| Impact | Details |
|---|---|
|
Bypass Protection Mechanism |
Scope: Access Control
In some cases, injectable code controls authentication; this may lead to a remote vulnerability.
|
|
Gain Privileges or Assume Identity |
Scope: Access Control
Injected code can access resources that the attacker is directly prevented from accessing.
|
|
Execute Unauthorized Code or Commands |
Scope: Integrity, Confidentiality, Availability
When a product allows a user's input to contain code syntax, it might be possible for an attacker to craft the code in such a way that it will alter the intended control flow of the product. As a result, code injection can often result in the execution of arbitrary code. Code injection attacks can also lead to loss of data integrity in nearly all cases, since the control-plane data injected is always incidental to data recall or writing.
|
|
Hide Activities |
Scope: Non-Repudiation
Often the actions performed by injected control code are unlogged.
|
| Phase(s) | Mitigation |
|---|---|
|
Architecture and Design |
Refactor your program so that you do not have to dynamically generate code.
|
|
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. |
|
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. 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(). |
|
Testing |
Use automated static analysis tools that target this type of weakness. Many modern techniques use data flow analysis to minimize the number of false positives. This is not a perfect solution, since 100% accuracy and coverage are not feasible.
|
|
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.
|
|
Operation |
Strategy: Compilation or Build Hardening 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).
|
|
Operation |
Strategy: Environment Hardening 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).
|
|
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]. Effectiveness: Discouraged Common Practice |
| Nature | Type | ID | Name |
|---|---|---|---|
| ChildOf | Class Class - a weakness that is described in a very abstract fashion, typically independent of any specific language or technology. More specific than a Pillar Weakness, but more general than a Base Weakness. Class level weaknesses typically describe issues in terms of 1 or 2 of the following dimensions: behavior, property, and resource. | 74 | Improper Neutralization of Special Elements in Output Used by a Downstream Component ('Injection') |
| ChildOf | Class Class - a weakness that is described in a very abstract fashion, typically independent of any specific language or technology. More specific than a Pillar Weakness, but more general than a Base Weakness. Class level weaknesses typically describe issues in terms of 1 or 2 of the following dimensions: behavior, property, and resource. | 913 | Improper Control of Dynamically-Managed Code Resources |
| ParentOf | Variant Variant - a weakness that is linked to a certain type of product, typically involving a specific language or technology. More specific than a Base weakness. Variant level weaknesses typically describe issues in terms of 3 to 5 of the following dimensions: behavior, property, technology, language, and resource. | 95 | Improper Neutralization of Directives in Dynamically Evaluated Code ('Eval Injection') |
| ParentOf | Base Base - a weakness that is still mostly independent of a resource or technology, but with sufficient details to provide specific methods for detection and prevention. Base level weaknesses typically describe issues in terms of 2 or 3 of the following dimensions: behavior, property, technology, language, and resource. | 96 | Improper Neutralization of Directives in Statically Saved Code ('Static Code Injection') |
| ParentOf | Base Base - a weakness that is still mostly independent of a resource or technology, but with sufficient details to provide specific methods for detection and prevention. Base level weaknesses typically describe issues in terms of 2 or 3 of the following dimensions: behavior, property, technology, language, and resource. | 1336 | Improper Neutralization of Special Elements Used in a Template Engine |
| CanFollow | Variant Variant - a weakness that is linked to a certain type of product, typically involving a specific language or technology. More specific than a Base weakness. Variant level weaknesses typically describe issues in terms of 3 to 5 of the following dimensions: behavior, property, technology, language, and resource. | 98 | Improper Control of Filename for Include/Require Statement in PHP Program ('PHP Remote File Inclusion') |
| Nature | Type | ID | Name |
|---|---|---|---|
| MemberOf | Category Category - a CWE entry that contains a set of other entries that share a common characteristic. | 137 | Data Neutralization Issues |
| Nature | Type | ID | Name |
|---|---|---|---|
| ChildOf | Class Class - a weakness that is described in a very abstract fashion, typically independent of any specific language or technology. More specific than a Pillar Weakness, but more general than a Base Weakness. Class level weaknesses typically describe issues in terms of 1 or 2 of the following dimensions: behavior, property, and resource. | 74 | Improper Neutralization of Special Elements in Output Used by a Downstream Component ('Injection') |
| Nature | Type | ID | Name |
|---|---|---|---|
| MemberOf | Category Category - a CWE entry that contains a set of other entries that share a common characteristic. | 1019 | Validate Inputs |
| Phase | Note |
|---|---|
| Implementation | REALIZATION: This weakness is caused during implementation of an architectural security tactic. |
Class: Interpreted (Sometimes Prevalent)
AI/ML (Undetermined Prevalence)
Example 1
This example attempts to write user messages to a message file and allow users to view them.
