Weakness (CWE)
CWE-94: Improper Control of Generation of Code
The product constructs all or part of a code segment using externally-influenced input from an upstream component, but it does not neutralize or incorrectly neutralizes special elements that could modify the syntax or behavior of the intended code segment.
How to prevent it (7 mitigations)
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Architecture and Design
Refactor your program so that you do not have to dynamically generate code.
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Architecture and Design
Run your code in a "jail" or similar sandbox environment that enforces strict boundaries between the process and the operating system. This may effectively restrict which code can be executed by your product.
Examples include the Unix chroot jail and AppArmor. In general, managed code may provide some protection.
This may not be a feasible solution, and it only limits the impact to the operating system; the rest of your application may still be subject to compromise.
Be careful to avoid CWE-243 and other weaknesses related to jails.
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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 code injection, use stringent allowlists that limit which constructs are allowed. If you are dynamically constructing code that invokes a function, then verifying that the input is alphanumeric might be insufficient. An attacker might still be able to reference a dangerous function that you did not intend to allow, such as system(), exec(), or exit().
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Testing
Use dynamic tools and techniques that interact with the product using large test suites with many diverse inputs, such as fuzz testing (fuzzing), robustness testing, and fault injection. The product's operation may slow down, but it should not become unstable, crash, or generate incorrect results.
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Operation
Run the code in an environment that performs automatic taint propagation and prevents any command execution that uses tainted variables, such as Perl's "-T" switch. This will force the program to perform validation steps that remove the taint, although you must be careful to correctly validate your inputs so that you do not accidentally mark dangerous inputs as untainted (see CWE-183 and CWE-184).
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Operation
Run the code in an environment that performs automatic taint propagation and prevents any command execution that uses tainted variables, such as Perl's "-T" switch. This will force the program to perform validation steps that remove the taint, although you must be careful to correctly validate your inputs so that you do not accidentally mark dangerous inputs as untainted (see CWE-183 and CWE-184).
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Implementation
For Python programs, it is frequently encouraged to use the ast.literal_eval() function instead of eval, since it is intentionally designed to avoid executing code. However, an adversary could still cause excessive memory or stack consumption via deeply nested structures [REF-1372], so the python documentation discourages use of ast.literal_eval() on untrusted data [REF-1373].
Source: MITRE CWE-94
5,290 results · Feed
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Medium 6.5
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Medium 4.8
Popup Box 6.4.1 - 6.4.2 - Unauthenticated Arbitrary Shortcode Execution via Client-IP / X-Forwarded-For HTTP Headers
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Medium 5.3
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Medium 4.8
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High 8.8
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Low 2.5
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Medium 6.5
WordPress Broken Link Checker plugin <= 2.4.14.1 - Content Injection vulnerability
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Medium 6.5
Ocean Extra <= 2.6.0 - Unauthenticated Arbitrary Shortcode Execution via 'oceanwp_library' Shortcode Template
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Critical 9.8CVE-2026-104586 Public exploit
AUTOM8N (WHM/cPanel plugin) through commit 82821f7 contains an OS Command Injection in borg_restore.cgi.
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Medium 6.5
WeGIA: Pre-auth Installer Injection Chain Enables Command Execution and Arbitrary PHP Code Injection
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High 8.5
Markdown Preview Enhanced: Remote Code Execution via VM Sandbox Escape in `.crossnote/config.js` and `.crossnote/parser.js`
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Medium 5.3
WordPress MDTF plugin <= 1.3.9 - Arbitrary Code Execution vulnerability
Improper Control of Generation of Code ('Code Injection') vulnerability in PluginUs.Net MDTF wp-meta-data-filter-and-taxonomy-filter allows Code Injection.This issue affects MDTF: from n/a through 1.3.9.
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High 7.5
WordPress Salevo plugin <= 1.3.0 - Content Injection vulnerability
Improper Control of Generation of Code ('Code Injection') vulnerability in VillaTheme Salevo woo-boost-sales allows Code Injection.This issue affects Salevo: from n/a through 1.3.0.
