CWE-20: Improper Input Validation
The product receives input or data, but it does not validate or incorrectly validates that the input has the properties that are required to process the data safely and correctly.
Last updated
Overview
Input validation is a frequently-used technique for checking potentially dangerous inputs in order to ensure that the inputs are safe for processing within the code, or when communicating with other components. Input can consist of: raw data - strings, numbers, parameters, file contents, etc. metadata - information about the raw data, such as headers or size Data can be simple or structured. Structured data can be composed of many nested layers, composed of combinations of metadata and raw data, with other simple or structured data. Many properties of raw data or metadata may need to be validated upon entry into the code, such as: specified quantities such as size, length, frequency, price, rate, number of operations, time, etc. implied or derived quantities, such as the actual size of a file instead of a specified size indexes, offsets, or positions into more complex data structures symbolic keys or other elements into hash tables, associative arrays, etc. well-formedness, i.e. syntactic correctness - compliance with expected syntax lexical token correctness - compliance with rules for what is treated as a token specified or derived type - the actual type of the input (or what the input appears to be) consistency - between individual data elements, between raw data and metadata, between references, etc. conformance to domain-specific rules, e.g. business logic equivalence - ensuring that equivalent inputs are treated the same authenticity, ownership, or other attestations about the input, e.g. a cryptographic signature to prove the source of the data Implied or derived properties of data must often be calculated or inferred by the code itself. Errors in deriving properties may be considered a contributing factor to improper input validation.
Real-world CVEs
4,270 recorded CVEs are caused by CWE-20 (Improper Input Validation), including 61 in CISA's KEV (Known Exploited Vulnerabilities) catalog. KEVs are shown first. 693 new CWE-20 CVEs have been recorded so far in 2026 (552 in 2025).
- CVE-2026-34910CISA KEVCritical · CVSS 10.0 · EPSS 100th2026-05-22
- CVE-2025-54236CISA KEV
Adobe Commerce | Improper Input Validation (CWE-20)
Critical · CVSS 10.0 · EPSS 100th2025-09-09 - CVE-2020-1350CISA KEVCritical · CVSS 10.0 · EPSS 100th2020-07-14
- CVE-2019-11708CISA KEVCritical · CVSS 10.0 · EPSS 99th2019-07-23
- CVE-2018-0125CISA KEVCritical · CVSS 10.0 · EPSS 99th2018-02-08
- CVE-2017-12240CISA KEVCritical · CVSS 10.0 · EPSS 96th2017-09-28
- CVE-2025-8876CISA KEV
Command Injection Vulnerability
Critical · CVSS 9.4 · EPSS 86th2025-08-14 - CVE-2020-1040CISA KEVCritical · CVSS 9.4 · EPSS 93th2020-07-14
- CVE-2026-12569CISA KEV
Remote Code Execution (RCE) vulnerability in Windchill PDMlink
Critical · CVSS 9.3 · EPSS 66th2026-06-18 - CVE-2025-20393CISA KEV
Cisco Secure Email Gateway and Cisco Secure Email and Web Manager Remote Command Execution Vulnerability
Critical · CVSS 9.3 · EPSS 98th2025-12-17 - CVE-2024-21413CISA KEV
Microsoft Outlook Remote Code Execution Vulnerability
Critical · CVSS 9.3 · EPSS 100th2024-02-13 - CVE-2023-22515CISA KEVCritical · CVSS 9.3 · EPSS 100th2023-10-04
Showing 12 of 4,270 recorded CWE-20 CVEs. Track new ones as they are published and get AI-written analysis and fixes.
Monitor CWE-20 vulnerabilitiesCommon consequences
What can happen when CWE-20 is exploited.
DoS: Crash, Exit, or Restart, DoS: Resource Consumption (CPU), DoS: Resource Consumption (Memory)
Affects: Availability
An attacker could provide unexpected values and cause a program crash or arbitrary control of resource allocation, leading to excessive consumption of resources such as memory and CPU.
Read Memory, Read Files or Directories
Affects: Confidentiality
An attacker could read confidential data if they are able to control resource references.
Modify Memory, Execute Unauthorized Code or Commands
Affects: Integrity, Confidentiality, Availability
An attacker could use malicious input to modify data or possibly alter control flow in unexpected ways, including arbitrary command execution.