While the programmer intends for the MessageFile to only include data, an attacker can provide a message such as:
which will decode to the following:
The programmer thought they were just including the contents of a regular data file, but PHP parsed it and executed the code. Now, this code is executed any time people view messages.
Notice that XSS (CWE-79) is also possible in this situation.
Example 2
edit-config.pl: This CGI script is used to modify settings in a configuration file.
The script intends to take the 'action' parameter and invoke one of a variety of functions based on the value of that parameter - config_file_add_key(), config_file_set_key(), or config_file_delete_key(). It could set up a conditional to invoke each function separately, but eval() is a powerful way of doing the same thing in fewer lines of code, especially when a large number of functions or variables are involved. Unfortunately, in this case, the attacker can provide other values in the action parameter, such as:
This would produce the following string in handleConfigAction():
Any arbitrary Perl code could be added after the attacker has "closed off" the construction of the original function call, in order to prevent parsing errors from causing the malicious eval() to fail before the attacker's payload is activated. This particular manipulation would fail after the system() call, because the "_key(\$fname, \$key, \$val)" portion of the string would cause an error, but this is irrelevant to the attack because the payload has already been activated.
Example 3
This simple script asks a user to supply a list of numbers as input and adds them together.
The eval() function can take the user-supplied list and convert it into a Python list object, therefore allowing the programmer to use list comprehension methods to work with the data. However, if code is supplied to the eval() function, it will execute that code. For example, a malicious user could supply the following string:
This would delete all the files in the current directory. For this reason, it is not recommended to use eval() with untrusted input.
A way to accomplish this without the use of eval() is to apply an integer conversion on the input within a try/except block. If the user-supplied input is not numeric, this will raise a ValueError. By avoiding eval(), there is no opportunity for the input string to be executed as code.
An alternative, commonly-cited mitigation for this kind of weakness is to use the ast.literal_eval() function, 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].
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.
| Reference | Description |
|---|---|
|
Math component in an LLM framework translates user input into a Python
expression that is input into the Python exec() method, allowing code
execution - one variant of a "prompt injection" attack.
|
|
|
Python-based library uses an LLM prompt containing user input to
dynamically generate code that is then fed as input into the Python
exec() method, allowing code execution - one variant of a "prompt
injection" attack.
|
|
|
Framework for LLM applications allows eval injection via a crafted response from a hosting provider.
|
|
|
Python compiler uses eval() to execute malicious strings as Python code.
|
|
|
"Code injection" in VPN product, as exploited in the wild per CISA KEV.
|
|
|
Eval injection in PHP program.
|
|
|
Eval injection in Perl program.
|
|
|
Eval injection in Perl program using an ID that should only contain hyphens and numbers.
|
|
|
Direct code injection into Perl eval function.
|
|
|
Eval injection in Perl program.
|
|
|
Direct code injection into Perl eval function.
|
|
|
Direct code injection into Perl eval function.
|
|
|
MFV. code injection into PHP eval statement using nested constructs that should not be nested.
|
|
|
MFV. code injection into PHP eval statement using nested constructs that should not be nested.
|
|
|
Code injection into Python eval statement from a field in a formatted file.
|
|
|
Eval injection in Python program.
|
|
|
chain: Resultant eval injection. An invalid value prevents initialization of variables, which can be modified by attacker and later injected into PHP eval statement.
|
|
|
Perl code directly injected into CGI library file from parameters to another CGI program.
|
|
|
Direct PHP code injection into supporting template file.
|
|
|
Direct code injection into PHP script that can be accessed by attacker.
|
|
|
PHP code from User-Agent HTTP header directly inserted into log file implemented as PHP script.
|
| Method | Details |
|---|---|
|
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.)
