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.
3025 vulnerabilities reference this CWE, most recent first.
CVE-2026-34062 (GCVE-0-2026-34062)
Vulnerability from cvelistv5 – Published: 2026-04-22 19:23 – Updated: 2026-04-23 12:57
VLAI
EPSS
VEX
Title
Nimiq has Allocation of Resources Without Limits or Throttling in its libp2p request/response
Summary
nimiq-libp2p is a Nimiq network implementation based on libp2p. Prior to version 1.3.0, `MessageCodec::read_request` and `read_response` call `read_to_end()` on inbound substreams, so a remote peer can send only a partial frame and keep the substream open. because `Behaviour::new` also sets `with_max_concurrent_streams(1000)`, the node exposes a much larger stalled-slot budget than the library default. The patch for this vulnerability is formally released as part of v1.3.0. No known workarounds are available.
Severity
5.3 (Medium)
SSVC
Exploitation: none
Automatable: yes
Technical Impact: partial
CISA Coordinator (v2.0.3)
CWE
- CWE-770 - Allocation of Resources Without Limits or Throttling
Assigner
References
3 references
| URL | Tags |
|---|---|
| https://github.com/nimiq/core-rs-albatross/securi… | x_refsource_CONFIRM |
| https://github.com/nimiq/core-rs-albatross/commit… | x_refsource_MISC |
| https://github.com/nimiq/core-rs-albatross/releas… | x_refsource_MISC |
Impacted products
1 product
| Vendor | Product | Version | |
|---|---|---|---|
| nimiq | network-libp2p |
Affected:
< 1.3.0
|
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CVE-2026-34052 (GCVE-0-2026-34052)
Vulnerability from cvelistv5 – Published: 2026-04-03 22:04 – Updated: 2026-04-06 18:59
VLAI
EPSS
VEX
Title
LTI JupyterHub Authenticator: Unbounded Memory Growth via Nonce Storage (Denial of Service)
Summary
LTI JupyterHub Authenticator is a JupyterHub authenticator for LTI. Prior to version 1.6.3, the LTI 1.1 validator stores OAuth nonces in a class-level dictionary that grows without bounds. Nonces are added before signature validation, so an attacker with knowledge of a valid consumer key can send repeated requests with unique nonces to gradually exhaust server memory, causing a denial of service. This issue has been patched in version 1.6.3.
Severity
5.9 (Medium)
SSVC
Exploitation: none
Automatable: no
Technical Impact: partial
CISA Coordinator (v2.0.3)
CWE
Assigner
References
2 references
| URL | Tags |
|---|---|
| https://github.com/jupyterhub/ltiauthenticator/se… | x_refsource_CONFIRM |
| https://github.com/jupyterhub/ltiauthenticator/re… | x_refsource_MISC |
Impacted products
1 product
| Vendor | Product | Version | |
|---|---|---|---|
| jupyterhub | ltiauthenticator |
Affected:
< 1.6.3
|
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CVE-2026-33871 (GCVE-0-2026-33871)
Vulnerability from cvelistv5 – Published: 2026-03-27 19:55 – Updated: 2026-07-15 01:05
VLAI
EPSS
VEX
Title
Netty HTTP/2 CONTINUATION Frame Flood DoS via Zero-Byte Frame Bypass
Summary
Netty is an asynchronous, event-driven network application framework. In versions prior to 4.1.132.Final and 4.2.10.Final, a remote user can trigger a Denial of Service (DoS) against a Netty HTTP/2 server by sending a flood of `CONTINUATION` frames. The server's lack of a limit on the number of `CONTINUATION` frames, combined with a bypass of existing size-based mitigations using zero-byte frames, allows an user to cause excessive CPU consumption with minimal bandwidth, rendering the server unresponsive. Versions 4.1.132.Final and 4.2.10.Final fix the issue.
