CWE-770
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 intended restrictions on the size or number of resources that can be allocated.
CVE-2023-45142 (GCVE-0-2023-45142)
Vulnerability from cvelistv5 – Published: 2023-10-12 16:33 – Updated: 2025-02-13 17:13
VLAI
Title
OpenTelemetry-Go Contrib has DoS vulnerability in otelhttp due to unbound cardinality metrics
Summary
OpenTelemetry-Go Contrib is a collection of third-party packages for OpenTelemetry-Go. A handler wrapper out of the box adds labels `http.user_agent` and `http.method` that have unbound cardinality. It leads to the server's potential memory exhaustion when many malicious requests are sent to it. HTTP header User-Agent or HTTP method for requests can be easily set by an attacker to be random and long. The library internally uses `httpconv.ServerRequest` that records every value for HTTP `method` and `User-Agent`. In order to be affected, a program has to use the `otelhttp.NewHandler` wrapper and not filter any unknown HTTP methods or User agents on the level of CDN, LB, previous middleware, etc. Version 0.44.0 fixed this issue when the values collected for attribute `http.request.method` were changed to be restricted to a set of well-known values and other high cardinality attributes were removed. As a workaround to stop being affected, `otelhttp.WithFilter()` can be used, but it requires manual careful configuration to not log certain requests entirely. For convenience and safe usage of this library, it should by default mark with the label `unknown` non-standard HTTP methods and User agents to show that such requests were made but do not increase cardinality. In case someone wants to stay with the current behavior, library API should allow to enable it.
Severity
7.5 (High)
CWE
- CWE-770 - Allocation of Resources Without Limits or Throttling
Assigner
References
9 references
| URL | Tags |
|---|---|
| https://github.com/open-telemetry/opentelemetry-g… | x_refsource_CONFIRM |
| https://github.com/open-telemetry/opentelemetry-g… | x_refsource_MISC |
| https://github.com/open-telemetry/opentelemetry-g… | x_refsource_MISC |
| https://github.com/advisories/GHSA-cg3q-j54f-5p7p | x_refsource_MISC |
| https://github.com/open-telemetry/opentelemetry-g… | x_refsource_MISC |
| https://github.com/open-telemetry/opentelemetry-g… | x_refsource_MISC |
| https://github.com/open-telemetry/opentelemetry-g… | x_refsource_MISC |
| https://github.com/open-telemetry/opentelemetry-g… | x_refsource_MISC |
| https://lists.fedoraproject.org/archives/list/pac… |
Impacted products
1 product
| Vendor | Product | Version | |
|---|---|---|---|
| open-telemetry | opentelemetry-go-contrib |
Affected:
< 0.44.0
|
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CVE-2023-46130 (GCVE-0-2023-46130)
Vulnerability from cvelistv5 – Published: 2023-11-10 14:54 – Updated: 2024-09-03 18:57
VLAI
Title
Bypassing height value allowed in some theme components
Summary
Discourse is an open source platform for community discussion. Prior to version 3.1.3 of the `stable` branch and version 3.2.0.beta3 of the `beta` and `tests-passed` branches, some theme components allow users to add svgs with unlimited `height` attributes, and this can affect the availability of subsequent replies in a topic. Most Discourse instances are unaffected, only instances with the svgbob or the mermaid theme component are within scope. The issue is patched in version 3.1.3 of the `stable` branch and version 3.2.0.beta3 of the `beta` and `tests-passed` branches. As a workaround, disable or remove the relevant theme components.
Severity
4.3 (Medium)
CWE
- CWE-770 - Allocation of Resources Without Limits or Throttling
Assigner
References
3 references
| URL | Tags |
|---|---|
| https://github.com/discourse/discourse/security/a… | x_refsource_CONFIRM |
| https://github.com/discourse/discourse/commit/618… | x_refsource_MISC |
| https://github.com/discourse/discourse/commit/89a… | x_refsource_MISC |
Impacted products
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CVE-2023-4647 (GCVE-0-2023-4647)
Vulnerability from cvelistv5 – Published: 2023-09-01 10:30 – Updated: 2026-04-21 04:05
VLAI
Title
Allocation of Resources Without Limits or Throttling in GitLab
Summary
An issue has been discovered in GitLab affecting all versions starting from 15.2 before 16.1.5, all versions starting from 16.2 before 16.2.5, all versions starting from 16.3 before 16.3.1 in which the projects API pagination can be skipped, potentially leading to DoS on certain instances.
