The product allocates a reusable resource or group of resources on behalf of an actor without imposing any intended restrictions on the size or number of resources that can be allocated.

What CVEs are caused by CWE-770?

1,273 recorded CVEs are attributed to CWE-770, including CVE-2025-11832, CVE-2026-31283, CVE-2024-44241.

What are the consequences of CWE-770?

Exploiting CWE-770 can lead to: DoS: Resource Consumption (CPU), DoS: Resource Consumption (Memory), DoS: Resource Consumption (Other).

Is CWE-770 actively exploited?

1,273 recorded CVEs are caused by CWE-770; none are currently in CISA's KEV catalog of actively exploited flaws.

CWE-770: Allocation of Resources Without Limits or Throttling

Q: How is CWE-770 detected?

Manual Static Analysis: Manual static analysis can be useful for finding this weakness, but it might not achieve desired code coverage within limited time constraints. If denial-of-service is not considered a significant risk, or if there is strong emphasis on consequences such as code execution, then manual analysis may not focus on this weakness at all.

How to prevent it

Practical mitigations for CWE-770, grouped by where in the lifecycle they apply.

Requirements

Clearly specify the minimum and maximum expectations for capabilities, and dictate which behaviors are acceptable when resource allocation reaches limits.

Architecture and Design

Limit the amount of resources that are accessible to unprivileged users. Set per-user limits for resources. Allow the system administrator to define these limits. Be careful to avoid CWE-410.

Architecture and Design

Design throttling mechanisms into the system architecture. The best protection is to limit the amount of resources that an unauthorized user can cause to be expended. A strong authentication and access control model will help prevent such attacks from occurring in the first place, and it will help the administrator to identify who is committing the abuse. The login application should be protected against DoS attacks as much as possible. Limiting the database access, perhaps by caching result sets, can help minimize the resources expended. To further limit the potential for a DoS attack, consider tracking the rate of requests received from users and blocking requests that exceed a defined rate threshold.

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. 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.

Architecture and Design

For any security checks that are performed on the client side, ensure that these checks are duplicated on the server side, in order to avoid CWE-602. Attackers can bypass the client-side checks by modifying values after the checks have been performed, or by changing the client to remove the client-side checks entirely. Then, these modified values would be submitted to the server.

Architecture and Design

Mitigation of resource exhaustion attacks requires that the target system either:

The first of these solutions is an issue in itself though, since it may allow attackers to prevent the use of the system by a particular valid user. If the attacker impersonates the valid user, they may be able to prevent the user from accessing the server in question.

The second solution can be difficult to effectively institute -- and even when properly done, it does not provide a full solution. It simply requires more resources on the part of the attacker.

recognizes the attack and denies that user further access for a given amount of time, typically by using increasing time delays
uniformly throttles all requests in order to make it more difficult to consume resources more quickly than they can again be freed.

Architecture and Design

Ensure that protocols have specific limits of scale placed on them.

Architecture and Design

Implementation

If the program must fail, ensure that it fails gracefully (fails closed). There may be a temptation to simply let the program fail poorly in cases such as low memory conditions, but an attacker may be able to assert control before the software has fully exited. Alternately, an uncontrolled failure could cause cascading problems with other downstream components; for example, the program could send a signal to a downstream process so the process immediately knows that a problem has occurred and has a better chance of recovery.

Ensure that all failures in resource allocation place the system into a safe posture.

Operation

Architecture and Design

Resource Limitation

Use quotas or other resource-limiting settings provided by the operating system or environment. For example, when managing system resources in POSIX, setrlimit() can be used to set limits for certain types of resources, and getrlimit() can determine how many resources are available. However, these functions are not available on all operating systems.

When the current levels get close to the maximum that is defined for the application (see CWE-770), then limit the allocation of further resources to privileged users; alternately, begin releasing resources for less-privileged users. While this mitigation may protect the system from attack, it will not necessarily stop attackers from adversely impacting other users.

Ensure that the application performs the appropriate error checks and error handling in case resources become unavailable (CWE-703).

How to detect it

Manual Static Analysis

Manual static analysis can be useful for finding this weakness, but it might not achieve desired code coverage within limited time constraints. If denial-of-service is not considered a significant risk, or if there is strong emphasis on consequences such as code execution, then manual analysis may not focus on this weakness at all.