Severity
SSVC
Exploitation: none
Automatable: yes
Technical Impact: partial
CISA Coordinator (v2.0.3)
CWE
- CWE-770 - Allocation of Resources Without Limits or Throttling
Assigner
References
20 references
Impacted products
43 products
| Vendor | Product | Version | |
|---|---|---|---|
| netty | netty |
Affected:
< 4.1.132.Final
Affected: >= 4.2.0.Alpha1, < 4.2.10.Final |
|
| Red Hat | Cryostat 4 on RHEL 9 |
Unaffected:
4.2.0-9 , < *
(rpm)
cpe:/a:redhat:cryostat:4::el9 |
|
| Red Hat | Red Hat AMQ Broker 7.12.7 |
Unaffected:
codec-http2 , < *
(rpm)
cpe:/a:redhat:amq_broker:7.12 |
|
| Red Hat | Red Hat AMQ Broker 7.13.5 |
Unaffected:
codec-http2 , < *
(rpm)
cpe:/a:redhat:amq_broker:7.13 |
|
| Red Hat | Red Hat AMQ Broker 7.14.0 |
Unaffected:
codec-http , < *
(rpm)
Unaffected: codec-http2 , < * (rpm) cpe:/a:redhat:amq_broker:7.14 |
|
| Red Hat | Red Hat Build of Apache Camel 4.14 for Quarkus 3.27 |
Unaffected:
codec-http2 , < *
(rpm)
cpe:/a:redhat:apache_camel_quarkus:3.27 |
|
| Red Hat | Red Hat build of Apache Camel 4.18.1 for Spring Boot 3.5.14 |
Unaffected:
codec-http , < *
(rpm)
Unaffected: codec-http2 , < * (rpm) cpe:/a:redhat:apache_camel_spring_boot:4.18 |
|
| Red Hat | Red Hat build of Quarkus 3.20.6 |
Unaffected:
codec-http2 , < *
(rpm)
cpe:/a:redhat:quarkus:3.20::el8 |
|
| Red Hat | Red Hat build of Quarkus 3.27.3 |
Unaffected:
codec-http2 , < *
(rpm)
cpe:/a:redhat:quarkus:3.27::el8 |
|
| Red Hat | Red Hat Data Grid 8.6.1 |
Unaffected:
codec-http , < *
(rpm)
Unaffected: codec-http2 , < * (rpm) cpe:/a:redhat:jboss_data_grid:8 |
|
| Red Hat | Red Hat JBoss Enterprise Application Platform 8.1 |
Unaffected:
codec-http , < *
(rpm)
cpe:/a:redhat:jboss_enterprise_application_platform:8.1::el9 |
|
| Red Hat | Red Hat JBoss Enterprise Application Platform 8.1 |
Unaffected:
http-4.1.100.Final.jar , < *
(rpm)
cpe:/a:redhat:jboss_enterprise_application_platform:8.1::el9 |
|
| Red Hat | Red Hat JBoss Enterprise Application Platform 8.1 for RHEL 8 |
Unaffected:
0:4.1.132-1.Final_redhat_00001.1.el8eap , < *
(rpm)
cpe:/a:redhat:jboss_enterprise_application_platform:8.1::el8 |
|
| Red Hat | Red Hat JBoss Enterprise Application Platform 8.1 for RHEL 9 |
Unaffected:
0:4.1.132-1.Final_redhat_00001.1.el9eap , < *
(rpm)
cpe:/a:redhat:jboss_enterprise_application_platform:8.1::el9 |
|
| Red Hat | Streams for Apache Kafka 2.9.4 |
Unaffected:
codec-http , < *
(rpm)
Unaffected: codec-http2 , < * (rpm) cpe:/a:redhat:amq_streams:2.9::el9 |
|
| Red Hat | Streams for Apache Kafka 3.2.0 |
cpe:/a:redhat:amq_streams:3.2::el9 |
|
| Red Hat | Red Hat OpenShift AI 2.25 |
Unaffected:
1776756834 , < *
(rpm)
cpe:/a:redhat:openshift_ai:2.25::el9 |
|
| Red Hat | Red Hat OpenShift Dev Spaces 3.27 |
Unaffected:
1776716842 , < *
(rpm)
cpe:/a:redhat:openshift_devspaces:3.27::el9 |
|
| Red Hat | Red Hat OpenShift Dev Spaces 3.27 |
Unaffected:
1776717247 , < *
(rpm)
cpe:/a:redhat:openshift_devspaces:3.27::el9 |
|
| Red Hat | Red Hat OpenShift Dev Spaces 3.27 |
Unaffected:
1776796445 , < *
(rpm)
cpe:/a:redhat:openshift_devspaces:3.27::el9 |
|
| Red Hat | Cryostat 4 |
cpe:/a:redhat:cryostat:4 |
|
| Red Hat | Logging Subsystem for Red Hat OpenShift |
cpe:/a:redhat:logging:5 |
|
