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CWE-20 (输入验证不恰当) — Vulnerability Class 4415

4415 vulnerabilities classified as CWE-20 (输入验证不恰当). AI Chinese analysis included.

CWE-20 represents a critical software weakness where applications fail to properly verify the integrity, format, or type of incoming data before processing it. This oversight allows attackers to inject malicious payloads, such as SQL injection strings or cross-site scripting code, which can bypass security controls and compromise system integrity. Exploitation typically occurs when untrusted data from external sources, like user forms or network packets, is treated as executable code or trusted input. To mitigate this risk, developers must implement rigorous input validation strategies, including strict type checking, length constraints, and allow-listing acceptable characters. Additionally, employing parameterized queries and output encoding ensures that even if validation fails, the injected data remains inert, thereby preserving application security and preventing unauthorized execution or data exposure.

MITRE CWE Description
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. 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 el…
Common Consequences (3)
Availability DoS: Crash, Exit, or Restart, DoS: Resource Consumption (CPU), DoS: Resource Consumption (Memory)
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.
Confidentiality Read Memory, Read Files or Directories
An attacker could read confidential data if they are able to control resource references.
Integrity, Confidentiality, Availability Modify Memory, Execute Unauthorized Code or Commands
An attacker could use malicious input to modify data or possibly alter control flow in unexpected ways, including arbitrary command execution.
Mitigations (5)
Architecture and Design 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 subjec…
Architecture and Design 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 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 b…
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…
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 clien…
Examples (2)
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.
... public static final double price = 20.00; int quantity = currentUser.getAttribute("quantity"); double total = price * quantity; chargeUser(total); ...
Bad · Java
This example asks the user for a height and width of an m X n game board with a maximum dimension of 100 squares.
... #define MAX_DIM 100 ... /* board dimensions */ int m,n, error; board_square_t *board; printf("Please specify the board height: \n"); error = scanf("%d", &m); if ( EOF == error ){ die("No integer passed: Die evil hacker!\n"); } printf("Please specify the board width: \n"); error = scanf("%d", &n); if ( EOF == error ){ die("No integer passed: Die evil hacker!\n"); } if ( m > MAX_DIM || n > MAX_DIM ) { die("Value too large: Die evil hacker!\n"); } board = (board_square_t*) malloc( m * n * sizeof(board_square_t)); ...
Bad · C
CVE ID Title CVSS Severity Published
CVE-2026-100120 CAI Content Credentials | Improper Input Validation (CWE-20) — Content Credentials Rust SDK 7.5 High 2026-10-13
CVE-2026-100117 CAI Content Credentials | Improper Input Validation (CWE-20) — Content Credentials Rust SDK 7.5 High 2026-10-13
CVE-2026-100135 CAI Content Credentials | Improper Input Validation (CWE-20) — Content Credentials Rust SDK 7.5 High 2026-10-13
CVE-2026-100113 CAI Content Credentials | Improper Input Validation (CWE-20) — Content Credentials Rust SDK 7.5 High 2026-10-13
CVE-2026-100124 CAI Content Credentials | Improper Input Validation (CWE-20) — Content Credentials Rust SDK 7.5 High 2026-10-13
CVE-2026-100125 CAI Content Credentials | Improper Input Validation (CWE-20) — Content Credentials Rust SDK 5.9 Medium 2026-10-13
CVE-2026-48377 CAI Content Credentials | Improper Input Validation (CWE-20) — Content Credentials Rust SDK 5.3 Medium 2026-10-13
CVE-2026-106619 ColdFusion | Improper Input Validation (CWE-20) — ColdFusion 2025 9.0 Critical 2026-10-13
CVE-2026-106613 ColdFusion | Improper Input Validation (CWE-20) — ColdFusion 2025 8.8 High 2026-10-13
CVE-2026-75995 ColdFusion | Improper Input Validation (CWE-20) — ColdFusion 2025 8.4 High 2026-10-13
CVE-2026-105900 ColdFusion | Improper Input Validation (CWE-20) — ColdFusion 2025 7.5 High 2026-10-13
CVE-2026-78628 Improper Input Validation in the Okta Credential Provider for Windows — Okta Credential Provider for Windows 6.0 Medium 2026-10-13
CVE-2026-106626 Adobe Experience Manager | Improper Input Validation (CWE-20) — Adobe Experience Manager as a Cloud Service 9.1 Critical 2026-10-13
CVE-2026-105895 Adobe Experience Manager | Improper Input Validation (CWE-20) — Adobe Experience Manager 6.5 9.9 Critical 2026-10-13
CVE-2026-105719 Microsoft SharePoint Server Information Disclosure Vulnerability — Microsoft SharePoint Server Subscription Edition 6.5 Medium 2026-10-13
CVE-2026-95631 Adobe Commerce | Improper Input Validation (CWE-20) — Adobe Commerce 8.7 High 2026-10-13
CVE-2026-92464 Adobe Commerce | Improper Input Validation (CWE-20) — Adobe Commerce 9.1 Critical 2026-10-13
CVE-2026-95630 Adobe Commerce | Improper Input Validation (CWE-20) — Adobe Commerce 4.3 Medium 2026-10-13
CVE-2026-54700 ConnectBot SSH: Unbounded SSH field lengths can cause excessive memory allocation — cbssh 6.9 Medium 2026-10-13
CVE-2026-107918 Insufficient input validation vulnerability in NETGEAR R7300 — R7300DST 4.5 Medium 2026-10-13
CVE-2026-107917 Insufficient input validation vulnerability in NETGEAR R7300 router — R7300DST 4.5 Medium 2026-10-13
CVE-2026-11732 Insufficient input validation vulnerability exists in website blocking feature of certain NETGEAR RAX/CAX series models — CAX30 8.8 High 2026-10-13
CVE-2026-9218 Insufficient input validation vulnerability in Certain NETGEAR routers allows unauthorized access — CBR40 4.5 Medium 2026-10-13
CVE-2026-14308 Insufficient Signature Validation — ManageEngine Malware Protection Plus 4.9 Medium 2026-10-13
CVE-2026-84316 Nginx UI: nginx config directive denylist (ValidateConfigFile) is bypassable via same-line ";" separation → authenticated directive injection (RCE on the official image) — nginx-ui 8.8 High 2026-10-12
CVE-2026-78673 Maximo AI Service Improper Input Validation — Maximo AI Service 7.5 High 2026-10-12
CVE-2026-84317 Nginx UI: MCP nginx_config_add skips config directive validation → authenticated nginx directive injection (RCE on the official image) — nginx-ui 8.8 High 2026-10-12
CVE-2026-104364 IBM® Db2® Denial of Service — Db2 3.3 Low 2026-10-12
CVE-2026-57143 PraisonAI: Server-Side Request Forgery (SSRF) in SearxNG / search_web tools via attacker-controlled searxng_url parameter — praisonaiagents 8.8 High 2026-10-12
CVE-2026-94451 Quarkus-hibernate-orm-rest-data-panache: quarkus-hibernate-orm-rest-data-panache: information disclosure and dos via unvalidated sort parameter in rest data panache — Red Hat build of Quarkus 3.27.6.redhat 6.5 Medium 2026-10-12

Vulnerabilities classified as CWE-20 (输入验证不恰当) represent 4415 CVEs. The CWE taxonomy describes the weakness; review individual CVEs for product-specific impact.