How it happens
When it is introduced
Typically introduced during these phases of the software lifecycle.
Applies to
Technologies
How to prevent it
Practical mitigations for CWE-20, grouped by where in the lifecycle they apply.
Consider using language-theoretic security (LangSec) techniques that characterize inputs using a formal language and build "recognizers" for that language. This effectively requires parsing to be a distinct layer that effectively enforces a boundary between raw input and internal data representations, instead of allowing parser code to be scattered throughout the program, where it could be subject to errors or inconsistencies that create weaknesses. [REF-1109] [REF-1110] [REF-1111]
Use an input validation framework such as Struts or the OWASP ESAPI Validation API. Note that using a framework does not automatically address all input validation problems; be mindful of weaknesses that could arise from misusing the framework itself (CWE-1173).
Understand all the potential areas where untrusted inputs can enter the product, including but not limited to: parameters or arguments, cookies, anything read from the network, environment variables, reverse DNS lookups, query results, request headers, URL components, e-mail, files, filenames, databases, and any external systems that provide data to the application. Remember that such inputs may be obtained indirectly through API calls.
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.
Effectiveness: High
For any security checks that are performed on the client side, ensure that these checks are duplicated on the server side, in order to avoid CWE-602. Attackers can bypass the client-side checks by modifying values after the checks have been performed, or by changing the client to remove the client-side checks entirely. Then, these modified values would be submitted to the server.
Even though client-side checks provide minimal benefits with respect to server-side security, they are still useful. First, they can support intrusion detection. If the server receives input that should have been rejected by the client, then it may be an indication of an attack. Second, client-side error-checking can provide helpful feedback to the user about the expectations for valid input. Third, there may be a reduction in server-side processing time for accidental input errors, although this is typically a small savings.
When your application combines data from multiple sources, perform the validation after the sources have been combined. The individual data elements may pass the validation step but violate the intended restrictions after they have been combined.
Be especially careful to validate all input when invoking code that crosses language boundaries, such as from an interpreted language to native code. This could create an unexpected interaction between the language boundaries. Ensure that you are not violating any of the expectations of the language with which you are interfacing. For example, even though Java may not be susceptible to buffer overflows, providing a large argument in a call to native code might trigger an overflow.
Directly convert your input type into the expected data type, such as using a conversion function that translates a string into a number. After converting to the expected data type, ensure that the input's values fall within the expected range of allowable values and that multi-field consistencies are maintained.
Inputs should be decoded and canonicalized to the application's current internal representation before being validated (CWE-180, CWE-181). Make sure that your application does not inadvertently decode the same input twice (CWE-174). Such errors could be used to bypass allowlist schemes by introducing dangerous inputs after they have been checked. Use libraries such as the OWASP ESAPI Canonicalization control.
Consider performing repeated canonicalization until your input does not change any more. This will avoid double-decoding and similar scenarios, but it might inadvertently modify inputs that are allowed to contain properly-encoded dangerous content.
When exchanging data between components, ensure that both components are using the same character encoding. Ensure that the proper encoding is applied at each interface. Explicitly set the encoding you are using whenever the protocol allows you to do so.
How to detect it
Automated Static Analysis
Some instances of improper input validation can be detected using automated static analysis.
A static analysis tool might allow the user to specify which application-specific methods or functions perform input validation; the tool might also have built-in knowledge of validation frameworks such as Struts. The tool may then suppress or de-prioritize any associated warnings. This allows the analyst to focus on areas of the software in which input validation does not appear to be present.
Except in the cases described in the previous paragraph, automated static analysis might not be able to recognize when proper input validation is being performed, leading to false positives - i.e., warnings that do not have any security consequences or require any code changes.
Manual Static Analysis
When custom input validation is required, such as when enforcing business rules, manual analysis is necessary to ensure that the validation is properly implemented.
Fuzzing
Fuzzing techniques can be useful for detecting input validation errors. When unexpected inputs are provided to the software, the software should not crash or otherwise become unstable, and it should generate application-controlled error messages. If exceptions or interpreter-generated error messages occur, this indicates that the input was not detected and handled within the application logic itself.
