CWE-770
Allocation of Resources Without Limits or Throttling
HIGH
Incomplete
2009-05-27 00:00 +00:00
2024-02-29 00:00 +00:00
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Allocation of Resources Without Limits or Throttling
The product allocates a reusable resource or group of resources on behalf of an actor without imposing any restrictions on the size or number of resources that can be allocated, in violation of the intended security policy for that actor.
Extended Description
Code frequently has to work with limited resources, so programmers must be careful to ensure that resources are not consumed too quickly, or too easily. Without use of quotas, resource limits, or other protection mechanisms, it can be easy for an attacker to consume many resources by rapidly making many requests, or causing larger resources to be used than is needed. When too many resources are allocated, or if a single resource is too large, then it can prevent the code from working correctly, possibly leading to a denial of service.
Informations
Modes Of Introduction
Architecture and Design : OMISSION: This weakness is caused by missing a security tactic during the architecture and design phase.Implementation
Operation
System Configuration
Applicable Platforms
Language
Class: Not Language-Specific (Often)Common Consequences
| Scope | Impact | Likelihood |
|---|---|---|
| Availability | DoS: Resource Consumption (CPU), DoS: Resource Consumption (Memory), DoS: Resource Consumption (Other) Note: When allocating resources without limits, an attacker could prevent other systems, applications, or processes from accessing the same type of resource. |
Observed Examples
| Reference | Description |
|---|---|
| Chain: Python library does not limit the resources used to process images that specify a very large number of bands (CWE-1284), leading to excessive memory consumption (CWE-789) or an integer overflow (CWE-190). | |
| Language interpreter does not restrict the number of temporary files being created when handling a MIME request with a large number of parts.. | |
| Driver does not use a maximum width when invoking sscanf style functions, causing stack consumption. | |
| Large integer value for a length property in an object causes a large amount of memory allocation. | |
| Product allows exhaustion of file descriptors when processing a large number of TCP packets. | |
| Communication product allows memory consumption with a large number of SIP requests, which cause many sessions to be created. | |
| Product allows attackers to cause a denial of service via a large number of directives, each of which opens a separate window. | |
| CMS does not restrict the number of searches that can occur simultaneously, leading to resource exhaustion. | |
| web application scanner attempts to read an excessively large file created by a user, causing process termination | |
| Go-based workload orchestrator does not limit resource usage with unauthenticated connections, allowing a DoS by flooding the service |
Potential Mitigations
Phases : RequirementsClearly specify the minimum and maximum expectations for capabilities, and dictate which behaviors are acceptable when resource allocation reaches limits.
Phases : 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.
Phases : 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.
Phases : 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.
Phases : 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.
Phases : Architecture and Design
Mitigation of resource exhaustion attacks requires that the target system either:
- 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.
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.
Phases : Architecture and Design
Ensure that protocols have specific limits of scale placed on them.
Phases : 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.
Phases : Operation // Architecture and Design
Use 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).
Detection Methods
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.
Vulnerability Mapping Notes
Rationale : This CWE entry is at the Base level of abstraction, which is a preferred level of abstraction for mapping to the root causes of vulnerabilities.Comments : Carefully read both the name and description to ensure that this mapping is an appropriate fit. Do not try to 'force' a mapping to a lower-level Base/Variant simply to comply with this preferred level of abstraction.
