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.

This table specifies different individual consequences associated with the weakness. The Scope identifies the application security area that is violated, while the Impact describes the negative technical impact that arises if an adversary succeeds in exploiting this weakness. The Likelihood provides information about how likely the specific consequence is expected to be seen relative to the other consequences in the list. For example, there may be high likelihood that a weakness will be exploited to achieve a certain impact, but a low likelihood that it will be exploited to achieve a different impact.

Impact	Details
DoS: Crash, Exit, or Restart; DoS: Resource Consumption (CPU); DoS: Resource Consumption (Memory)	Scope: 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	Scope: Confidentiality An attacker could read confidential data if they are able to control resource references.
Modify Memory; Execute Unauthorized Code or Commands	Scope: Integrity, Confidentiality, Availability An attacker could use malicious input to modify data or possibly alter control flow in unexpected ways, including arbitrary command execution.

Phase(s)	Mitigation
Architecture and Design	Strategy: Attack Surface Reduction 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]
Architecture and Design	Strategy: Libraries or Frameworks 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).
Architecture and Design; Implementation	Strategy: Attack Surface Reduction 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.
Implementation	Strategy: Input Validation 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
Architecture and Design	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.
Implementation	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.
Implementation	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.
Implementation	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.
Implementation	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.
Implementation	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.

This table shows the weaknesses and high level categories that are related to this weakness. These relationships are defined as ChildOf, ParentOf, MemberOf and give insight to similar items that may exist at higher and lower levels of abstraction. In addition, relationships such as PeerOf and CanAlsoBe are defined to show similar weaknesses that the user may want to explore.

The different Modes of Introduction provide information about how and when this weakness may be introduced. The Phase identifies a point in the life cycle at which introduction may occur, while the Note provides a typical scenario related to introduction during the given phase.

Phase	Note
Architecture and Design
Implementation	REALIZATION: This weakness is caused during implementation of an architectural security tactic. If a programmer believes that an attacker cannot modify certain inputs, then the programmer might not perform any input validation at all. For example, in web applications, many programmers believe that cookies and hidden form fields can not be modified from a web browser (CWE-472), although they can be altered using a proxy or a custom program. In a client-server architecture, the programmer might assume that client-side security checks cannot be bypassed, even when a custom client could be written that skips those checks (CWE-602).

This listing shows possible areas for which the given weakness could appear. These may be for specific named Languages, Operating Systems, Architectures, Paradigms, Technologies, or a class of such platforms. The platform is listed along with how frequently the given weakness appears for that instance.

Languages	Class: Not Language-Specific (Often Prevalent)
Technologies	AI/ML (Often Prevalent)

High

Example 1

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.

Example 2

This example asks the user for a height and width of an m X n game board with a maximum dimension of 100 squares.

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.

Example 3

The following example shows a PHP application in which the programmer attempts to display a user's birthday and homepage.

The programmer intended for $birthday to be in a date format and $homepage to be a valid URL. However, since the values are derived from an HTTP request, if an attacker can trick a victim into clicking a crafted URL with <script> tags providing the values for birthday and / or homepage, then the script will run on the client's browser when the web server echoes the content. Notice that even if the programmer were to defend the $birthday variable by restricting input to integers and dashes, it would still be possible for an attacker to provide a string of the form:

If this data were used in a SQL statement, it would treat the remainder of the statement as a comment. The comment could disable other security-related logic in the statement. In this case, encoding combined with input validation would be a more useful protection mechanism.

Furthermore, an XSS (CWE-79) attack or SQL injection (CWE-89) are just a few of the potential consequences when input validation is not used. Depending on the context of the code, CRLF Injection (CWE-93), Argument Injection (CWE-88), or Command Injection (CWE-77) may also be possible.

Example 4

The following example takes a user-supplied value to allocate an array of objects and then operates on the array.

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.

Example 5

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.

Note: this is a curated list of examples for users to understand the variety of ways in which this weakness can be introduced. It is not a complete list of all CVEs that are related to this CWE entry.