Automated Static Analysis - Binary or Bytecode
According to SOAR [REF-1479], the following detection techniques may be useful:
Effectiveness: SOAR Partial
Manual Static Analysis - Binary or Bytecode
According to SOAR [REF-1479], the following detection techniques may be useful:
Effectiveness: SOAR Partial
Dynamic Analysis with Automated Results Interpretation
According to SOAR [REF-1479], the following detection techniques may be useful:
Effectiveness: High
Dynamic Analysis with Manual Results Interpretation
According to SOAR [REF-1479], the following detection techniques may be useful:
Effectiveness: High
Manual Static Analysis - Source Code
According to SOAR [REF-1479], the following detection techniques may be useful:
Effectiveness: High
Automated Static Analysis - Source Code
According to SOAR [REF-1479], the following detection techniques may be useful:
Effectiveness: High
Architecture or Design Review
According to SOAR [REF-1479], the following detection techniques may be useful:
Effectiveness: High
Code examples
Illustrative examples from MITRE showing how the weakness appears in code.
This example demonstrates a shopping interaction in which the user is free to specify the quantity of items to be purchased and a total is calculated.
The user has no control over the price variable, however the code does not prevent a negative value from being specified for quantity. If an attacker were to provide a negative value, then the user would have their account credited instead of debited.
This example asks the user for a height and width of an m X n game board with a maximum dimension of 100 squares.
Vulnerable example
/* board dimensions */
...While this code checks to make sure the user cannot specify large, positive integers and consume too much memory, it does not check for negative values supplied by the user. As a result, an attacker can perform a resource consumption (CWE-400) attack against this program by specifying two, large negative values that will not overflow, resulting in a very large memory allocation (CWE-789) and possibly a system crash. Alternatively, an attacker can provide very large negative values which will cause an integer overflow (CWE-190) and unexpected behavior will follow depending on how the values are treated in the remainder of the program.
The following example shows a PHP application in which the programmer attempts to display a user's birthday and homepage.
Vulnerable example
$birthday = $_GET['birthday'];Attack input
2009-01-09--The following example takes a user-supplied value to allocate an array of objects and then operates on the array.
Vulnerable example
private void buildList ( int untrustedListSize ){This example attempts to build a list from a user-specified value, and even checks to ensure a non-negative value is supplied. If, however, a 0 value is provided, the code will build an array of size 0 and then try to store a new Widget in the first location, causing an exception to be thrown.
This Android application has registered to handle a URL when sent an intent:
The application assumes the URL will always be included in the intent. When the URL is not present, the call to getStringExtra() will return null, thus causing a null pointer exception when length() is called.
Illustrative examples
Real CVEs that MITRE cites as examples of this weakness.
- CVE-2021-30860CISA KEV— Chain: improper input validation (CWE-20) leads to integer overflow (CWE-190) in mobile OS, as exploited in the wild per CISA KEV.
- CVE-2021-30663CISA KEV— Chain: improper input validation (CWE-20) leads to integer overflow (CWE-190) in mobile OS, as exploited in the wild per CISA KEV.
- CVE-2021-22205CISA KEV— Chain: backslash followed by a newline can bypass a validation step (CWE-20), leading to eval injection (CWE-95), as exploited in the wild per CISA KEV.
- CVE-2021-21220CISA KEV— Chain: insufficient input validation (CWE-20) in browser allows heap corruption (CWE-787), as exploited in the wild per CISA KEV.
- CVE-2020-9054CISA KEV— Chain: improper input validation (CWE-20) in username parameter, leading to OS command injection (CWE-78), as exploited in the wild per CISA KEV.
- CVE-2020-3452CISA KEV— Chain: security product has improper input validation (CWE-20) leading to directory traversal (CWE-22), as exploited in the wild per CISA KEV.
- CVE-2020-3161CISA KEV— Improper input validation of HTTP requests in IP phone, as exploited in the wild per CISA KEV.
- CVE-2020-3580CISA KEV— Chain: improper input validation (CWE-20) in firewall product leads to XSS (CWE-79), as exploited in the wild per CISA KEV.