| Red Hat | OpenShift Serverless |
cpe:/a:redhat:serverless:1 |
|
| Red Hat | Red Hat AMQ Clients |
cpe:/a:redhat:amq_clients:2023 |
|
| Red Hat | Red Hat build of Apache Camel 4 for Quarkus 3 |
cpe:/a:redhat:camel_quarkus:3 |
|
| Red Hat | Red Hat build of Apache Camel - HawtIO 4 |
cpe:/a:redhat:apache_camel_hawtio:4 |
|
| Red Hat | Red Hat build of Apicurio Registry 2 |
cpe:/a:redhat:service_registry:2 |
|
| Red Hat | Red Hat build of Apicurio Registry 3 |
cpe:/a:redhat:apicurio_registry:3 |
|
| Red Hat | Red Hat build of Debezium 2 |
cpe:/a:redhat:debezium:2 |
|
| Red Hat | Red Hat build of Debezium 3 |
cpe:/a:redhat:debezium:3 |
|
| Red Hat | Red Hat Build of Keycloak |
cpe:/a:redhat:build_keycloak: |
|
| Red Hat | Red Hat build of OptaPlanner 8 |
cpe:/a:redhat:optaplanner:::el6 |
|
| Red Hat | Red Hat build of Quarkus |
cpe:/a:redhat:quarkus:3 |
|
| Red Hat | Red Hat Enterprise Linux AI (RHEL AI) 3 |
cpe:/a:redhat:enterprise_linux_ai:3 |
|
| Red Hat | Red Hat Fuse 7 |
cpe:/a:redhat:jboss_fuse:7 |
|
| Red Hat | Red Hat JBoss Enterprise Application Platform 7 |
cpe:/a:redhat:jboss_enterprise_application_platform:7 |
|
| Red Hat | Red Hat JBoss Enterprise Application Platform 8 |
cpe:/a:redhat:jboss_enterprise_application_platform:8 |
|
| Red Hat | Red Hat JBoss Enterprise Application Platform Expansion Pack |
cpe:/a:redhat:jbosseapxp |
|
| Red Hat | Red Hat OpenShift AI (RHOAI) |
cpe:/a:redhat:openshift_ai |
|
| Red Hat | Red Hat Process Automation 7 |
cpe:/a:redhat:jboss_enterprise_bpms_platform:7 |
|
| Red Hat | Red Hat Satellite 6 |
cpe:/a:redhat:satellite:6 |
|
| Red Hat | Red Hat Single Sign-On 7 |
cpe:/a:redhat:red_hat_single_sign_on:7 |
|
| Red Hat | streams for Apache Kafka 3 |
cpe:/a:redhat:amq_streams:3 |
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"timestamp": "2026-03-31T18:51:31.168118Z",
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"product": "Cryostat 4 on RHEL 9",
"vendor": "Red Hat",
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"vendor": "Red Hat",
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"cpes": [
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"packageName": "cryostat/jfr-datasource-rhel9",
"product": "Cryostat 4 on RHEL 9",
"vendor": "Red Hat",
"versions": [
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"status": "unaffected",
"version": "4.2.0-9",
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"cpes": [
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"vendor": "Red Hat",
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"version": "codec-http2",
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},
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"cpes": [
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],
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"packageName": "netty",
"product": "Red Hat AMQ Broker 7.14.0",
"vendor": "Red Hat",
"versions": [
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"lessThan": "*",
"status": "unaffected",
"version": "codec-http",
"versionType": "rpm"
},
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"lessThan": "*",
"status": "unaffected",
"version": "codec-http2",
"versionType": "rpm"
