CWE-94: Code Injection

How it's found

Code Injection is typically found by tracing untrusted input from where it enters the system to the point where it is used without the check or neutralization this weakness describes, combining manual code review with dynamic testing.

Vulnerable vs. safe

numbers = eval(input("Enter a comma-separated list of numbers: "))

print("Error: invalid input")return

sum = sum + numsum = 0try:except SyntaxError:for num in numbers:print(f"Sum of {numbers} = {sum}")def main():main()

sum = sum + int(num)for num in numbers:print(f"Sum of {numbers} = {sum}")

print("Error: invalid input")sum = 0numbers = input("Enter a comma-separated list of numbers: ").split(",")try:except ValueError:def main():main()

Consequences

• Bypass Protection Mechanism: In some cases, injectable code controls authentication; this may lead to a remote vulnerability.
• Gain Privileges or Assume Identity: Injected code can access resources that the attacker is directly prevented from accessing.
• 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 data integrity in nearly all cases, since the control-plane data injected is always incidental to data recall or writing.
• Hide Activities: Often the actions performed by injected control code are unlogged.

Mitigations

• 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: 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 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: 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: 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].

How TurboPentest tests for this (white-box)

This weakness (Code Injection) is caught by white-box static analysis when you connect a GitHub repo: IntegSec's Opengrep SAST rule pack carries 6 rules for it, flagging the issue directly in your source code as part of the pentest.

• Code Injection Tainted Input
• NoSQL Where Operator
• Code Injection Eval
• Preg Replace Eval Modifier
• Code Injection Eval Exec
• Code Injection Eval Tainted Input

Frequently asked questions

Related CWEs

• Class weakness
  CWE-74: Injection
• Class weakness
  CWE-913: Improper Control of Dynamically-Managed Code Resources