Common Weakness Enumeration
CWE-770
AllowedAllocation of Resources Without Limits or Throttling
Abstraction: Base · Status: Incomplete
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.
1852 vulnerabilities reference this CWE, most recent first.
CVE-2026-111383 (GCVE-0-2026-111383)
Vulnerability from cvelistv5 – Published: 2026-10-16 01:17 – Updated: 2026-10-16 16:24
VLAI
EPSS
VEX
Title
Nezha 2.0.13 before 2.3.15 Denial of Service via /api/v1/ws/transfer WebSocket
Summary
Nezha from 2.0.13 before 2.3.15 contains a resource exhaustion vulnerability that allows authenticated users to open unbounded concurrent connections to the /api/v1/ws/transfer WebSocket endpoint. Attackers can hold thousands of subscriptions created by ServerTransferClass.Subscribe without limits, exhausting file descriptors, memory, and goroutines and blocking agent gRPC reconnections.
Severity
SSVC
Exploitation: poc
Automatable: no
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-10-16 16:23 UTC
CWE
- CWE-770 - Allocation of Resources Without Limits or Throttling
Assigner
VulnCheck
CNA
References
3 references
| URL | Tags |
|---|---|
| https://github.com/nezhahq/nezha/security/advisor… | vendor-advisory |
| https://github.com/nezhahq/nezha/commit/36b742a7e… | patch |
| https://www.vulncheck.com/advisories/nezha-2.0.13… | third-party-advisory |
Impacted products
Date Public
2026-10-01 00:00
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CVE-2026-111108 (GCVE-0-2026-111108)
Vulnerability from cvelistv5 – Published: 2026-10-28 16:38 – Updated: 2026-11-05 19:16
VLAI
EPSS
VEX
Title
Apache Kafka: Broker OutOfMemoryError via array allocation amplification in code-generated protocol readers
Summary
Apache Kafka's code-generated protocol readers pre-size an array's collection from the element count declared by the sender. That count is checked only against the bytes remaining in the request buffer, which assumes about one byte per element; because most elements need several bytes, a request can declare far more elements than the buffer holds and still pass. For a keyed array the reader then allocates an ImplicitLinkedHashCollection of capacity (2 * count +1), so a request of a few tens of megabytes can force a heap allocation several times larger before any element is read. The pattern is emitted into every generated reader, so it affects all Kafka API types with an array field.
Impact:
Request parsing happens before any authorization check. On a listener that does not require authentication (for example PLAINTEXT), an unauthenticated attacker can send a few concurrent requests that each declare a very large=
array length and allocate many times their wire size in broker heap, crashing the broker with an OutOfMemoryError. The reporter demonstrated three concurrent ~90 MB ProduceRequest (v3) connections exhausting a 1 GB heap (~8x amplification). On listeners that require authentication, the attacker needs valid credentials but no specific ACL, since parsing precedes authorization..
Mitigation:
Upgrade to Apache Kafka 4.2.2, 4.3.2, or 4.4.0. Until then, lowering socket.request.max.bytes and restricting network access to broker listeners reduces, but does not remove, exposure.
Resolution:
From Apache Kafka 4.2.2, 4.3.2, and 4.4.0: generated readers cap the initial array pre-allocation at MessageUtil.MAX_PREALLOCATED_ARRAY_CAPACITY (1000) and grow it on demand, and reject a declared array length above MessageUtil.MAX_ARRAY_LENGTH (1,000,000).
Severity
9.1 (Critical)
SSVC
Exploitation: none
Automatable: yes
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-11-05 19:16 UTC
CWE
Assigner
apache
CNA
References
2 references
| URL | Tags |
|---|---|
| https://kafka.apache.org/cve-list | vendor-advisory |
| http://www.openwall.com/lists/oss-security/2026/1… |
Impacted products
1 product
| Vendor | Product | Version | |
|---|---|---|---|
| Apache Software Foundation | Apache Kafka |
Affected:
3.3.0 , ≤ 4.1.2
(semver)
Affected: 4.2.0 , ≤ 4.2.1 (semver) Affected: 4.3.0 , ≤ 4.3.1 (semver) |
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CVE-2026-111101 (GCVE-0-2026-111101)
Vulnerability from cvelistv5 – Published: 2026-10-26 13:31 – Updated: 2026-10-26 15:35
VLAI
EPSS
VEX
Title
HTTP/1.1 chunked request bodies made of 1-byte chunks amplify memory use in Bandit
Summary
Allocation of Resources Without Limits or Throttling vulnerability in the HTTP/1.1 chunked body reader of mtrudel bandit allows an unauthenticated remote attacker to exhaust server memory and CPU via a request body made of many 1-byte chunks.
The chunked reader in lib/bandit/http1/socket.ex keeps every chunk as its own list cell and binary term until IO.iodata_to_binary/1 joins them, and nothing limits the number of chunks. The :length option of read_body/2 counts only data bytes, so tiny chunks cost far more memory than their payload: 48 MB of 1-byte chunks grew one handler process to about 500 MB and took about 6 s of CPU. The route does not need to read the body, because on keep-alive connections ensure_completed/1 drains unread bodies through the same reader.