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"cpes": [
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],
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"packageName": "netty",
"product": "Red Hat Build of Apache Camel 4.14 for Quarkus 3.27",
"vendor": "Red Hat",
"versions": [
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"lessThan": "*",
"status": "unaffected",
"version": "codec-http2",
"versionType": "rpm"
}
]
},
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"cpes": [
"cpe:/a:redhat:apache_camel_spring_boot:4.18"
],
"defaultStatus": "affected",
"packageName": "netty",
"product": "Red Hat build of Apache Camel 4.18.1 for Spring Boot 3.5.14",
"vendor": "Red Hat",
"versions": [
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"lessThan": "*",
"status": "unaffected",
"version": "codec-http",
"versionType": "rpm"
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"lessThan": "*",
"status": "unaffected",
"version": "codec-http2",
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CVE-2026-33756 (GCVE-0-2026-33756)
Vulnerability from cvelistv5 – Published: 2026-04-08 17:07 – Updated: 2026-04-08 18:42
VLAI
EPSS
VEX
Title
Saleor Affected by Denial of Service via Unbounded GraphQL Query Batching
Summary
Saleor is an e-commerce platform. From 2.0.0 to before 3.23.0a3, 3.22.47, 3.21.54, and 3.20.118, Saleor supports query batching by submitting multiple GraphQL operations in a single HTTP request as a JSON array but wasn't enforcing any upper limit on the number of operations. This allowed an unauthenticated attacker to send a single HTTP request many operations (bypassing the per query complexity limit) to exhaust resources. This vulnerability is fixed in 3.23.0a3, 3.22.47, 3.21.54, and 3.20.118.
Severity
7.5 (High)
SSVC
Exploitation: none
Automatable: yes
Technical Impact: partial
CISA Coordinator (v2.0.3)
CWE
- CWE-770 - Allocation of Resources Without Limits or Throttling
Assigner
References
6 references
| URL | Tags |
|---|---|
| https://github.com/saleor/saleor/security/advisor… | x_refsource_CONFIRM |
| https://github.com/saleor/saleor/commit/7be352fa8… | x_refsource_MISC |
| https://github.com/saleor/saleor/commit/cdb66da97… | x_refsource_MISC |
| https://github.com/saleor/saleor/commit/d6a94e95b… | x_refsource_MISC |
| https://github.com/saleor/saleor/commit/e42aa4d6e… | x_refsource_MISC |
| https://github.com/saleor/saleor/commit/f0371bdd4… | x_refsource_MISC |
Impacted products
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CVE-2026-33743 (GCVE-0-2026-33743)
Vulnerability from cvelistv5 – Published: 2026-03-26 22:40 – Updated: 2026-03-27 13:53
VLAI
EPSS
VEX
Title
Incus vulnerable to denial of source through crafted bucket backup file
Summary
Incus is a system container and virtual machine manager. Prior to version 6.23.0, a specially crafted storage bucket backup can be used by an user with access to Incus' storage bucket feature to crash the Incus daemon. Repeated use of this attack can be used to keep the server offline causing a denial of service of the control plane API. This does not impact any running workload, existing containers and virtual machines will keep operating. Version 6.23.0 fixes the issue.