Effectiveness: High |
| Nature | Type | ID | Name |
|---|---|---|---|
| MemberOf | ViewView - a subset of CWE entries that provides a way of examining CWE content. The two main view structures are Slices (flat lists) and Graphs (containing relationships between entries). | 635 | Weaknesses Originally Used by NVD from 2008 to 2016 |
| MemberOf | CategoryCategory - a CWE entry that contains a set of other entries that share a common characteristic. | 752 | 2009 Top 25 - Risky Resource Management |
| MemberOf | ViewView - a subset of CWE entries that provides a way of examining CWE content. The two main view structures are Slices (flat lists) and Graphs (containing relationships between entries). | 884 | CWE Cross-section |
| MemberOf | CategoryCategory - a CWE entry that contains a set of other entries that share a common characteristic. | 991 | SFP Secondary Cluster: Tainted Input to Environment |
| MemberOf | ViewView - a subset of CWE entries that provides a way of examining CWE content. The two main view structures are Slices (flat lists) and Graphs (containing relationships between entries). | 1200 | Weaknesses in the 2019 CWE Top 25 Most Dangerous Software Errors |
| MemberOf | CategoryCategory - a CWE entry that contains a set of other entries that share a common characteristic. | 1347 | OWASP Top Ten 2021 Category A03:2021 - Injection |
| MemberOf | ViewView - a subset of CWE entries that provides a way of examining CWE content. The two main view structures are Slices (flat lists) and Graphs (containing relationships between entries). | 1350 | Weaknesses in the 2020 CWE Top 25 Most Dangerous Software Weaknesses |
| MemberOf | ViewView - a subset of CWE entries that provides a way of examining CWE content. The two main view structures are Slices (flat lists) and Graphs (containing relationships between entries). | 1387 | Weaknesses in the 2022 CWE Top 25 Most Dangerous Software Weaknesses |
| MemberOf | CategoryCategory - a CWE entry that contains a set of other entries that share a common characteristic. | 1409 | Comprehensive Categorization: Injection |
| MemberOf | ViewView - a subset of CWE entries that provides a way of examining CWE content. The two main view structures are Slices (flat lists) and Graphs (containing relationships between entries). | 1425 | Weaknesses in the 2023 CWE Top 25 Most Dangerous Software Weaknesses |
| MemberOf | ViewView - a subset of CWE entries that provides a way of examining CWE content. The two main view structures are Slices (flat lists) and Graphs (containing relationships between entries). | 1430 | Weaknesses in the 2024 CWE Top 25 Most Dangerous Software Weaknesses |
Rationale
This entry is frequently misused for vulnerabilities with a technical impact of "code execution," which does not by itself indicate a root cause weakness, since dozens of weaknesses can enable code execution.Comments
This weakness only applies when the product's functionality intentionally constructs all or part of a code segment. It could be that executing code could be the result of other weaknesses that do not involve the construction of code segments.Theoretical
Injection problems encompass a wide variety of issues -- all mitigated in very different ways. For this reason, the most effective way to discuss these weaknesses is to note the distinct features that classify them as injection weaknesses. The most important issue to note is that all injection problems share one thing in common -- i.e., they allow for the injection of control plane data into the user-controlled data plane. This means that the execution of the process may be altered by sending code in through legitimate data channels, using no other mechanism. While buffer overflows, and many other flaws, involve the use of some further issue to gain execution, injection problems need only for the data to be parsed. The most classic instantiations of this category of weakness are SQL injection and format string vulnerabilities.
