Common Weakness Enumeration

CWE-770

Allowed

Allocation 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.

3023 vulnerabilities reference this CWE, most recent first.

CVE-2026-14330 (GCVE-0-2026-14330)

Vulnerability from cvelistv5 – Published: 2026-07-01 14:09 – Updated: 2026-07-01 15:37
VLAI
Title
Pipewire: pulse server alloca stack overflow
Summary
Multiple unbounded alloca() calls in the PulseAudio protocol server.
SSVC
Exploitation: none Automatable: no Technical Impact: partial
CISA Coordinator (v2.0.3)
CWE
  • CWE-770 - Allocation of Resources Without Limits or Throttling
Assigner
References
URL Tags
https://access.redhat.com/security/cve/CVE-2026-14330 vdb-entryx_refsource_REDHAT
https://bugzilla.redhat.com/show_bug.cgi?id=2495907 issue-trackingx_refsource_REDHAT
Impacted products
Vendor Product Version
Red Hat Red Hat Enterprise Linux 10     cpe:/o:redhat:enterprise_linux:10
Create a notification for this product.
Red Hat Red Hat Enterprise Linux 8     cpe:/o:redhat:enterprise_linux:8
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Red Hat Red Hat Enterprise Linux 9     cpe:/o:redhat:enterprise_linux:9
Create a notification for this product.
Date Public
2026-07-01 00:00
Credits
Red Hat would like to thank Tristan for reporting this issue.
Show details on NVD website

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CVE-2026-13698 (GCVE-0-2026-13698)

Vulnerability from cvelistv5 – Published: 2026-07-06 14:13 – Updated: 2026-07-06 15:28
VLAI
Summary
A memory leak in OpenVPN version 2.5.0 through 2.5.11, 2.6.0 through 2.6.20 and 2.7_alpha1 through 2.7.4 allows remote attackers with a valid tls-crypt-v2 client key to potentially cause a denial of service
SSVC
Exploitation: none Automatable: no Technical Impact: partial
CISA Coordinator (v2.0.3)
CWE
  • CWE-401 - Missing release of memory after effective lifetime
  • CWE-770 - Allocation of resources without limits or throttling
Assigner
References
Impacted products
Vendor Product Version
OpenVPN OpenVPN Affected: 2.5.0 , ≤ 2.5.11 (semver)
Affected: 2.6.0 , ≤ 2.6.20 (semver)
Affected: 2.7_alpha1 , ≤ 2.7.4 (semver)
Create a notification for this product.
Show details on NVD website

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CVE-2026-13585 (GCVE-0-2026-13585)

Vulnerability from cvelistv5 – Published: 2026-07-15 02:01 – Updated: 2026-07-15 13:11
VLAI
Summary
Allocation of Resources Without Limits and Throttling and Sensitive Information in Resource Not Removed Before Reuse in the ASUS System Control Interface driver and ASUS Business Manager allow a local administrator to disclose sensitive information via crafted IOCTL requests, which, in severe cases, may lead to a Denial of Service (DoS) on the system. Refer to the '  Security Update for ASUS System Control Interface  ' section on the ASUS Security Advisory for more information.
SSVC
Exploitation: none Automatable: no Technical Impact: partial
CISA Coordinator (v2.0.3)
CWE
  • CWE-770 - Allocation of Resources Without Limits or Throttling
  • CWE-226 - Sensitive Information in Resource Not Removed Before Reuse
Assigner
References
Impacted products
Credits
Rehman Ahmadzai
Show details on NVD website

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CVE-2026-13322 (GCVE-0-2026-13322)

Vulnerability from cvelistv5 – Published: 2026-06-26 00:04 – Updated: 2026-06-26 13:39
VLAI
Title
Kubevirt: virt-handler-rhel9: kubevirt: unbounded virtio-serial readline in virt-handler causes oom denial of service
Summary
A flaw was found in KubeVirt's downward metrics virtio-serial server. The server reads guest requests using textproto.Reader.ReadLine(), which buffers input indefinitely until a newline character is received, with no length limit or read deadline. A user with access to a VM guest that has the downward metrics virtio-serial device configured can write a continuous byte stream to the device, causing unbounded memory allocation in the virt-handler process until it is OOM-killed.
SSVC
Exploitation: none Automatable: no Technical Impact: partial
CISA Coordinator (v2.0.3)
CWE
  • CWE-770 - Allocation of Resources Without Limits or Throttling
Assigner
References
URL Tags
https://access.redhat.com/security/cve/CVE-2026-13322 vdb-entryx_refsource_REDHAT
https://bugzilla.redhat.com/show_bug.cgi?id=2492681 issue-trackingx_refsource_REDHAT
Impacted products
Vendor Product Version
Red Hat Red Hat OpenShift Virtualization 4     cpe:/a:redhat:container_native_virtualization:4
Create a notification for this product.
Date Public
2026-06-25 00:00
Credits
This issue was discovered by Huzaifa Sidhpurwala (Red Hat).
Show details on NVD website