Ordinality	Description
Primary	(where the weakness exists independent of other weaknesses)

Method	Details
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: Cost effective for partial coverage: Bytecode Weakness Analysis - including disassembler + source code weakness analysis Binary Weakness Analysis - including disassembler + source code weakness analysis Effectiveness: SOAR Partial
Manual Static Analysis - Binary or Bytecode	According to SOAR [REF-1479], the following detection techniques may be useful: Cost effective for partial coverage: Binary / Bytecode disassembler - then use manual analysis for vulnerabilities & anomalies Effectiveness: SOAR Partial
Dynamic Analysis with Automated Results Interpretation	According to SOAR [REF-1479], the following detection techniques may be useful: Highly cost effective: Web Application Scanner Web Services Scanner Database Scanners Effectiveness: High
Dynamic Analysis with Manual Results Interpretation	According to SOAR [REF-1479], the following detection techniques may be useful: Highly cost effective: Fuzz Tester Framework-based Fuzzer Cost effective for partial coverage: Host Application Interface Scanner Monitored Virtual Environment - run potentially malicious code in sandbox / wrapper / virtual machine, see if it does anything suspicious Effectiveness: High
Manual Static Analysis - Source Code	According to SOAR [REF-1479], the following detection techniques may be useful: Highly cost effective: Focused Manual Spotcheck - Focused manual analysis of source Manual Source Code Review (not inspections) Effectiveness: High
Automated Static Analysis - Source Code	According to SOAR [REF-1479], the following detection techniques may be useful: Highly cost effective: Source code Weakness Analyzer Context-configured Source Code Weakness Analyzer Effectiveness: High
Architecture or Design Review	According to SOAR [REF-1479], the following detection techniques may be useful: Highly cost effective: Inspection (IEEE 1028 standard) (can apply to requirements, design, source code, etc.) Formal Methods / Correct-By-Construction Cost effective for partial coverage: Attack Modeling Effectiveness: High

This MemberOf Relationships table shows additional CWE Categories and Views that reference this weakness as a member. This information is often useful in understanding where a weakness fits within the context of external information sources.

Usage	DISCOURAGED (this CWE ID should not be used to map to real-world vulnerabilities)
Reasons	Frequent Misuse, Frequent Misinterpretation, Abstraction
Rationale	CWE-20 is commonly misused in low-information vulnerability reports when lower-level CWEs could be used instead, or when more details about the vulnerability are available [REF-1287]. It is not useful for trend analysis. It is also a level-1 Class (i.e., a child of a Pillar). Finally, CWE-20 is often misused when the root cause issue is related to how input is incorrectly transformed, instead of "validated" to be correct as-is.
Comments	Within CWE, the "input validation" term focuses on the act of checking whether an input is already safe, which is different from other techniques that ensure safe processing of input. Carefully perform root-cause analysis to be sure that the issue is not due to techniques that attempt to transform potentially-dangerous input into something safe, such as filtering (CWE-790) - which attempts to remove dangerous inputs - or encoding/escaping (CWE-116), which attempts to ensure that the input is not misinterpreted when it is included in output to another component. If the issue is truly due to imroper input validation, consider using lower-level children.
Suggestions	CWE-ID Comment CWE-1173 Not Using an Input Validation Framework CWE-116 Improper Encoding or Escaping of Output CWE-790 Improper Filtering of Special Elements CWE-1284 Specified Quantity CWE-1285 Specified Index, Position, or Offset CWE-1286 Syntactic Correctness CWE-1287 Specified Type CWE-1288 Consistency within Input CWE-1289 Unsafe Equivalence

