CWE-94: Improper Control of Generation of Code ('Code Injection')
Description
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.
- Abstraction
- BaseA weakness specific enough to point to detection and prevention methods.
- Likelihood of exploit
- Medium
- Status
- Draft
Common consequences
- Access Control
Bypass Protection Mechanism
In some cases, injectable code controls authentication; this may lead to a remote vulnerability.
- Access Control
Gain Privileges or Assume Identity
Injected code can access resources that the attacker is directly prevented from accessing.
- IntegrityConfidentialityAvailability
Execute Unauthorized Code or Commands
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...
- Non-Repudiation
Hide Activities
Often the actions performed by injected control code are unlogged.
Potential mitigations
- Architecture and DesignRefactoring
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.
- ImplementationInput 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...
- 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.
- OperationCompilation 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).
- OperationEnvironment 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).
- ImplementationEffectiveness: Discouraged Common Practice
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, so the python documentation discourages use of ast.literal_eval() on untrusted data.