Severity
5.3 (Medium)
CWE
- CWE-770 - Allocation of Resources Without Limits or Throttling
Assigner
References
1 reference
| URL | Tags |
|---|---|
| https://gitlab.com/gitlab-org/gitlab/-/issues/414502 | issue-trackingpermissions-required |
Impacted products
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CVE-2023-46738 (GCVE-0-2023-46738)
Vulnerability from cvelistv5 – Published: 2024-01-03 15:35 – Updated: 2024-08-27 20:47
VLAI
Title
Authenticated users can crash the CubeFS servers with maliciously crafted requests
Summary
CubeFS is an open-source cloud-native file storage system. A security vulnerability was found in CubeFS HandlerNode in versions prior to 3.3.1 that could allow authenticated users to send maliciously-crafted requests that would crash the ObjectNode and deny other users from using it. The root cause was improper handling of incoming HTTP requests that could allow an attacker to control the ammount of memory that the ObjectNode would allocate. A malicious request could make the ObjectNode allocate more memory that the machine had available, and the attacker could exhaust memory by way of a single malicious request. An attacker would need to be authenticated in order to invoke the vulnerable code with their malicious request and have permissions to delete objects. In addition, the attacker would need to know the names of existing buckets of the CubeFS deployment - otherwise the request would be rejected before it reached the vulnerable code. As such, the most likely attacker is an inside user or an attacker that has breached the account of an existing user in the cluster. The issue has been patched in v3.3.1. There is no other mitigation besides upgrading.
Severity
6.5 (Medium)
CWE
- CWE-770 - Allocation of Resources Without Limits or Throttling
Assigner
References
2 references
| URL | Tags |
|---|---|
| https://github.com/cubefs/cubefs/security/advisor… | x_refsource_CONFIRM |
| https://github.com/cubefs/cubefs/commit/dd46c2487… | x_refsource_MISC |
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CVE-2023-47108 (GCVE-0-2023-47108)
Vulnerability from cvelistv5 – Published: 2023-11-10 18:31 – Updated: 2025-10-28 18:22
VLAI
Title
DoS vulnerability in otelgrpc (uncontrolled resource consumption) due to unbound cardinality metrics
Summary
OpenTelemetry-Go Contrib is a collection of third-party packages for OpenTelemetry-Go. Starting in version 0.37.0 and prior to version 0.46.0, the grpc Unary Server Interceptor out of the box adds labels `net.peer.sock.addr` and `net.peer.sock.port` that have unbound cardinality. It leads to the server's potential memory exhaustion when many malicious requests are sent. An attacker can easily flood the peer address and port for requests. Version 0.46.0 contains a fix for this issue. As a workaround to stop being affected, a view removing the attributes can be used. The other possibility is to disable grpc metrics instrumentation by passing `otelgrpc.WithMeterProvider` option with `noop.NewMeterProvider`.
Severity
7.5 (High)
CWE
- CWE-770 - Allocation of Resources Without Limits or Throttling
Assigner
References
7 references
| URL | Tags |
|---|---|
| https://github.com/open-telemetry/opentelemetry-g… | x_refsource_CONFIRM |
| https://github.com/open-telemetry/opentelemetry-g… | x_refsource_MISC |
| https://github.com/open-telemetry/opentelemetry-g… | x_refsource_MISC |
| https://github.com/open-telemetry/opentelemetry-g… | x_refsource_MISC |
| https://github.com/open-telemetry/opentelemetry-g… | x_refsource_MISC |
| https://github.com/open-telemetry/opentelemetry-g… | x_refsource_MISC |
| https://pkg.go.dev/go.opentelemetry.io/otel/metri… | x_refsource_MISC |
Impacted products
1 product
| Vendor | Product | Version | |
|---|---|---|---|
| open-telemetry | opentelemetry-go-contrib |
Affected:
>= 0.37.0, < 0.46.0
|
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CVE-2023-47120 (GCVE-0-2023-47120)
Vulnerability from cvelistv5 – Published: 2023-11-10 15:09 – Updated: 2024-09-03 18:55
VLAI
Title
Discourse DoS through Onebox favicon URL
Summary
Discourse is an open source platform for community discussion. In versions 3.1.0 through 3.1.2 of the `stable` branch and versions 3.1.0,beta6 through 3.2.0.beta2 of the `beta` and `tests-passed` branches, Redis memory can be depleted by crafting a site with an abnormally long favicon URL and drafting multiple posts which Onebox it. The issue is patched in version 3.1.3 of the `stable` branch and version 3.2.0.beta3 of the `beta` and `tests-passed` branches. There are no known workarounds.