Mapped Taxonomy Name	Node ID	Fit	Mapped Node Name
7 Pernicious Kingdoms			Input validation and representation
OWASP Top Ten 2004	A1	CWE More Specific	Unvalidated Input
CERT C Secure Coding	ERR07-C		Prefer functions that support error checking over equivalent functions that don't
CERT C Secure Coding	FIO30-C	CWE More Abstract	Exclude user input from format strings
CERT C Secure Coding	MEM10-C		Define and use a pointer validation function
WASC	20		Improper Input Handling
Software Fault Patterns	SFP25		Tainted input to variable

[REF-6]	Katrina Tsipenyuk, Brian Chess and Gary McGraw. "Seven Pernicious Kingdoms: A Taxonomy of Software Security Errors". NIST Workshop on Software Security Assurance Tools Techniques and Metrics. NIST. 2005-11-07. <https://samate.nist.gov/SSATTM_Content/papers/Seven%20Pernicious%20Kingdoms%20-%20Taxonomy%20of%20Sw%20Security%20Errors%20-%20Tsipenyuk%20-%20Chess%20-%20McGraw.pdf>.
[REF-166]	Jim Manico. "Input Validation with ESAPI - Very Important". 2008-08-15. <https://manicode.blogspot.com/2008/08/input-validation-with-esapi.html>. (URL validated: 2023-04-07)
[REF-45]	OWASP. "OWASP Enterprise Security API (ESAPI) Project". <https://owasp.org/www-project-enterprise-security-api/>. (URL validated: 2025-07-24)
[REF-168]	Joel Scambray, Mike Shema and Caleb Sima. "Hacking Exposed Web Applications, Second Edition". Input Validation Attacks. McGraw-Hill. 2006-06-05.
[REF-48]	Jeremiah Grossman. "Input validation or output filtering, which is better?". 2007-01-30. <https://blog.jeremiahgrossman.com/2007/01/input-validation-or-output-filtering.html>. (URL validated: 2023-04-07)
[REF-170]	Kevin Beaver. "The importance of input validation". 2006-09-06. <http://searchsoftwarequality.techtarget.com/tip/0,289483,sid92_gci1214373,00.html>.
[REF-7]	Michael Howard and David LeBlanc. "Writing Secure Code". Chapter 10, "All Input Is Evil!" Page 341. 2nd Edition. Microsoft Press. 2002-12-04. <https://www.microsoftpressstore.com/store/writing-secure-code-9780735617223>.
[REF-1109]	"LANGSEC: Language-theoretic Security". <http://langsec.org/>.
[REF-1110]	"LangSec: Recognition, Validation, and Compositional Correctness for Real World Security". <http://langsec.org/bof-handout.pdf>.
[REF-1111]	Sergey Bratus, Lars Hermerschmidt, Sven M. Hallberg, Michael E. Locasto, Falcon D. Momot, Meredith L. Patterson and Anna Shubina. "Curing the Vulnerable Parser: Design Patterns for Secure Input Handling". USENIX ;login:. 2017. <https://www.usenix.org/system/files/login/articles/login_spring17_08_bratus.pdf>.
[REF-1287]	MITRE. "Supplemental Details - 2022 CWE Top 25". Details of Problematic Mappings. 2022-06-28. <https://cwe.mitre.org/top25/archive/2022/2022_cwe_top25_supplemental.html#problematicMappingDetails>. (URL validated: 2024-11-17)
[REF-1479]	Gregory Larsen, E. Kenneth Hong Fong, David A. Wheeler and Rama S. Moorthy. "State-of-the-Art Resources (SOAR) for Software Vulnerability Detection, Test, and Evaluation". 2014-07. <https://www.ida.org/-/media/feature/publications/s/st/stateoftheart-resources-soar-for-software-vulnerability-detection-test-and-evaluation/p-5061.ashx>. (URL validated: 2025-09-05)