Severity
6.5 (Medium)
SSVC
Exploitation: poc
Automatable: no
Technical Impact: partial
CISA Coordinator (v2.0.3)
CWE
- CWE-770 - Allocation of Resources Without Limits or Throttling
Assigner
References
1 reference
| URL | Tags |
|---|---|
| https://github.com/lxc/incus/security/advisories/… | x_refsource_CONFIRM |
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CVE-2026-33658 (GCVE-0-2026-33658)
Vulnerability from cvelistv5 – Published: 2026-03-26 21:03 – Updated: 2026-03-30 11:42
VLAI
EPSS
VEX
Title
Rails Active Storage has a possible DoS vulnerability in proxy mode via multi-range requests
Summary
Active Storage allows users to attach cloud and local files in Rails applications. Prior to versions 8.1.2.1, 8.0.4.1, and 7.2.3.1
Active Storage's proxy controller does not limit the number of byte ranges in an HTTP Range header. A request with thousands of small ranges causes disproportionate CPU usage compared to a normal request for the same file, possibly resulting in a DoS vulnerability. Versions 8.1.2.1, 8.0.4.1, and 7.2.3.1 contain a patch.
Severity
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
5 references
| URL | Tags |
|---|---|
| https://github.com/rails/rails/security/advisorie… | x_refsource_CONFIRM |
| https://github.com/rails/rails/releases/tag/v7.2.3.1 | x_refsource_MISC |
| https://github.com/rails/rails/releases/tag/v8.0.4.1 | x_refsource_MISC |
| https://github.com/rails/rails/releases/tag/v8.1.2.1 | x_refsource_MISC |
| https://github.com/rubysec/ruby-advisory-db/blob/… | x_refsource_MISC |
Impacted products
1 product
| Vendor | Product | Version | |
|---|---|---|---|
| rails | activestorage |
Affected:
>= 8.1.0, < 8.1.2.1
Affected: >= 8.0.0, < 8.0.4.1 Affected: < 7.2.3.1 |
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CVE-2026-33621 (GCVE-0-2026-33621)
Vulnerability from cvelistv5 – Published: 2026-03-26 20:42 – Updated: 2026-03-27 13:55
VLAI
EPSS
VEX
Title
PinchTab: Unapplied Rate Limiting Middleware Allows Unbounded Brute-Force of API Token
Summary
PinchTab is a standalone HTTP server that gives AI agents direct control over a Chrome browser. PinchTab `v0.7.7` through `v0.8.4` contain incomplete request-throttling protections for auth-checkable endpoints. In `v0.7.7` through `v0.8.3`, a fully implemented `RateLimitMiddleware` existed in `internal/handlers/middleware.go` but was not inserted into the production HTTP handler chain, so requests were not subject to the intended per-IP throttle. In the same pre-`v0.8.4` range, the original limiter also keyed clients using `X-Forwarded-For`, which would have allowed client-controlled header spoofing if the middleware had been enabled. `v0.8.4` addressed those two issues by wiring the limiter into the live handler chain and switching the key to the immediate peer IP, but it still exempted `/health` and `/metrics` from rate limiting even though `/health` remained an auth-checkable endpoint when a token was configured. This issue weakens defense in depth for deployments where an attacker can reach the API, especially if a weak human-chosen token is used. It is not a direct authentication bypass or token disclosure issue by itself. PinchTab is documented as local-first by default and uses `127.0.0.1` plus a generated random token in the recommended setup. PinchTab's default deployment model is a local-first, user-controlled environment between the user and their agents; wider exposure is an intentional operator choice. This lowers practical risk in the default configuration, even though it does not by itself change the intrinsic base characteristics of the bug. This was fully addressed in `v0.8.5` by applying `RateLimitMiddleware` in the production handler chain, deriving the client address from the immediate peer IP instead of trusting forwarded headers by default, and removing the `/health` and `/metrics` exemption so auth-checkable endpoints are throttled as well.