Related Attack Patterns
| CAPEC-ID | Attack Pattern Name |
|---|---|
| CAPEC-125 | Flooding An adversary consumes the resources of a target by rapidly engaging in a large number of interactions with the target. This type of attack generally exposes a weakness in rate limiting or flow. When successful this attack prevents legitimate users from accessing the service and can cause the target to crash. This attack differs from resource depletion through leaks or allocations in that the latter attacks do not rely on the volume of requests made to the target but instead focus on manipulation of the target's operations. The key factor in a flooding attack is the number of requests the adversary can make in a given period of time. The greater this number, the more likely an attack is to succeed against a given target. |
| CAPEC-130 | Excessive Allocation An adversary causes the target to allocate excessive resources to servicing the attackers' request, thereby reducing the resources available for legitimate services and degrading or denying services. Usually, this attack focuses on memory allocation, but any finite resource on the target could be the attacked, including bandwidth, processing cycles, or other resources. This attack does not attempt to force this allocation through a large number of requests (that would be Resource Depletion through Flooding) but instead uses one or a small number of requests that are carefully formatted to force the target to allocate excessive resources to service this request(s). Often this attack takes advantage of a bug in the target to cause the target to allocate resources vastly beyond what would be needed for a normal request. |
| CAPEC-147 | XML Ping of the Death An attacker initiates a resource depletion attack where a large number of small XML messages are delivered at a sufficiently rapid rate to cause a denial of service or crash of the target. Transactions such as repetitive SOAP transactions can deplete resources faster than a simple flooding attack because of the additional resources used by the SOAP protocol and the resources necessary to process SOAP messages. The transactions used are immaterial as long as they cause resource utilization on the target. In other words, this is a normal flooding attack augmented by using messages that will require extra processing on the target. |
| CAPEC-197 | Exponential Data Expansion An adversary submits data to a target application which contains nested exponential data expansion to produce excessively large output. Many data format languages allow the definition of macro-like structures that can be used to simplify the creation of complex structures. However, this capability can be abused to create excessive demands on a processor's CPU and memory. A small number of nested expansions can result in an exponential growth in demands on memory. |
| CAPEC-229 | Serialized Data Parameter Blowup This attack exploits certain serialized data parsers (e.g., XML, YAML, etc.) which manage data in an inefficient manner. The attacker crafts an serialized data file with multiple configuration parameters in the same dataset. In a vulnerable parser, this results in a denial of service condition where CPU resources are exhausted because of the parsing algorithm. The weakness being exploited is tied to parser implementation and not language specific. |
| CAPEC-230 | Serialized Data with Nested Payloads Applications often need to transform data in and out of a data format (e.g., XML and YAML) by using a parser. It may be possible for an adversary to inject data that may have an adverse effect on the parser when it is being processed. Many data format languages allow the definition of macro-like structures that can be used to simplify the creation of complex structures. By nesting these structures, causing the data to be repeatedly substituted, an adversary can cause the parser to consume more resources while processing, causing excessive memory consumption and CPU utilization. |
| CAPEC-231 | Oversized Serialized Data Payloads An adversary injects oversized serialized data payloads into a parser during data processing to produce adverse effects upon the parser such as exhausting system resources and arbitrary code execution. |
| CAPEC-469 | HTTP DoS An attacker performs flooding at the HTTP level to bring down only a particular web application rather than anything listening on a TCP/IP connection. This denial of service attack requires substantially fewer packets to be sent which makes DoS harder to detect. This is an equivalent of SYN flood in HTTP. The idea is to keep the HTTP session alive indefinitely and then repeat that hundreds of times. This attack targets resource depletion weaknesses in web server software. The web server will wait to attacker's responses on the initiated HTTP sessions while the connection threads are being exhausted. |
| CAPEC-482 | TCP Flood An adversary may execute a flooding attack using the TCP protocol with the intent to deny legitimate users access to a service. These attacks exploit the weakness within the TCP protocol where there is some state information for the connection the server needs to maintain. This often involves the use of TCP SYN messages. |
| CAPEC-486 | UDP Flood An adversary may execute a flooding attack using the UDP protocol with the intent to deny legitimate users access to a service by consuming the available network bandwidth. Additionally, firewalls often open a port for each UDP connection destined for a service with an open UDP port, meaning the firewalls in essence save the connection state thus the high packet nature of a UDP flood can also overwhelm resources allocated to the firewall. UDP attacks can also target services like DNS or VoIP which utilize these protocols. Additionally, due to the session-less nature of the UDP protocol, the source of a packet is easily spoofed making it difficult to find the source of the attack. |