This issue affects bandit: from 0.1.0 before 1.14.0.
Severity
SSVC
Exploitation: none
Automatable: yes
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-10-26 15:10 UTC
CWE
- CWE-770 - Allocation of Resources Without Limits or Throttling
Assigner
EEF
CNA
References
5 references
| URL | Tags |
|---|---|
| https://github.com/mtrudel/bandit/security/adviso… | vendor-advisoryrelated |
| https://cna.erlef.org/cves/CVE-2026-111101.html | related |
| https://osv.dev/vulnerability/EEF-CVE-2026-111101 | related |
| https://github.com/mtrudel/bandit/commit/7201270c… | related |
| https://github.com/mtrudel/bandit/commit/220b9dfd… | patch |
Impacted products
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CVE-2026-111073 (GCVE-0-2026-111073)
Vulnerability from cvelistv5 – Published: 2026-10-28 16:37 – Updated: 2026-11-05 19:15
VLAI
EPSS
VEX
Title
Apache Kafka: PushTelemetry (KIP-714) metrics payloads are decompressed without a size limit, allowing a broker out-of-memory denial of service
Summary
The broker-side PushTelemetry API (KIP-714) validates only the compressed size of a client's metrics payload against telemetry.max.bytes (default 1 MB) before decompressing it. ClientTelemetryUtils.decompress() then decompresses the payload with no limit on the decompressed output size, growing a heap buffer until the compressed input is exhausted. A small, highly compressible payload (for example gzip-compressed zeros) can therefore expand to hundreds of megabytes of broker heap.
Impact:
An authenticated client can send a PushTelemetry request with a small compressed payload that decompresses to a very large size, consuming broker heap out of proportion to the request size. Repeated or concurrent requests can exhaust the broker heap and cause an OutOfMemoryError, degrading or crashing the broker; a client that targets multiple brokers can affect cluster availability. PushTelemetry is available to any authenticated client and is not gated by an ACL.
Mitigation:
Upgrade to Apache Kafka 4.2.2, 4.3.1, or 4.4.0. On affected versions there is no configuration that fully prevents the amplification, because telemetry.max.bytes bounds only the compressed size; lowering telemetry.max.bytes reduces the worst-case decompressed size proportionally and is a partial mitigation.
Resolution:
- From Apache Kafka 4.2.2, 4.3.1, and 4.4.0: ClientTelemetryUtils.decompress() enforces a maximum decompressed size equal to telemetry.max.bytes (default 1 MB). Decompression reads in bounded chunks and aborts with a TelemetryTooLargeException once the decompressed total exceeds the limit, so an over-large or highly compressible payload is rejected instead of being fully expanded in heap. The decompressed size is therefore bounded by default.
Severity
6.5 (Medium)
SSVC
Exploitation: none
Automatable: no
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-11-05 19:15 UTC
CWE
Assigner
apache
CNA
References
2 references
| URL | Tags |
|---|---|
| https://kafka.apache.org/cve-list | vendor-advisory |
| http://www.openwall.com/lists/oss-security/2026/1… |
Impacted products
1 product
| Vendor | Product | Version | |
|---|---|---|---|
| Apache Software Foundation | Apache Kafka |
Affected:
3.7.0 , ≤ 4.1.2
(semver)
Affected: 4.2.0 , ≤ 4.2.1 (semver) Affected: 4.3.0 (semver) |
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CVE-2026-111066 (GCVE-0-2026-111066)
Vulnerability from cvelistv5 – Published: 2026-10-19 16:59 – Updated: 2026-10-20 16:10
VLAI
EPSS
VEX
Title
AIOHTTP: File descriptor exhaustion in multipart requests
Summary
AIOHTTP is an asynchronous HTTP client/server framework for asyncio and Python. From 2.0.0 until 3.14.4, multipart request processing can retain an unbounded number of open file descriptors. An unauthenticated attacker can consequently exhaust file descriptors with specially crafted multipart requests when a handler uses Request.post(). This issue is fixed in version 3.14.4.
Severity
SSVC
Exploitation: none
Automatable: no
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-10-20 15:10 UTC
CWE
Assigner
GitHub_M
CNA
References
3 references
| URL | Tags |
|---|---|
| https://github.com/aio-libs/aiohttp/security/advi… | x_refsource_CONFIRM |
| https://github.com/aio-libs/aiohttp/commit/2d9463… | x_refsource_MISC |
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CVE-2026-111065 (GCVE-0-2026-111065)
Vulnerability from cvelistv5 – Published: 2026-10-19 16:57 – Updated: 2026-10-19 17:35
VLAI
EPSS
VEX
Title
AIOHTTP: Connector pool exhaustion via Max-Age overflow
Summary
AIOHTTP is an asynchronous HTTP client/server framework for asyncio and Python. Prior to 3.14.4, Max-Age processing can overflow and skip closing a connection. An attacker can consequently exhaust the connection pool temporarily until garbage collection resolves the connections. This issue is fixed in version 3.14.4.
