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.

Extended Description

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. Such an alteration could lead to arbitrary code execution.

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 which 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.

Related Weaknesses

Modes of Introduction

Applicable Platforms

Languages

Class: Interpreted

Technologies

Likelihood Of Exploit

Medium

Common Consequences

Detection Methods

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

Potential 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

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).

Observed Examples

• CVE-2022-2054: Python compiler uses eval() to execute malicious strings as Python code.
• CVE-2021-22204: Chain: regex in EXIF processor code does not correctly determine where a string ends (CWE-625), enabling eval injection (CWE-95), as exploited in the wild per CISA KEV.
• CVE-2020-8218: “Code injection” in VPN product, as exploited in the wild per CISA KEV.
• CVE-2008-5071: Eval injection in PHP program.
• CVE-2002-1750: Eval injection in Perl program.
• CVE-2008-5305: Eval injection in Perl program using an ID that should only contain hyphens and numbers.
• CVE-2002-1752: Direct code injection into Perl eval function.
• CVE-2002-1753: Eval injection in Perl program.
• CVE-2005-1527: Direct code injection into Perl eval function.
• CVE-2005-2837: Direct code injection into Perl eval function.
• CVE-2005-1921: MFV. code injection into PHP eval statement using nested constructs that should not be nested.
• CVE-2005-2498: MFV. code injection into PHP eval statement using nested constructs that should not be nested.
• CVE-2005-3302: Code injection into Python eval statement from a field in a formatted file.
• CVE-2007-1253: Eval injection in Python program.
• CVE-2001-1471: chain: Resultant eval injection. An invalid value prevents initialization of variables, which can be modified by attacker and later injected into PHP eval statement.
• CVE-2002-0495: Perl code directly injected into CGI library file from parameters to another CGI program.
• CVE-2005-1876: Direct PHP code injection into supporting template file.
• CVE-2005-1894: Direct code injection into PHP script that can be accessed by attacker.
• CVE-2003-0395: PHP code from User-Agent HTTP header directly inserted into log file implemented as PHP script.