| CAPEC-487 | ICMP Flood An adversary may execute a flooding attack using the ICMP protocol with the intent to deny legitimate users access to a service by consuming the available network bandwidth. A typical attack involves a victim server receiving ICMP packets at a high rate from a wide range of source addresses. Additionally, due to the session-less nature of the ICMP protocol, the source of a packet is easily spoofed making it difficult to find the source of the attack. |
| CAPEC-488 | HTTP Flood An adversary may execute a flooding attack using the HTTP protocol with the intent to deny legitimate users access to a service by consuming resources at the application layer such as web services and their infrastructure. These attacks use legitimate session-based HTTP GET requests designed to consume large amounts of a server's resources. Since these are legitimate sessions this attack is very difficult to detect. |
| CAPEC-489 | SSL Flood An adversary may execute a flooding attack using the SSL protocol with the intent to deny legitimate users access to a service by consuming all the available resources on the server side. These attacks take advantage of the asymmetric relationship between the processing power used by the client and the processing power used by the server to create a secure connection. In this manner the attacker can make a large number of HTTPS requests on a low provisioned machine to tie up a disproportionately large number of resources on the server. The clients then continue to keep renegotiating the SSL connection. When multiplied by a large number of attacking machines, this attack can result in a crash or loss of service to legitimate users. |
| CAPEC-490 | Amplification An adversary may execute an amplification where the size of a response is far greater than that of the request that generates it. The goal of this attack is to use a relatively few resources to create a large amount of traffic against a target server. To execute this attack, an adversary send a request to a 3rd party service, spoofing the source address to be that of the target server. The larger response that is generated by the 3rd party service is then sent to the target server. By sending a large number of initial requests, the adversary can generate a tremendous amount of traffic directed at the target. The greater the discrepancy in size between the initial request and the final payload delivered to the target increased the effectiveness of this attack. |
| CAPEC-491 | Quadratic Data Expansion An adversary exploits macro-like substitution to cause a denial of service situation due to excessive memory being allocated to fully expand the data. The result of this denial of service could cause the application to freeze or crash. This involves defining a very large entity and using it multiple times in a single entity substitution. CAPEC-197 is a similar attack pattern, but it is easier to discover and defend against. This attack pattern does not perform multi-level substitution and therefore does not obviously appear to consume extensive resources. |
| CAPEC-493 | SOAP Array Blowup An adversary may execute an attack on a web service that uses SOAP messages in communication. By sending a very large SOAP array declaration to the web service, the attacker forces the web service to allocate space for the array elements before they are parsed by the XML parser. The attacker message is typically small in size containing a large array declaration of say 1,000,000 elements and a couple of array elements. This attack targets exhaustion of the memory resources of the web service. |
| CAPEC-494 | TCP Fragmentation An adversary may execute a TCP Fragmentation attack against a target with the intention of avoiding filtering rules of network controls, by attempting to fragment the TCP packet such that the headers flag field is pushed into the second fragment which typically is not filtered. |
| CAPEC-495 | UDP Fragmentation An attacker may execute a UDP Fragmentation attack against a target server in an attempt to consume resources such as bandwidth and CPU. IP fragmentation occurs when an IP datagram is larger than the MTU of the route the datagram has to traverse. Typically the attacker will use large UDP packets over 1500 bytes of data which forces fragmentation as ethernet MTU is 1500 bytes. This attack is a variation on a typical UDP flood but it enables more network bandwidth to be consumed with fewer packets. Additionally it has the potential to consume server CPU resources and fill memory buffers associated with the processing and reassembling of fragmented packets. |
| CAPEC-496 | ICMP Fragmentation An attacker may execute a ICMP Fragmentation attack against a target with the intention of consuming resources or causing a crash. The attacker crafts a large number of identical fragmented IP packets containing a portion of a fragmented ICMP message. The attacker these sends these messages to a target host which causes the host to become non-responsive. Another vector may be sending a fragmented ICMP message to a target host with incorrect sizes in the header which causes the host to hang. |
| CAPEC-528 | XML Flood An adversary may execute a flooding attack using XML messages with the intent to deny legitimate users access to a web service. These attacks are accomplished by sending a large number of XML based requests and letting the service attempt to parse each one. In many cases this type of an attack will result in a XML Denial of Service (XDoS) due to an application becoming unstable, freezing, or crashing. |
Notes
This entry is different from uncontrolled resource consumption (CWE-400) in that there are other weaknesses that are related to inability to control resource consumption, such as holding on to a resource too long after use, or not correctly keeping track of active resources so that they can be managed and released when they are finished (CWE-771).Vulnerability theory is largely about how behaviors and resources interact. "Resource exhaustion" can be regarded as either a consequence or an attack, depending on the perspective. This entry is an attempt to reflect one of the underlying weaknesses that enable these attacks (or consequences) to take place.