- CVE-2024-37032 — Large language model (LLM) management tool does not validate the format of a digest value (CWE-1287) from a private, untrusted model registry, enabling relative path traversal (CWE-23), a.k.a. Probllama
- CVE-2022-45918 — Chain: a learning management tool debugger uses external input to locate previous session logs (CWE-73) and does not properly validate the given path (CWE-20), allowing for filesystem path traversal using "../" sequences (CWE-24)
- CVE-2021-37147 — Chain: caching proxy server has improper input validation (CWE-20) of headers, allowing HTTP response smuggling (CWE-444) using an "LF line ending"
- CVE-2008-5305 — Eval injection in Perl program using an ID that should only contain hyphens and numbers.
- CVE-2008-2223 — SQL injection through an ID that was supposed to be numeric.
- CVE-2008-3477 — lack of input validation in spreadsheet program leads to buffer overflows, integer overflows, array index errors, and memory corruption.
- CVE-2008-3843 — insufficient validation enables XSS
- CVE-2008-3174 — driver in security product allows code execution due to insufficient validation
- CVE-2007-3409 — infinite loop from DNS packet with a label that points to itself
- CVE-2006-6870 — infinite loop from DNS packet with a label that points to itself
- CVE-2008-1303 — missing parameter leads to crash
- CVE-2007-5893 — HTTP request with missing protocol version number leads to crash
- CVE-2006-6658 — request with missing parameters leads to information exposure
- CVE-2008-4114 — system crash with offset value that is inconsistent with packet size
- CVE-2006-3790 — size field that is inconsistent with packet size leads to buffer over-read
- CVE-2008-2309 — product uses a denylist to identify potentially dangerous content, allowing attacker to bypass a warning
- CVE-2008-3494 — security bypass via an extra header
- CVE-2008-3571 — empty packet triggers reboot
- CVE-2006-5525 — incomplete denylist allows SQL injection
- CVE-2008-1284 — NUL byte in theme name causes directory traversal impact to be worse
- CVE-2008-0600 — kernel does not validate an incoming pointer before dereferencing it
- CVE-2008-1738 — anti-virus product has insufficient input validation of hooked SSDT functions, allowing code execution
- CVE-2008-1737 — anti-virus product allows DoS via zero-length field
- CVE-2008-3464 — driver does not validate input from userland to the kernel
- CVE-2008-2252 — kernel does not validate parameters sent in from userland, allowing code execution
- CVE-2008-2374 — lack of validation of string length fields allows memory consumption or buffer over-read
- CVE-2008-1440 — lack of validation of length field leads to infinite loop
- CVE-2008-1625 — lack of validation of input to an IOCTL allows code execution
- CVE-2008-3177 — zero-length attachment causes crash
- CVE-2007-2442 — zero-length input causes free of uninitialized pointer
- CVE-2008-5563 — crash via a malformed frame structure
- CVE-2008-5285 — infinite loop from a long SMTP request
- CVE-2008-3812 — router crashes with a malformed packet
- CVE-2008-3680 — packet with invalid version number leads to NULL pointer dereference
- CVE-2008-3660 — crash via multiple "." characters in file extension
Terminology & mappings
Mapped taxonomies
- 7 Pernicious Kingdoms: Input validation and representation
- OWASP Top Ten 2004: Unvalidated Input (A1) — CWE More Specific fit
- CERT C Secure Coding: Prefer functions that support error checking over equivalent functions that don't (ERR07-C)
- CERT C Secure Coding: Exclude user input from format strings (FIO30-C) — CWE More Abstract fit
- CERT C Secure Coding: Define and use a pointer validation function (MEM10-C)
- WASC: Improper Input Handling (20)
- Software Fault Patterns: Tainted input to variable (SFP25)
Attack patterns
CAPEC attack patterns that exploit this weakness.