Submissions
Submission Date	Submitter	Organization
2006-07-19 (CWE Draft 3, 2006-07-19)	7 Pernicious Kingdoms
Contributions
Contribution Date	Contributor	Organization
2024-02-29 (CWE 4.17, 2025-04-03)	Abhi Balakrishnan
	Contributed usability diagram concepts used by the CWE team.
Modifications
Modification Date	Modifier	Organization
2026-04-30 (CWE 4.20, 2026-04-30)	CWE Content Team	MITRE
	updated Applicable_Platforms, Mapping_Notes
2025-12-11 (CWE 4.19, 2025-12-11)	CWE Content Team	MITRE
	updated Relationships, Weakness_Ordinalities
2025-09-09 (CWE 4.18, 2025-09-09)	CWE Content Team	MITRE
	updated Detection_Factors, References
2025-04-03 (CWE 4.17, 2025-04-03)	CWE Content Team	MITRE
	updated Common_Consequences, Description, Diagram, Mapping_Notes, Potential_Mitigations, Relationship_Notes, Terminology_Notes
2024-11-19 (CWE 4.16, 2024-11-19)	CWE Content Team	MITRE
	updated Relationships
2024-07-16 (CWE 4.15, 2024-07-16)	CWE Content Team	MITRE
	updated Observed_Examples
2023-10-26 (CWE 4.13, 2023-10-26)	CWE Content Team	MITRE
	updated Observed_Examples
2023-06-29 (CWE 4.12, 2023-06-29)	CWE Content Team	MITRE
	updated Mapping_Notes, Relationships
2023-04-27 (CWE 4.11, 2023-04-27)	CWE Content Team	MITRE
	updated References, Relationships
2022-10-13 (CWE 4.9, 2022-10-13)	CWE Content Team	MITRE
	updated References, Relationships
2022-06-28 (CWE 4.8, 2022-06-28)	CWE Content Team	MITRE
	updated Observed_Examples, Relationships
2022-04-28 (CWE 4.7, 2022-04-28)	CWE Content Team	MITRE
	updated Relationships
2021-10-28 (CWE 4.6, 2021-10-28)	CWE Content Team	MITRE
	updated Relationships
2021-07-20 (CWE 4.5, 2021-07-20)	CWE Content Team	MITRE
	updated Related_Attack_Patterns, Relationships
2021-03-15 (CWE 4.4, 2021-03-15)	CWE Content Team	MITRE
	updated Description, Potential_Mitigations
2020-08-20 (CWE 4.2, 2020-08-20)	CWE Content Team	MITRE
	updated Potential_Mitigations, Related_Attack_Patterns, Relationships
2020-06-25 (CWE 4.1, 2020-06-25)	CWE Content Team	MITRE
	updated Applicable_Platforms, Demonstrative_Examples, Description, Maintenance_Notes, Observed_Examples, Potential_Mitigations, References, Relationship_Notes, Relationships, Research_Gaps, Terminology_Notes
2020-02-24 (CWE 4.0, 2020-02-24)	CWE Content Team	MITRE
	updated Potential_Mitigations, References, Related_Attack_Patterns, Relationships
2019-09-19 (CWE 3.4, 2019-09-19)	CWE Content Team	MITRE
	updated Relationships
2019-06-20 (CWE 3.3, 2019-06-20)	CWE Content Team	MITRE
	updated Related_Attack_Patterns, Relationships
2019-01-03 (CWE 3.2, 2019-01-03)	CWE Content Team	MITRE
	updated Related_Attack_Patterns, Relationships
2018-03-27 (CWE 3.1, 2018-03-27)	CWE Content Team	MITRE
	updated References
2017-11-08 (CWE 3.0, 2017-11-08)	CWE Content Team	MITRE
	updated Modes_of_Introduction, References, Relationships, Taxonomy_Mappings
2017-05-03 (CWE 2.11, 2017-05-05)	CWE Content Team	MITRE
	updated Related_Attack_Patterns, Relationships
2017-01-19 (CWE 2.10, 2017-01-19)	CWE Content Team	MITRE