Severity
4.8 (Medium)
SSVC
Exploitation: poc
Automatable: no
Technical Impact: partial
CISA Coordinator (v2.0.3)
CWE
Assigner
References
3 references
| URL | Tags |
|---|---|
| https://github.com/pinchtab/pinchtab/security/adv… | x_refsource_CONFIRM |
| https://github.com/pinchtab/pinchtab/commit/c619c… | x_refsource_MISC |
| https://github.com/pinchtab/pinchtab/releases/tag… | x_refsource_MISC |
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CVE-2026-33592 (GCVE-0-2026-33592)
Vulnerability from cvelistv5 – Published: 2026-07-02 07:12 – Updated: 2026-07-02 12:30
VLAI
EPSS
VEX
Title
FindServers Memory Exhaustion in open62541
Summary
An unauthenticated remote attacker can exhaust
server memory via the FindServers Discovery Service in open62541. The
serverUris field of FindServersRequest is not validated for length or array
size. An attacker can declare an arbitrarily large string (up to ~3.9 GB)
delivered across intermediate chunks without ever sending the final chunk. The
server buffers all chunks in RAM indefinitely until the SecureChannel times
out. The attack is pre-session and bypasses all encryption configuration. The issue affects open62541: from 1.4.0 through 1.4.16, from 1.5.0 through 1.5.4, master.
Severity
7.5 (High)
SSVC
Exploitation: none
Automatable: yes
Technical Impact: partial
CISA Coordinator (v2.0.3)
CWE
Assigner
References
3 references
Impacted products
1 product
| Vendor | Product | Version | |
|---|---|---|---|
| open62541 project / o6 Automation GmbH | open62541 |
Affected:
1.4.0 , ≤ 1.4.16
(semver)
Affected: 1.5.0 , ≤ 1.5.4 (semver) Affected: master (custom) |
Credits
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CVE-2026-33541 (GCVE-0-2026-33541)
Vulnerability from cvelistv5 – Published: 2026-03-26 20:27 – Updated: 2026-03-27 20:01
VLAI
EPSS
VEX
Title
TSPortal's Uncontrolled User Creation via Validation Side Effects Leads to Potential Denial of Service
Summary
TSPortal is the WikiTide Foundation’s in-house platform used by the Trust and Safety team to manage reports, investigations, appeals, and transparency work. Prior to version 34, a flaw in TSPortal allowed attackers to create arbitrary user records in the database by abusing validation logic. While validation correctly rejected invalid usernames, a side effect within a validation rule caused user records to be created regardless of whether the request succeeded. This could be exploited to cause uncontrolled database growth, leading to a potential denial of service (DoS). Version 34 contains a fix for the issue.
Severity
6.5 (Medium)
SSVC
Exploitation: none
Automatable: no
Technical Impact: partial
CISA Coordinator (v2.0.3)
CWE
Assigner
References
1 reference
| URL | Tags |
|---|---|
| https://github.com/miraheze/TSPortal/security/adv… | x_refsource_CONFIRM |
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CVE-2026-33483 (GCVE-0-2026-33483)
Vulnerability from cvelistv5 – Published: 2026-03-23 14:12 – Updated: 2026-03-24 17:42
VLAI
EPSS
VEX
Title
AVideo Affected by Unauthenticated Disk Space Exhaustion via Unlimited Temp File Creation in aVideoEncoderChunk.json.php
Summary
WWBN AVideo is an open source video platform. In versions up to and including 26.0, the `aVideoEncoderChunk.json.php` endpoint is a completely standalone PHP script with no authentication, no framework includes, and no resource limits. An unauthenticated remote attacker can send arbitrary POST data which is written to persistent temp files in `/tmp/` with no size cap, no rate limiting, and no cleanup mechanism. This allows trivial disk space exhaustion leading to denial of service of the entire server. Commit 33d1bae6c731ef1682fcdc47b428313be073a5d1 contains a patch.
Severity
7.5 (High)
SSVC
Exploitation: poc
Automatable: yes
Technical Impact: partial
CISA Coordinator (v2.0.3)
CWE
- CWE-770 - Allocation of Resources Without Limits or Throttling
Assigner
References
2 references
| URL | Tags |
|---|---|
| https://github.com/WWBN/AVideo/security/advisorie… | x_refsource_CONFIRM |
| https://github.com/WWBN/AVideo/commit/33d1bae6c73… | x_refsource_MISC |
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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.