Severity
SSVC
Exploitation: none
Automatable: yes
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-10-19 17:34 UTC
CWE
- CWE-770 - Allocation of Resources Without Limits or Throttling
Assigner
GitHub_M
CNA
References
3 references
| URL | Tags |
|---|---|
| https://github.com/aio-libs/aiohttp/security/advi… | x_refsource_CONFIRM |
| https://github.com/aio-libs/aiohttp/commit/9dd8ea… | x_refsource_MISC |
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CVE-2026-111064 (GCVE-0-2026-111064)
Vulnerability from cvelistv5 – Published: 2026-10-19 16:47 – Updated: 2026-10-28 15:29
VLAI
EPSS
VEX
Title
aiohttp server lacks an initial request/header timeout
Summary
AIOHTTP is an asynchronous HTTP client/server framework for asyncio and Python. Prior to 3.14.4, keepalive timeout handling is absent during the initial portion of a request. An attacker can keep an idle connection open indefinitely before sending any request data, consuming server connection capacity. This issue is fixed in version 3.14.4.
Severity
SSVC
Exploitation: none
Automatable: yes
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-10-28 15:29 UTC
CWE
- CWE-770 - Allocation of Resources Without Limits or Throttling
Assigner
GitHub_M
CNA
References
3 references
| URL | Tags |
|---|---|
| https://github.com/aio-libs/aiohttp/security/advi… | x_refsource_CONFIRM |
| https://github.com/aio-libs/aiohttp/commit/be8468… | x_refsource_MISC |
| https://github.com/aio-libs/aiohttp/releases/tag/… | x_refsource_MISC |
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CVE-2026-111061 (GCVE-0-2026-111061)
Vulnerability from cvelistv5 – Published: 2026-10-19 16:30 – Updated: 2026-10-19 18:29
VLAI
EPSS
VEX
Title
russh agent server converts constraint records into unbounded never-rolled-back tasks
Summary
russh is a Rust SSH client and server library that includes an SSH agent protocol implementation. Prior to 0.64.1, the agent server spawns a separate long-lived task for every SSH_AGENT_CONSTRAIN_LIFETIME record in a constrained add-key request. The loop accepts repeated lifetime records, clones the key blob into each task, and does not roll back tasks when later constraint parsing fails. An attacker that can speak the agent protocol locally or through agent forwarding can exhaust memory and tasks until the agent process is starved or terminated, denying SSH agent service. This issue is fixed in version 0.64.1.
Severity
4.3 (Medium)
SSVC
Exploitation: poc
Automatable: no
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-10-19 18:29 UTC
CWE
- CWE-770 - Allocation of Resources Without Limits or Throttling
Assigner
GitHub_M
CNA
References
3 references
| URL | Tags |
|---|---|
| https://github.com/Eugeny/russh/security/advisori… | x_refsource_CONFIRM |
| https://github.com/Eugeny/russh/commit/4c305033d7… | x_refsource_MISC |
| https://github.com/Eugeny/russh/releases/tag/v0.64.1 | x_refsource_MISC |
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CVE-2026-110944 (GCVE-0-2026-110944)
Vulnerability from cvelistv5 – Published: 2026-11-04 07:04 – Updated: 2026-11-09 21:21
VLAI
EPSS
VEX
Title
Resource exhaustion vulnerability in HTTP request handling impacts Qt HTTP Server (QHttpServer)
Summary
Resource exhaustion vulnerability in the HTTP request handling of the QHttpServer component of Qt HTTP Server.
Severity
SSVC
Exploitation: none
Automatable: yes
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-11-09 21:21 UTC
CWE
- CWE-770 - Allocation of Resources Without Limits or Throttling
Assigner
Qt
CNA
References
3 references
| URL | Tags |
|---|---|
| https://wiki.qt.io/List_of_known_vulnerabilities_… | vendor-advisory |
| https://codereview.qt-project.org/c/qt/qthttpserv… | patch |
| https://codereview.qt-project.org/c/qt/qthttpserv… | patch |
Impacted products
1 product
| Vendor | Product | Version | |
|---|---|---|---|
| qt | Qt Framework |
Affected:
6.4.0 , < 6.11.3
(python)
Affected: 6.12.0 , < 6.12.1 (python) cpe:2.3:a:qt:qt:*:*:*:*:*:*:*:* cpe:2.3:a:qt:qthttpserver:*:*:*:*:*:*:*:* |
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CVE-2026-110927 (GCVE-0-2026-110927)
Vulnerability from cvelistv5 – Published: 2026-10-15 13:07 – Updated: 2026-10-21 06:48
VLAI
EPSS
VEX
CVE-2026-110927 has been marked as a duplicate of CVE-2026-106585.
Show details on NVD website{
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Mitigation
Requirements
Clearly specify the minimum and maximum expectations for capabilities, and dictate which behaviors are acceptable when resource allocation reaches limits.
Mitigation
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.
Mitigation
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.
Mitigation MIT-5
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.
Mitigation MIT-15
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.
Mitigation
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.
Mitigation
Architecture and Design
Ensure that protocols have specific limits of scale placed on them.
Mitigation MIT-38.1
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.
Mitigation MIT-47
Operation
Architecture and Design
Strategy: 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).
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.