory abstractions.

How to find it

Fuzzing. Fuzz testing (fuzzing) is a powerful technique for generating large numbers of diverse inputs - either randomly or algorithmically - and dynamically invoking the code with those inputs. Even with random inputs, it is often capable of generating unexpected results such as crashes, memory corruption, or resource consumption. Fuzzing effectively produces repeatable test cases that clearly indicate bugs, which helps developers to diagnose the issues.
Automated Static Analysis. Automated static analysis, commonly referred to as Static Application Security Testing (SAST), can find some instances of this weakness by analyzing source code (or binary/compiled code) without having to execute it. Typically, this is done by building a model of data flow and control flow, then searching for potentially-vulnerable patterns that connect "sources" (origins of input) with "sinks" (destinations where the data interacts with external components, a lower layer such as the OS, etc.)
Automated Dynamic Analysis. Use tools that are integrated during compilation to insert runtime error-checking mechanisms related to memory safety errors, such as AddressSanitizer (ASan) for C/C++.

CWE-125 on MITRE's CWE site

Exploited in the wild: 17 CVEs

Vulnerabilities caused by CWE-125 that attackers have used, from CISA's Known Exploited Vulnerabilities catalog, newest first.

All known exploited vulnerabilities

H2 Security

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Source: MITRE Common Weakness Enumeration, CWE version 4.19.1. CWE is a trademark of The MITRE Corporation.