The product receives data from an HTTP agent/component (e.g., web server, proxy, browser, etc.), but it does not neutralize or incorrectly neutralizes CR and LF characters before the data is included in outgoing HTTP headers.

What CVEs are caused by CWE-113?

71 recorded CVEs are attributed to CWE-113, including CVE-2026-38967, CVE-2024-40324, CVE-2019-25101.

How is CWE-113 detected?

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.)

What are the consequences of CWE-113?

Exploiting CWE-113 can lead to: Modify Application Data, Gain Privileges or Assume Identity.

Is CWE-113 actively exploited?

71 recorded CVEs are caused by CWE-113; none are currently in CISA's KEV catalog of actively exploited flaws.

CWE-113: Improper Neutralization of CRLF Sequences in HTTP Headers ('HTTP Request/Response Splitting') (HTTP Request Splitting)

How to prevent it

Practical mitigations for CWE-113, grouped by where in the lifecycle they apply.

Implementation

Input Validation

Construct HTTP headers very carefully, avoiding the use of non-validated input data.

Implementation

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. If an input does not strictly conform to specifications, reject it or transform it into something that conforms.

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.

Implementation

Output Encoding

Use and specify an output encoding that can be handled by the downstream component that is reading the output. Common encodings include ISO-8859-1, UTF-7, and UTF-8. When an encoding is not specified, a downstream component may choose a different encoding, either by assuming a default encoding or automatically inferring which encoding is being used, which can be erroneous. When the encodings are inconsistent, the downstream component might treat some character or byte sequences as special, even if they are not special in the original encoding. Attackers might then be able to exploit this discrepancy and conduct injection attacks; they even might be able to bypass protection mechanisms that assume the original encoding is also being used by the downstream component.

Implementation

Input Validation

Inputs should be decoded and canonicalized to the application's current internal representation before being validated (CWE-180). Make sure that the application does not decode the same input twice (CWE-174). Such errors could be used to bypass allowlist validation schemes by introducing dangerous inputs after they have been checked.

Code examples

Illustrative examples from MITRE showing how the weakness appears in code.

The following code segment reads the name of the author of a weblog entry, author, from an HTTP request and sets it in a cookie header of an HTTP response.

Vulnerable example

java

String author = request.getParameter(AUTHOR_PARAM);

Resulting query

plaintext

HTTP/1.1 200 OK

Attack input

plaintext

Wiley Hacker\r\nHTTP/1.1 200 OK\r\n

Resulting query

plaintext

HTTP/1.1 200 OK

An attacker can make a single request to a vulnerable server that will cause the server to create two responses, the second of which may be misinterpreted as a response to a different request, possibly one made by another user sharing the same TCP connection with the server.

Cross-User Defacement can be accomplished by convincing the user to submit the malicious request themselves, or remotely in situations where the attacker and the user share a common TCP connection to the server, such as a shared proxy server.

In the best case, an attacker can leverage this ability to convince users that the application has been hacked, causing users to lose confidence in the security of the application.

In the worst case, an attacker may provide specially crafted content designed to mimic the behavior of the application but redirect private information, such as account numbers and passwords, back to the attacker.

The impact of a maliciously constructed response can be magnified if it is cached, either by a web cache used by multiple users or even the browser cache of a single user.

Cache Poisoning: if a response is cached in a shared web cache, such as those commonly found in proxy servers, then all users of that cache will continue receive the malicious content until the cache entry is purged. Similarly, if the response is cached in the browser of an individual user, then that user will continue to receive the malicious content until the cache entry is purged, although the user of the local browser instance will be affected.

Once attackers have control of the responses sent by an application, they have a choice of a variety of malicious content to provide users.

Cross-Site Scripting: cross-site scripting is common form of attack where malicious JavaScript or other code included in a response is executed in the user's browser.

The variety of attacks based on XSS is almost limitless, but they commonly include transmitting private data like cookies or other session information to the attacker, redirecting the victim to web content controlled by the attacker, or performing other malicious operations on the user's machine under the guise of the vulnerable site.

The most common and dangerous attack vector against users of a vulnerable application uses JavaScript to transmit session and authentication information back to the attacker who can then take complete control of the victim's account.

In addition to using a vulnerable application to send malicious content to a user, the same weakness can also be leveraged to redirect sensitive content generated by the server to the attacker instead of the intended user.

Page Hijacking: by submitting a request that results in two responses, the intended response from the server and the response generated by the attacker, an attacker can cause an intermediate node, such as a shared proxy server, to misdirect a response generated by the server to the attacker instead of the intended user.

Because the request made by the attacker generates two responses, the first is interpreted as a response to the attacker's request, while the second remains in limbo. When the user makes a legitimate request through the same TCP connection, the attacker's request is already waiting and is interpreted as a response to the victim's request. The attacker then sends a second request to the server, to which the proxy server responds with the server generated request intended for the victim, thereby compromising any sensitive information in the headers or body of the response intended for the victim.

CWE-113: Improper Neutralization of CRLF Sequences in HTTP Headers ('HTTP Request/Response Splitting')

Overview

Real-world CVEs

Common consequences

How it happens

When it is introduced

Applies to

How to prevent it

How to detect it

Automated Static Analysis

Code examples

Illustrative examples

Terminology & mappings

Alternate terms

Mapped taxonomies

Attack patterns

Frequently asked questions

References

Stay ahead of CWE-113

Overview

Real-world CVEs

Common consequences

How it happens

When it is introduced

Applies to

How to prevent it

How to detect it

Automated Static Analysis

Code examples

Illustrative examples

Related weaknesses

Parent

Can precede

Terminology & mappings

Alternate terms

Mapped taxonomies

Attack patterns

Frequently asked questions

References

Stay ahead of CWE-113