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High 8.5
PAN-OS: Authenticated Remote Code Execution (RCE) in the Management Interface
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KEV Oct 14, 2026 -
Critical 9.9
HestiaCP Low-Privileged User to Root via Config-Field Injection and PATH Hijacking
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High 8.8
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High 7.5
WordPress Email Template Customizer for WooCommerce plugin <= 1.3.4 - Content Injection vulnerability
Improper Control of Generation of Code ('Code Injection') vulnerability in VillaTheme Email Template Customizer for WooCommerce email-template-customizer-for-woo allows Code Injection.This issue affects Email Template Customizer for WooCommerce: from n/a thro…
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High 7.2
Affiliate Toolkit 3.8.7 - 3.9.0 - Contributor+ RCE via BladeOne @php Directive
The affiliate-toolkit WordPress plugin before 3.9.1 does not prevent a low-privileged user from supplying a template body that its bundled templating engine compiles and executes as PHP, allowing users with the Contributor role or above to run arbitrary PHP c…
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High 8.8
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High 8.8
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Critical 9.1
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Critical 10.0
ColdFusion | Improper Control of Generation of Code ('Code Injection') (CWE-94)
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Critical 9.1
ColdFusion | Improper Control of Generation of Code ('Code Injection') (CWE-94)
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Critical 9.9
ColdFusion | Improper Control of Generation of Code ('Code Injection') (CWE-94)
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Critical 9.8
Omnispace Agora Project < 26.10.0 PHP Code Injection via config.inc.php
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High 8.8
ASP.NET Core Remote Code Execution Vulnerability
Improper control of generation of code ('code injection') in ASP.NET Core allows an unauthorized attacker to execute code over a network.
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High 7.8
Windows Assigned Access Elevation of Privilege Vulnerability
Improper control of generation of code ('code injection') in Windows Assigned Access allows an authorized attacker to elevate privileges locally.
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High 7.8
Windows Performance Monitor Elevation of Privilege Vulnerability
Improper control of generation of code ('code injection') in Windows Performance Monitor allows an authorized attacker to elevate privileges locally.
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High 8.8
Windows Encrypting File System (EFS) Remote Code Execution Vulnerability
Improper control of generation of code ('code injection') in Windows Encrypting File System (EFS) allows an authorized attacker to execute code over a network.
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High 8.8
Microsoft Office SharePoint Elevation of Privilege Vulnerability
Improper control of generation of code ('code injection') in Microsoft Office SharePoint allows an authorized attacker to elevate privileges over a network.
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High 8.8
Visual Studio Tools for Applications and SQL Server Management Studio Remote Code Execution Vulnerability
Improper control of generation of code ('code injection') in Visual Studio Tools for Applications and SQL Server Management Studio allows an unauthorized attacker to execute code over a network.
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High 8.8
dataclasses-avroschema enum symbols can inject statements through generated member names
dataclasses-avroschema generates Avro schemas from Python dataclasses, Pydantic models, and Faust Records and generates Python code from Avro schemas. From version 0.38.0 through 0.70.5, BaseGenerator.parse_enum and EnumRepresentation.render_symbols use each …
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High 8.8
dataclasses-avroschema allows code injection through fixed-type aliases supplied as a bare string
dataclasses-avroschema generates Avro schemas from Python dataclasses, Pydantic models, and Faust Records and generates Python code from Avro schemas. From version 0.38.0 through 0.70.5, BaseGenerator.parse_fixed interpolates a fixed type's aliases value dire…
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High 8.8
dataclasses-avroschema enum field defaults can inject statements into generated modules
dataclasses-avroschema generates Avro schemas from Python dataclasses, Pydantic models, and Faust Records and generates Python code from Avro schemas. From version 0.38.0 through 0.70.5, FieldRepresentation.get_field_default renders a schema-controlled enum f…
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High 8.8
dataclasses-avroschema allows code injection through generated enum-symbol string literals
dataclasses-avroschema generates Avro schemas from Python dataclasses, Pydantic models, and Faust Records and generates Python code from Avro schemas. From version 0.38.0 through 0.70.5, EnumRepresentation.render_symbols concatenates each schema-controlled en…
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High 8.8
dataclasses-avroschema pydantic-class metadata allows code injection in generated annotations
dataclasses-avroschema generates Avro schemas from Python dataclasses, Pydantic models, and Faust Records and generates Python code from Avro schemas. From version 0.44.0 through 0.70.5, the Pydantic and AvroDantic model generators insert a schema field's pyd…
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High 8.8
dataclasses-avroschema field documentation allows code injection in generated Pydantic descriptions
dataclasses-avroschema generates Avro schemas from Python dataclasses, Pydantic models, and Faust Records and generates Python code from Avro schemas. From version 0.65.9 through 0.70.5, PydanticFieldRepresentation.add_field_properties inserts a schema field'…
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High 8.8
dataclasses-avroschema fixed namespaces allow code injection in generated annotations
dataclasses-avroschema generates Avro schemas from Python dataclasses, Pydantic models, and Faust Records and generates Python code from Avro schemas. From version 0.38.0 through 0.70.5, BaseGenerator.parse_fixed inserts a fixed type's namespace value between…
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High 8.8
dataclasses-avroschema record documentation can terminate generated class docstrings
dataclasses-avroschema generates Avro schemas from Python dataclasses, Pydantic models, and Faust Records and generates Python code from Avro schemas. From version 0.40.0 through 0.70.5, ClassRepresentation.render_docstring copies a schema record's doc value …