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CVE-2026-12818 (GCVE-0-2026-12818)

Vulnerability from cvelistv5 – Published: 2026-06-30 06:24 – Updated: 2026-06-30 12:55
VLAI
Title
DVP-12SE Exposure of Sensitive Information Vulnerability
Summary
Delta Electronics DVP12SE PLCs are susceptible to a resource allocation vulnerability without limits or throttling (CWE-770) within their Modbus TCP service.
SSVC
Exploitation: none Automatable: yes Technical Impact: total
CISA Coordinator (v2.0.3)
CWE
  • CWE-770 - Allocation of resources without limits or throttling
Assigner
Impacted products
Date Public
2026-06-30 05:29
Credits
CISA Adm Bin Harbi (0xnoag) - Corvo Security
Show details on NVD website

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CVE-2026-12760 (GCVE-0-2026-12760)

Vulnerability from cvelistv5 – Published: 2026-06-24 18:10 – Updated: 2026-06-24 18:53
VLAI
Title
Denial-of-Service Vulnerability via Malformed IPv4 Fragmentation Handling in TP-Link Tapo C200
Summary
A denial-of-service (DoS) vulnerability has been identified in Tapo C200 v3 in the network packet handling logic due to improper handling of IPv4 fragmented packets.  An unauthenticated adjacent attacker can send crafted packets to cause excessive resource consumption, leading to instability of the device.Successful exploitation can remotely trigger a temporary denial-of-service condition, causing the camera to become unresponsive and resulting in intermittent loss of video monitoring and recording.
SSVC
Exploitation: none Automatable: no Technical Impact: partial
CISA Coordinator (v2.0.3)
CWE
  • CWE-770 - Allocation of resources without limits or throttling
Assigner
Impacted products
Vendor Product Version
TP-Link Systems Inc. Tapo C200 v3 Affected: 0 , < 1.4.4 Build 250922 (custom)
Create a notification for this product.
Credits
Arjan Chadha, Keysight Technologies
Show details on NVD website

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CVE-2026-12707 (GCVE-0-2026-12707)

Vulnerability from cvelistv5 – Published: 2026-07-14 15:18 – Updated: 2026-07-14 15:57
VLAI
Title
Unbounded path event queue growth in quiche via peer-driven source connection ID rotation
Summary
Summary Cloudflare quiche was discovered to be vulnerable to memory resource exhaustion due to unbounded queuing of post-handshake client migration events. Impact quiche supports the connection migration features described in Section 9 of RFC 9000, which allows a single QUIC connection to survive changes in the network path. Although quiche implements the protections described in Section 9.3 of RFC 9000 to limit server state commitment, it was discovered that the collection of PathEvents, intended to be consumed by applications via the path_event_next() function, was not bounded. Once the QUIC handshake completed, a peer could exploit rapid source address migration in order to cause unbounded queuing of the PathEvent::ReusedSourceConnectionId type. Servers are vulnerable even if active connection migration is disabled. Mitigation: * Applications can call path_event_next() to drain the PathEvent collection, mitigating the attack. * Users are requested to upgrade to quiche 0.29.3 which is the earliest version that prevents excessive queueing of PathEvent::ReusedSourceConnectionId.
SSVC
Exploitation: none Automatable: yes Technical Impact: partial
CISA Coordinator (v2.0.3)
CWE
  • CWE-770 - Allocation of resources without limits or throttling
Assigner
Impacted products
Vendor Product Version
Cloudflare quiche Affected: 0.15.0 , < 0.29.3 (semver)
Create a notification for this product.
Show details on NVD website

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CVE-2026-12590 (GCVE-0-2026-12590)