Severity
7.5 (High)
CWE
- CWE-770 - Allocation of Resources Without Limits or Throttling
Assigner
References
3 references
| URL | Tags |
|---|---|
| https://github.com/discourse/discourse/security/a… | x_refsource_CONFIRM |
| https://github.com/discourse/discourse/commit/95a… | x_refsource_MISC |
| https://github.com/discourse/discourse/commit/e91… | x_refsource_MISC |
Impacted products
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CVE-2023-4912 (GCVE-0-2023-4912)
Vulnerability from cvelistv5 – Published: 2023-12-01 07:01 – Updated: 2026-04-30 04:06
VLAI
Title
Allocation of Resources Without Limits or Throttling in GitLab
Summary
An issue has been discovered in GitLab EE affecting all versions starting from 10.5 before 16.4.3, all versions starting from 16.5 before 16.5.3, all versions starting from 16.6 before 16.6.1. It was possible for an attacker to cause a client-side denial of service using malicious crafted mermaid diagram input.
Severity
CWE
- CWE-770 - Allocation of Resources Without Limits or Throttling
Assigner
References
2 references
| URL | Tags |
|---|---|
| https://gitlab.com/gitlab-org/gitlab/-/issues/424882 | issue-trackingpermissions-required |
| https://hackerone.com/reports/2137421 | technical-descriptionexploitpermissions-required |
Impacted products
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CVE-2023-50247 (GCVE-0-2023-50247)
Vulnerability from cvelistv5 – Published: 2023-12-12 19:56 – Updated: 2024-08-02 22:09
VLAI
Title
h2o QUIC state exhaustion DoS
Summary
h2o is an HTTP server with support for HTTP/1.x, HTTP/2 and HTTP/3. The QUIC stack (quicly), as used by H2O up to commit 43f86e5 (in version 2.3.0-beta and prior), is susceptible to a state exhaustion attack. When H2O is serving HTTP/3, a remote attacker can exploit this vulnerability to progressively increase the memory retained by the QUIC stack. This can eventually cause H2O to abort due to memory exhaustion. The vulnerability has been resolved in commit d67e81d03be12a9d53dc8271af6530f40164cd35. HTTP/1 and HTTP/2 are not affected by this vulnerability as they do not use QUIC. Administrators looking to mitigate this issue without upgrading can disable HTTP/3 support.
Severity
CWE
- CWE-770 - Allocation of Resources Without Limits or Throttling
Assigner
References
2 references
| URL | Tags |
|---|---|
| https://github.com/h2o/h2o/security/advisories/GH… | x_refsource_CONFIRM |
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CVE-2023-5072 (GCVE-0-2023-5072)
Vulnerability from cvelistv5 – Published: 2023-10-12 16:13 – Updated: 2025-02-13 17:19
VLAI
Title
DoS Vulnerability in JSON-Java
Summary
Denial of Service in JSON-Java versions up to and including 20230618. A bug in the parser means that an input string of modest size can lead to indefinite amounts of memory being used.
Severity
7.5 (High)
CWE
- CWE-770 - Allocation of Resources Without Limits or Throttling
Assigner
References
Impacted products
1 product
| Vendor | Product | Version | |
|---|---|---|---|
| https://github.com/stleary/JSON-java | n/a |
Affected:
0 , ≤ 20230618
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CVE-2023-50730 (GCVE-0-2023-50730)
Vulnerability from cvelistv5 – Published: 2023-12-22 20:36 – Updated: 2024-08-02 22:16
VLAI
Title
Grackle has StackOverflowError in GraphQL query processing
Summary
Grackle is a GraphQL server written in functional Scala, built on the Typelevel stack. The GraphQL specification requires that GraphQL fragments must not form cycles, either directly or indirectly. Prior to Grackle version 0.18.0, that requirement wasn't checked, and queries with cyclic fragments would have been accepted for type checking and compilation. The attempted compilation of such fragments would result in a JVM `StackOverflowError` being thrown. Some knowledge of an applications GraphQL schema would be required to construct such a query, however no knowledge of any application-specific performance or other behavioural characteristics would be needed.