References
REF-386
Detection and Prediction of Resource-Exhaustion VulnerabilitiesJoao Antunes, Nuno Ferreira Neves, Paulo Verissimo.
http://homepages.di.fc.ul.pt/~nuno/PAPERS/ISSRE08.pdf
REF-387
Resource exhaustionD.J. Bernstein.
http://cr.yp.to/docs/resources.html
REF-388
Resource exhaustionPascal Meunier.
http://homes.cerias.purdue.edu/~pmeunier/secprog/sanitized/class1/6.resource%20exhaustion.ppt
REF-7
Writing Secure CodeMichael Howard, David LeBlanc.
https://www.microsoftpressstore.com/store/writing-secure-code-9780735617223
REF-667
Real-Life Example of a 'Business Logic Defect' (Screen Shots!)Rafal Los.
http://h30501.www3.hp.com/t5/Following-the-White-Rabbit-A/Real-Life-Example-of-a-Business-Logic-Defect-Screen-Shots/ba-p/22581
REF-672
Top 25 Series - Rank 22 - Allocation of Resources Without Limits or ThrottlingFrank Kim.
https://web.archive.org/web/20170113055136/https://software-security.sans.org/blog/2010/03/23/top-25-series-rank-22-allocation-of-resources-without-limits-or-throttling/
REF-62
The Art of Software Security AssessmentMark Dowd, John McDonald, Justin Schuh.
Submission
| Name | Organization | Date | Date Release | Version |
|---|---|---|---|---|
| CWE Content Team | MITRE | 1.4 |
Modifications
| Name | Organization | Date | Comment |
|---|---|---|---|
| CWE Content Team | MITRE | updated Related_Attack_Patterns | |
| CWE Content Team | MITRE | updated Relationships | |
| CWE Content Team | MITRE | updated Applicable_Platforms, Demonstrative_Examples, Detection_Factors, Observed_Examples, References, Time_of_Introduction | |
| CWE Content Team | MITRE | updated Common_Consequences, Detection_Factors, Potential_Mitigations, References, Related_Attack_Patterns, Relationships | |
| CWE Content Team | MITRE | updated Common_Consequences, Demonstrative_Examples, Related_Attack_Patterns | |
| CWE Content Team | MITRE | updated Common_Consequences, Potential_Mitigations, References | |
| CWE Content Team | MITRE | updated Demonstrative_Examples, Potential_Mitigations | |
| CWE Content Team | MITRE | updated Demonstrative_Examples, Detection_Factors, Relationships | |
| CWE Content Team | MITRE | updated Common_Consequences, Relationships, Taxonomy_Mappings | |
| CWE Content Team | MITRE | updated Relationships | |
| CWE Content Team | MITRE | updated Relationships, Taxonomy_Mappings | |
| CWE Content Team | MITRE | updated Demonstrative_Examples, References, Related_Attack_Patterns, Relationships, Taxonomy_Mappings | |
| CWE Content Team | MITRE | updated Potential_Mitigations | |
| CWE Content Team | MITRE | updated Related_Attack_Patterns | |
| CWE Content Team | MITRE | updated Related_Attack_Patterns | |
| CWE Content Team | MITRE | updated Relationships | |
| CWE Content Team | MITRE | updated Related_Attack_Patterns | |
| CWE Content Team | MITRE | updated Related_Attack_Patterns | |
| CWE Content Team | MITRE | updated Demonstrative_Examples, Likelihood_of_Exploit, Modes_of_Introduction, Potential_Mitigations, References, Relationships, Taxonomy_Mappings | |
| CWE Content Team | MITRE | updated References | |
| CWE Content Team | MITRE | updated Demonstrative_Examples, Description, Relationships, Taxonomy_Mappings | |
| CWE Content Team | MITRE | updated Related_Attack_Patterns, Relationships | |
| CWE Content Team | MITRE | updated Potential_Mitigations, Related_Attack_Patterns, Relationships | |
| CWE Content Team | MITRE | updated Applicable_Platforms, Description, Maintenance_Notes, Potential_Mitigations, Relationship_Notes, Relationships | |
| CWE Content Team | MITRE | updated Relationships | |
| CWE Content Team | MITRE | updated Observed_Examples | |
| CWE Content Team | MITRE | updated Observed_Examples, References | |
| CWE Content Team | MITRE | updated Description, Detection_Factors | |
| CWE Content Team | MITRE | updated References, Relationships | |
| CWE Content Team | MITRE | updated Mapping_Notes | |
| CWE Content Team | MITRE | updated Taxonomy_Mappings |
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