Vulnerability from cvelistv5 – Published: 2026-07-09 10:21 – Updated: 2026-07-09 12:06
VLAI
Title
body-parser vulnerable to denial of service when invalid limit value silently disables size enforcement
Summary
Impact: In body-parser versions prior to 1.20.6 (1.x line) and 2.3.0 (2.x line), when the parser is configured with an invalid limit option value such as an unparseable string or NaN, bytes.parse returns null and the request body size check is silently skipped. Applications that rely on limit as their primary safeguard against oversized request bodies will accept arbitrarily large payloads, leading to excessive memory and CPU usage and denial of service. Patches: This issue is fixed in body-parser 1.20.6 and 2.3.0. After the fix, invalid limit values throw a clear error at parser construction time instead of silently disabling enforcement, while null and undefined continue to fall back to the default limit of 100kb. Workarounds: Validate the limit value before passing it to body-parser. For example, parse the value at startup and reject any configuration where the result is null or a non-finite number.
SSVC
Exploitation: none Automatable: no Technical Impact: partial
CISA Coordinator (v2.0.3)
CWE
  • CWE-770 - Allocation of Resources Without Limits or Throttling
Assigner
Impacted products
Vendor Product Version
body-parser body-parser Affected: 0 , < 1.20.6 (semver)
Unaffected: 1.20.6 (semver)
Affected: 2.0.0 , < 2.3.0 (semver)
Unaffected: 2.3.0 (semver)
Create a notification for this product.
Credits
Phillip9587 UlisesGascon bjohansebas
Show details on NVD website

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CVE-2026-12151 (GCVE-0-2026-12151)