	updated Related_Attack_Patterns, Relationships
2015-12-07 (CWE 2.9, 2015-12-07)	CWE Content Team	MITRE
	updated Relationships
2014-07-30 (CWE 2.8, 2014-07-31)	CWE Content Team	MITRE
	updated Detection_Factors, Relationships, Taxonomy_Mappings
2014-02-18 (CWE 2.6, 2014-02-19)	CWE Content Team	MITRE
	updated Demonstrative_Examples, Related_Attack_Patterns
2013-07-17 (CWE 2.5, 2013-07-17)	CWE Content Team	MITRE
	updated Relationships
2013-02-21 (CWE 2.4, 2013-02-21)	CWE Content Team	MITRE
	updated Relationships
2012-10-30 (CWE 2.3, 2012-10-30)	CWE Content Team	MITRE
	updated Potential_Mitigations
2012-05-11 (CWE 2.2, 2012-05-15)	CWE Content Team	MITRE
	updated Demonstrative_Examples, References, Related_Attack_Patterns, Relationships
2011-09-13 (CWE 2.1, 2011-09-13)	CWE Content Team	MITRE
	updated Relationships, Taxonomy_Mappings
2011-06-01 (CWE 1.13, 2011-06-01)	CWE Content Team	MITRE
	updated Applicable_Platforms, Common_Consequences, Relationship_Notes
2011-03-29 (CWE 1.12, 2011-03-30)	CWE Content Team	MITRE
	updated Observed_Examples
2010-12-13 (CWE 1.11, 2010-12-13)	CWE Content Team	MITRE
	updated Demonstrative_Examples, Description
2010-09-27 (CWE 1.10, 2010-09-27)	CWE Content Team	MITRE
	updated Potential_Mitigations, Relationships
2010-06-21 (CWE 1.9, 2010-06-21)	CWE Content Team	MITRE
	updated Potential_Mitigations, Research_Gaps, Terminology_Notes
2010-04-05 (CWE 1.8.1, 2010-04-05)	CWE Content Team	MITRE
	updated Related_Attack_Patterns
2010-02-16 (CWE 1.8, 2010-02-16)	CWE Content Team	MITRE
	updated Detection_Factors, Potential_Mitigations, References, Taxonomy_Mappings
2009-12-28 (CWE 1.7, 2009-12-28)	CWE Content Team	MITRE
	updated Applicable_Platforms, Demonstrative_Examples, Detection_Factors
2009-10-29 (CWE 1.6, 2009-10-29)	CWE Content Team	MITRE
	updated Common_Consequences, Demonstrative_Examples, Maintenance_Notes, Modes_of_Introduction, Observed_Examples, Relationships, Research_Gaps, Terminology_Notes
2009-07-27 (CWE 1.5, 2009-07-27)	CWE Content Team	MITRE
	updated Relationships
2009-05-27 (CWE 1.4, 2009-05-27)	CWE Content Team	MITRE
	updated Related_Attack_Patterns
2009-03-10 (CWE 1.3, 2009-03-10)	CWE Content Team	MITRE
	updated Description, Potential_Mitigations
2009-01-12 (CWE 1.2, 2009-01-12)	CWE Content Team	MITRE
	updated Applicable_Platforms, Common_Consequences, Demonstrative_Examples, Description, Likelihood_of_Exploit, Name, Observed_Examples, Other_Notes, Potential_Mitigations, References, Relationship_Notes, Relationships
2008-11-24 (CWE 1.1, 2008-11-25)	CWE Content Team	MITRE
	updated Relationships, Taxonomy_Mappings
2008-09-08 (CWE 1.0, 2008-09-09)	CWE Content Team	MITRE
	updated Relationships, Other_Notes, Taxonomy_Mappings
2008-08-15 (CWE 1.0, 2008-09-09)		Veracode
	Suggested OWASP Top Ten 2004 mapping
2008-07-01 (CWE 1.0, 2008-09-09)	Eric Dalci	Cigital
	updated Potential_Mitigations, Time_of_Introduction
Previous Entry Names
Change Date	Previous Entry Name
2009-01-12	Insufficient Input Validation