| Mapped Taxonomy Name | Node ID | Fit | Mapped Node Name |
|---|---|---|---|
| PLOVER | CODE | Code Evaluation and Injection | |
| ISA/IEC 62443 | Part 4-2 | Req CR 3.5 | |
| ISA/IEC 62443 | Part 3-3 | Req SR 3.5 | |
| ISA/IEC 62443 | Part 4-1 | Req SVV-1 | |
| ISA/IEC 62443 | Part 4-1 | Req SVV-3 |
| Submissions | |||
|---|---|---|---|
| Submission Date | Submitter | Organization | |
|
2006年07月19日
(CWE Draft 3, 2006年07月19日) |
PLOVER | ||
| Contributions | |||
| Contribution Date | Contributor | Organization | |
|
2023年06月29日
(CWE 4.12, 2023年06月29日) |
"Mapping CWE to 62443" Sub-Working Group | CWE-CAPEC ICS/OT SIG | |
| Suggested mappings to ISA/IEC 62443. | |||
|
2024年02月29日
(CWE 4.17, 2025年04月03日) |
Abhi Balakrishnan | ||
| Contributed usability diagram concepts used by the CWE team. | |||
| Modifications | |||
| Modification Date | Modifier | Organization | |
|
2025年04月03日
(CWE 4.17, 2025年04月03日) |
CWE Content Team | MITRE | |
| updated Alternate_Terms, Common_Consequences, Description, Diagram, Theoretical_Notes | |||
|
2024年11月19日
(CWE 4.16, 2024年11月19日) |
CWE Content Team | MITRE | |
| updated Mapping_Notes, Relationships | |||
|
2024年07月16日
(CWE 4.15, 2024年07月16日) |
CWE Content Team | MITRE | |
| updated Applicable_Platforms, Observed_Examples | |||
|
2024年02月29日
(CWE 4.14, 2024年02月29日) |
CWE Content Team | MITRE | |
| updated Demonstrative_Examples, Potential_Mitigations, References | |||
| 2023年06月29日 | CWE Content Team | MITRE | |
| updated Mapping_Notes, Relationships, Taxonomy_Mappings | |||
| 2023年04月27日 | CWE Content Team | MITRE | |
| updated Demonstrative_Examples, Detection_Factors, Relationships, Time_of_Introduction | |||
| 2023年01月31日 | CWE Content Team | MITRE | |
| updated Demonstrative_Examples, Description, Potential_Mitigations, Relationships | |||
| 2022年10月13日 | CWE Content Team | MITRE | |
| updated Observed_Examples | |||
| 2022年06月28日 | CWE Content Team | MITRE | |
| updated Observed_Examples, Relationships | |||
| 2022年04月28日 | CWE Content Team | MITRE | |
| updated Research_Gaps | |||
| 2021年10月28日 | CWE Content Team | MITRE | |
| updated Relationships | |||
| 2021年07月20日 | CWE Content Team | MITRE | |
| updated Relationships | |||
| 2021年03月15日 | CWE Content Team | MITRE | |
| updated Demonstrative_Examples | |||
| 2020年08月20日 | CWE Content Team | MITRE | |
| updated Relationships | |||
| 2020年06月25日 | CWE Content Team | MITRE | |
| updated Potential_Mitigations | |||
| 2020年02月24日 | CWE Content Team | MITRE | |
| updated Potential_Mitigations, Relationships | |||
| 2019年09月19日 | CWE Content Team | MITRE | |
| updated Relationships | |||
| 2019年06月20日 | CWE Content Team | MITRE | |
| updated Related_Attack_Patterns, Type | |||
| 2017年11月08日 | CWE Content Team | MITRE | |
| updated Demonstrative_Examples, Modes_of_Introduction, Relationships | |||
| 2015年12月07日 | CWE Content Team | MITRE | |
| updated Relationships | |||
| 2014年07月30日 | CWE Content Team | MITRE | |
| updated Relationships | |||
| 2013年02月21日 | CWE Content Team | MITRE | |
| updated Relationships | |||
| 2012年10月30日 | CWE Content Team | MITRE | |
| updated Potential_Mitigations | |||
| 2012年05月11日 | CWE Content Team | MITRE | |
| updated Common_Consequences, Demonstrative_Examples, Observed_Examples, References, Relationships | |||
| 2011年06月01日 | CWE Content Team | MITRE | |
| updated Common_Consequences | |||
| 2011年03月29日 | CWE Content Team | MITRE | |
| updated Name | |||
| 2010年06月21日 | CWE Content Team | MITRE | |
| updated Description, Potential_Mitigations | |||
| 2010年02月16日 | CWE Content Team | MITRE | |
| updated Potential_Mitigations | |||
| 2009年05月27日 | CWE Content Team | MITRE | |
| updated Demonstrative_Examples, Name | |||
| 2009年03月10日 | CWE Content Team | MITRE | |
| updated Potential_Mitigations | |||
| 2009年01月12日 | CWE Content Team | MITRE | |
| updated Common_Consequences, Demonstrative_Examples, Description, Likelihood_of_Exploit, Name, Potential_Mitigations, Relationships | |||
| 2008年09月08日 | CWE Content Team | MITRE | |
| updated Applicable_Platforms, Relationships, Research_Gaps, Taxonomy_Mappings | |||
| 2008年07月01日 | Eric Dalci | Cigital | |
| updated Time_of_Introduction | |||
| Previous Entry Names | |||
| Change Date | Previous Entry Name | ||
| 2009年01月12日 | Code Injection | ||
| 2009年05月27日 | Failure to Control Generation of Code (aka 'Code Injection') | ||
| 2011年03月29日 | Failure to Control Generation of Code ('Code Injection') | ||
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