Vulnerability from cvelistv5 – Published: 2026-06-17 16:05 – Updated: 2026-07-15 11:49
VLAI
Title
undici WebSocket client vulnerable to denial of service via fragment count bypass
Summary
Impact: The undici WebSocket client enforces maxPayloadSize on the cumulative byte count of fragments in a message but does not enforce a limit on the number of fragments. A malicious WebSocket server can stream many small or empty continuation frames that each pass per-frame and cumulative-size validation, collectively causing unbounded memory growth in the client process. The result is memory exhaustion and a denial of service. Affected applications are those using the undici WebSocket client (new WebSocket(...)) or the WebSocketStream API that can be induced to connect to an attacker-controlled or compromised WebSocket endpoint. All releases starting at undici 6.17.0 are affected. Patches: Upgrade to undici >= 6.26.0, >= 7.28.0, or >= 8.5.0. Workarounds: No workaround is available. The fix must be applied through an upgrade.
SSVC
Exploitation: none Automatable: yes Technical Impact: partial
CISA Coordinator (v2.0.3)
CWE
  • CWE-400 - Uncontrolled Resource Consumption
  • CWE-770 - Allocation of Resources Without Limits or Throttling
Assigner
Impacted products
Vendor Product Version
undici undici Affected: 0 , < 6.26.0 (semver)
Unaffected: 6.26.0 (semver)
Affected: 7.0.0 , < 7.28.0 (semver)
Unaffected: 7.28.0 (semver)
Affected: 8.0.0 , < 8.5.0 (semver)
Unaffected: 8.5.0 (semver)
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Red Hat Red Hat Enterprise Linux 10 Unaffected: 1:24.18.0-1.el10_2 , < * (rpm)
    cpe:/o:redhat:enterprise_linux:10.2
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Red Hat Red Hat Enterprise Linux 10 Unaffected: 1:22.23.1-2.el10_2 , < * (rpm)
    cpe:/o:redhat:enterprise_linux:10.2
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Red Hat Red Hat Enterprise Linux 10.0 Extended Update Support Unaffected: 1:22.23.1-2.el10_0 , < * (rpm)
    cpe:/o:redhat:enterprise_linux_eus:10.0
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Red Hat Red Hat Enterprise Linux 9 Unaffected: 9080020260626074955.rhel9 , < * (rpm)
    cpe:/a:redhat:enterprise_linux:9
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Red Hat Red Hat Enterprise Linux 9 Unaffected: 9080020260626075442.rhel9 , < * (rpm)
    cpe:/a:redhat:enterprise_linux:9
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Red Hat Cluster Observability Operator 1.5.0 Unaffected: 1782840519 , < * (rpm)
    cpe:/a:redhat:cluster_observability_operator:1.5::el9
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Red Hat Cluster Observability Operator 1.5.0 Unaffected: 1782839981 , < * (rpm)
    cpe:/a:redhat:cluster_observability_operator:1.5::el9
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Red Hat Cluster Observability Operator 1.5.0 Unaffected: 1782839193 , < * (rpm)
    cpe:/a:redhat:cluster_observability_operator:1.5::el9
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Red Hat Cluster Observability Operator 1.5.0 Unaffected: 1782838753 , < * (rpm)
    cpe:/a:redhat:cluster_observability_operator:1.5::el9
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Red Hat Cluster Observability Operator 1.5.0 Unaffected: 1782839279 , < * (rpm)
    cpe:/a:redhat:cluster_observability_operator:1.5::el9
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Red Hat Cluster Observability Operator 1.5.0 Unaffected: 1782840539 , < * (rpm)
    cpe:/a:redhat:cluster_observability_operator:1.5::el9
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Red Hat Cluster Observability Operator 1.5.0 Unaffected: 1782841925 , < * (rpm)
    cpe:/a:redhat:cluster_observability_operator:1.5::el9
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Red Hat Cluster Observability Operator 1.5.0 Unaffected: 1782844225 , < * (rpm)
    cpe:/a:redhat:cluster_observability_operator:1.5::el9
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Red Hat Cluster Observability Operator 1.5.0 Unaffected: 1782839658 , < * (rpm)
    cpe:/a:redhat:cluster_observability_operator:1.5::el9
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Red Hat Cluster Observability Operator 1.5.0 Unaffected: 1782838476 , < * (rpm)
    cpe:/a:redhat:cluster_observability_operator:1.5::el9
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Red Hat Cluster Observability Operator 1.5.0 Unaffected: 1782839996 , < * (rpm)
    cpe:/a:redhat:cluster_observability_operator:1.5::el9
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Red Hat Cluster Observability Operator 1.5.0 Unaffected: 1782839494 , < * (rpm)
    cpe:/a:redhat:cluster_observability_operator:1.5::el9
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Red Hat Red Hat Developer Hub 1.10 Unaffected: 1783448184 , < * (rpm)
    cpe:/a:redhat:rhdh:1.10::el9
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Red Hat Red Hat Hardened Images Unaffected: 26.5.0-1.3.hum1 , < * (rpm)
    cpe:/a:redhat:hummingbird:1
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Red Hat Red Hat Hardened Images Unaffected: 24.18.0-0.3.hum1 , < * (rpm)
    cpe:/a:redhat:hummingbird:1
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Red Hat Red Hat OpenShift Dev Spaces 3.29 Unaffected: 1782498792 , < * (rpm)
    cpe:/a:redhat:openshift_devspaces:3.29::el9
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Red Hat Red Hat OpenShift Dev Spaces 3.29 Unaffected: 1783007534 , < * (rpm)
    cpe:/a:redhat:openshift_devspaces:3.29::el9
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Red Hat Red Hat OpenShift Dev Spaces 3.29 Unaffected: 1782989367 , < * (rpm)
    cpe:/a:redhat:openshift_devspaces:3.29::el9
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Red Hat Cryostat 4     cpe:/a:redhat:cryostat:4
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Red Hat OpenShift Pipelines     cpe:/a:redhat:openshift_pipelines:1
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Red Hat Red Hat AMQ Broker 7     cpe:/a:redhat:amq_broker:7
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Red Hat Red Hat Build of Podman Desktop     cpe:/a:redhat:podman_desktop:1
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Red Hat Red Hat Enterprise Linux 8     cpe:/o:redhat:enterprise_linux:8
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Red Hat Red Hat Hardened Images     cpe:/a:redhat:hummingbird:1
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Red Hat Red Hat OpenShift AI (RHOAI)     cpe:/a:redhat:openshift_ai
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Red Hat Red Hat OpenShift Container Platform 4     cpe:/a:redhat:openshift:4
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Red Hat Red Hat Openshift Data Foundation 4     cpe:/a:redhat:openshift_data_foundation:4
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Red Hat Red Hat OpenShift Dev Spaces     cpe:/a:redhat:openshift_devspaces:3
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Red Hat Self-service automation portal 2     cpe:/a:redhat:ansible_portal:2
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Credits
lpinca Nadav0077 UlisesGascon
Show details on NVD website

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CVE-2026-11972 (GCVE-0-2026-11972)

Vulnerability from cvelistv5 – Published: 2026-06-23 22:02 – Updated: 2026-06-30 15:13
VLAI
Title
tarfile opened in streaming mode mishandles EOF
Summary
When using the "tarfile" module with a file opened in "streaming mode" (mode="r|") the tarfile module did not properly handle EOF, making archive parsing take exponentially longer.
SSVC
Exploitation: none Automatable: no Technical Impact: partial
CISA Coordinator (v2.0.3)
Assigner
PSF
Impacted products
Vendor Product Version
Python Software Foundation CPython Affected: 0 , < 3.15.0 (python)
Create a notification for this product.
Credits
Ryan Hileman (https://github.com/lunixbochs) Petr Viktorin (https://github.com/encukou) Stan Ulbrych (https://github.com/StanFromIreland)
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.