Fuzzing

While fuzzing is typically geared toward finding low-level implementation bugs, it can inadvertently find uncontrolled resource allocation problems. This can occur when the fuzzer generates a large number of test cases but does not restart the targeted product in between test cases. If an individual test case produces a crash, but it does not do so reliably, then an inability to limit resource allocation may be the cause.

When the allocation is directly affected by numeric inputs, then fuzzing may produce indications of this weakness.

Effectiveness: Opportunistic

Automated Dynamic Analysis

Certain automated dynamic analysis techniques may be effective in producing side effects of uncontrolled resource allocation problems, especially with resources such as processes, memory, and connections. The technique may involve generating a large number of requests to the product within a short time frame. Manual analysis is likely required to interpret the results.

Automated Static Analysis

Specialized configuration or tuning may be required to train automated tools to recognize this weakness.

Automated static analysis typically has limited utility in recognizing unlimited allocation problems, except for the missing release of program-independent system resources such as files, sockets, and processes, or unchecked arguments to memory. For system resources, automated static analysis may be able to detect circumstances in which resources are not released after they have expired, or if too much of a resource is requested at once, as can occur with memory. Automated analysis of configuration files may be able to detect settings that do not specify a maximum value.

Automated static analysis tools will not be appropriate for detecting exhaustion of custom resources, such as an intended security policy in which a bulletin board user is only allowed to make a limited number of posts per day.

Code examples

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

This code allocates a socket and forks each time it receives a new connection.

Vulnerable example

sock=socket(AF_INET, SOCK_STREAM, 0);

The program does not track how many connections have been made, and it does not limit the number of connections. Because forking is a relatively expensive operation, an attacker would be able to cause the system to run out of CPU, processes, or memory by making a large number of connections. Alternatively, an attacker could consume all available connections, preventing others from accessing the system remotely.

In the following example a server socket connection is used to accept a request to store data on the local file system using a specified filename. The method openSocketConnection establishes a server socket to accept requests from a client. When a client establishes a connection to this service the getNextMessage method is first used to retrieve from the socket the name of the file to store the data, the openFileToWrite method will validate the filename and open a file to write to on the local file system. The getNextMessage is then used within a while loop to continuously read data from the socket and output the data to the file until there is no longer any data from the socket.

Vulnerable example

int writeDataFromSocketToFile(char *host, int port)

This example creates a situation where data can be dumped to a file on the local file system without any limits on the size of the file. This could potentially exhaust file or disk resources and/or limit other clients' ability to access the service.

In the following example, the processMessage method receives a two dimensional character array containing the message to be processed. The two-dimensional character array contains the length of the message in the first character array and the message body in the second character array. The getMessageLength method retrieves the integer value of the length from the first character array. After validating that the message length is greater than zero, the body character array pointer points to the start of the second character array of the two-dimensional character array and memory is allocated for the new body character array.

Vulnerable example

/* process message accepts a two-dimensional character array of the form [length][body] containing the message to be processed */

Safe example

unsigned int length = getMessageLength(message[0]);

In the following example, a server object creates a server socket and accepts client connections to the socket. For every client connection to the socket a separate thread object is generated using the ClientSocketThread class that handles request made by the client through the socket.

Vulnerable example

java

public void acceptConnections() {

Safe example

java

public static final int SERVER_PORT = 4444;

An unnamed web site allowed a user to purchase tickets for an event. A menu option allowed the user to purchase up to 10 tickets, but the back end did not restrict the actual number of tickets that could be purchased.

Here the problem is that every time a connection is made, more memory is allocated. So if one just opened up more and more connections, eventually the machine would run out of memory.

Vulnerable example

bar connection() {

CWE-770: Allocation of Resources Without Limits or Throttling

Overview

Real-world CVEs

Common consequences

How it happens

When it is introduced

How to prevent it

How to detect it

Manual Static Analysis

Fuzzing

Automated Dynamic Analysis

Automated Static Analysis

Code examples

Illustrative examples

Terminology & mappings

Mapped taxonomies

Attack patterns

Frequently asked questions

References

Stay ahead of CWE-770

Overview

Real-world CVEs

Common consequences

How it happens

When it is introduced

How to prevent it

How to detect it

Manual Static Analysis

Fuzzing

Automated Dynamic Analysis

Automated Static Analysis

Code examples

Illustrative examples

Related weaknesses

Parent

Child

Related

Terminology & mappings

Mapped taxonomies

Attack patterns

Frequently asked questions

References

Stay ahead of CWE-770