Grackle uses the cats-parse library for parsing GraphQL queries. Prior to version 0.18.0, Grackle made use of the cats-parse `recursive` operator. However, `recursive` is not currently stack safe. `recursive` was used in three places in the parser: nested selection sets, nested input values (lists and objects), and nested list type declarations. Consequently, queries with deeply nested selection sets, input values or list types could be constructed which exploited this, causing a JVM `StackOverflowException` to be thrown during parsing. Because this happens very early in query processing, no specific knowledge of an applications GraphQL schema would be required to construct such a query.
The possibility of small queries resulting in stack overflow is a potential denial of service vulnerability. This potentially affects all applications using Grackle which have untrusted users. Both stack overflow issues have been resolved in the v0.18.0 release of Grackle. As a workaround, users could interpose a sanitizing layer in between untrusted input and Grackle query processing.
Severity
7.5 (High)
CWE
Assigner
References
3 references
| URL | Tags |
|---|---|
| https://github.com/typelevel/grackle/security/adv… | x_refsource_CONFIRM |
| https://github.com/typelevel/grackle/commit/56e24… | x_refsource_MISC |
| https://github.com/typelevel/grackle/releases/tag… | x_refsource_MISC |
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}
]
}
],
"providerMetadata": {
"dateUpdated": "2023-12-22T20:36:11.402Z",
"orgId": "a0819718-46f1-4df5-94e2-005712e83aaa",
"shortName": "GitHub_M"
},
"references": [
{
"name": "https://github.com/typelevel/grackle/security/advisories/GHSA-g56x-7j6w-g8r8",
"tags": [
"x_refsource_CONFIRM"
],
"url": "https://github.com/typelevel/grackle/security/advisories/GHSA-g56x-7j6w-g8r8"
},
{
"name": "https://github.com/typelevel/grackle/commit/56e244b91659cf385df590fc6c46695b6f36cbfd",
"tags": [
"x_refsource_MISC"
],
"url": "https://github.com/typelevel/grackle/commit/56e244b91659cf385df590fc6c46695b6f36cbfd"
},
{
"name": "https://github.com/typelevel/grackle/releases/tag/v0.18.0",
"tags": [
"x_refsource_MISC"
],
"url": "https://github.com/typelevel/grackle/releases/tag/v0.18.0"
}
],
"source": {
"advisory": "GHSA-g56x-7j6w-g8r8",
"discovery": "UNKNOWN"
},
"title": "Grackle has StackOverflowError in GraphQL query processing"
}
},
"cveMetadata": {
"assignerOrgId": "a0819718-46f1-4df5-94e2-005712e83aaa",
"assignerShortName": "GitHub_M",
"cveId": "CVE-2023-50730",
"datePublished": "2023-12-22T20:36:11.402Z",
"dateReserved": "2023-12-11T17:53:36.032Z",
"dateUpdated": "2024-08-02T22:16:47.266Z",
"state": "PUBLISHED"
},
"dataType": "CVE_RECORD",
"dataVersion": "5.1"
}
Mitigation
Phase: Requirements
Description:
- Clearly specify the minimum and maximum expectations for capabilities, and dictate which behaviors are acceptable when resource allocation reaches limits.
Mitigation
Phase: Architecture and Design
Description:
- 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.
Mitigation
Phase: Architecture and Design
Description:
- 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.
Mitigation ID: MIT-5
Phase: Implementation
Strategy: Input Validation
Description:
- 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.
Mitigation ID: MIT-15
Phase: Architecture and Design
Description:
- 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.
Mitigation
Phase: Architecture and Design
Description:
- 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.
Mitigation
Phase: Architecture and Design
Description:
- Ensure that protocols have specific limits of scale placed on them.
Mitigation ID: MIT-38.1
Phases: Architecture and Design, Implementation
Description:
- 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.
Mitigation ID: MIT-47
Phases: Operation, Architecture and Design
Strategy: Resource Limitation
Description:
- 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).
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.