- CAPEC-10: Buffer Overflow via Environment Variables
- CAPEC-101: Server Side Include (SSI) Injection
- CAPEC-104: Cross Zone Scripting
- CAPEC-108: Command Line Execution through SQL Injection
- CAPEC-109: Object Relational Mapping Injection
- CAPEC-110: SQL Injection through SOAP Parameter Tampering
- CAPEC-120: Double Encoding
- CAPEC-13: Subverting Environment Variable Values
- CAPEC-135: Format String Injection
- CAPEC-136: LDAP Injection
- CAPEC-14: Client-side Injection-induced Buffer Overflow
- CAPEC-153: Input Data Manipulation
- CAPEC-182: Flash Injection
- CAPEC-209: XSS Using MIME Type Mismatch
- CAPEC-22: Exploiting Trust in Client
- CAPEC-23: File Content Injection
- CAPEC-230: Serialized Data with Nested Payloads
- CAPEC-231: Oversized Serialized Data Payloads
- CAPEC-24: Filter Failure through Buffer Overflow
- CAPEC-250: XML Injection
- CAPEC-261: Fuzzing for garnering other adjacent user/sensitive data
- CAPEC-267: Leverage Alternate Encoding
- CAPEC-28: Fuzzing
- CAPEC-3: Using Leading 'Ghost' Character Sequences to Bypass Input Filters
- CAPEC-31: Accessing/Intercepting/Modifying HTTP Cookies
- CAPEC-42: MIME Conversion
- CAPEC-43: Exploiting Multiple Input Interpretation Layers
- CAPEC-45: Buffer Overflow via Symbolic Links
- CAPEC-46: Overflow Variables and Tags
- CAPEC-47: Buffer Overflow via Parameter Expansion
- CAPEC-473: Signature Spoof
- CAPEC-52: Embedding NULL Bytes
- CAPEC-53: Postfix, Null Terminate, and Backslash
- CAPEC-588: DOM-Based XSS
- CAPEC-63: Cross-Site Scripting (XSS)
- CAPEC-64: Using Slashes and URL Encoding Combined to Bypass Validation Logic
- CAPEC-664: Server Side Request Forgery
- CAPEC-67: String Format Overflow in syslog()
- CAPEC-7: Blind SQL Injection
- CAPEC-71: Using Unicode Encoding to Bypass Validation Logic
- CAPEC-72: URL Encoding
- CAPEC-73: User-Controlled Filename
- CAPEC-78: Using Escaped Slashes in Alternate Encoding
- CAPEC-79: Using Slashes in Alternate Encoding
- CAPEC-8: Buffer Overflow in an API Call
- CAPEC-80: Using UTF-8 Encoding to Bypass Validation Logic
- CAPEC-81: Web Server Logs Tampering
- CAPEC-83: XPath Injection
- CAPEC-85: AJAX Footprinting
- CAPEC-88: OS Command Injection
- CAPEC-9: Buffer Overflow in Local Command-Line Utilities
Frequently asked questions
Common questions about CWE-20.
- What is CWE-20?
- The product receives input or data, but it does not validate or incorrectly validates that the input has the properties that are required to process the data safely and correctly.
- What CVEs are caused by CWE-20?
- 4,270 recorded CVEs are attributed to CWE-20, including CVE-2026-34910, CVE-2025-54236, CVE-2020-1350. 61 are listed in CISA's Known Exploited Vulnerabilities (KEV) catalog.
- Is CWE-20 part of the OWASP Top 10?
- CWE-20 maps to OWASP Top Ten 2004: Unvalidated Input (A1) in the OWASP security taxonomy.
- How do you prevent CWE-20?
- Consider using language-theoretic security (LangSec) techniques that characterize inputs using a formal language and build "recognizers" for that language. This effectively requires parsing to be a distinct layer that effectively enforces a boundary between raw input and internal data representations, instead of allowing parser code to be scattered throughout the program, where it could be subject to errors or inconsistencies that create weaknesses. [REF-1109] [REF-1110] [REF-1111]
- How is CWE-20 detected?
- Automated Static Analysis: Some instances of improper input validation can be detected using automated static analysis.
- What are the consequences of CWE-20?
- Exploiting CWE-20 can lead to: DoS: Crash, Exit, or Restart, DoS: Resource Consumption (CPU), DoS: Resource Consumption (Memory), Read Memory, Read Files or Directories, Modify Memory.
- Is CWE-20 actively exploited?
- Yes. 61 CWE-20 vulnerabilities are in CISA's KEV catalog of actively exploited flaws, out of 4,270 recorded CVEs.
References
- MITRE CWE definition (CWE-20) (opens in a new tab)
- CWE-20 vulnerabilities on NVD (opens in a new tab)
- Learn: What is a CWE?
Weakness data is sourced from the MITRE CWE catalog (v4.20). CVE associations are aggregated and kept current by RadicalNotion.AI.
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