CWE-770
Weakness 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.
Dimensions
- Behavior-Type: Allocation
- Behavior-Property: Without Limits or Throttling
- Resource-Type: Resources
Mapping guidance
This CWE entry is at the Base level of abstraction, which is a preferred level of abstraction for mapping to the root causes of vulnerabilities.
Carefully read both the name and description to ensure that this mapping is an appropriate fit. Do not try to 'force' a mapping to a lower-level Base/Variant simply to comply with this preferred level of abstraction.
Relationships and members
Modes of introduction
OMISSION: This weakness is caused by missing a security tactic during the architecture and design phase.
Detection methods
Manual Static Analysis
Manual static analysis can be useful for finding this weakness, but it might not achieve desired code coverage within limited time constraints. If denial-of-service is not considered a significant risk, or if there is strong emphasis on consequences such as code execution, then manual analysis may not focus on this weakness at all.
Fuzzing
While fuzzing is typically geared toward finding low-level implementation bugs, it can inadvertently find uncontrolled resource allocation problems. This can occur when the fuzzer generates a large number of test cases but does not restart the targeted product in between test cases. If an individual test case produces a crash, but it does not do so reliably, then an inability to limit resource allocation may be the cause.
When the allocation is directly affected by numeric inputs, then fuzzing may produce indications of this weakness.
Effectiveness: Opportunistic
Automated Dynamic Analysis
Certain automated dynamic analysis techniques may be effective in producing side effects of uncontrolled resource allocation problems, especially with resources such as processes, memory, and connections. The technique may involve generating a large number of requests to the product within a short time frame. Manual analysis is likely required to interpret the results.
Automated Static Analysis
Specialized configuration or tuning may be required to train automated tools to recognize this weakness.
Automated static analysis typically has limited utility in recognizing unlimited allocation problems, except for the missing release of program-independent system resources such as files, sockets, and processes, or unchecked arguments to memory. For system resources, automated static analysis may be able to detect circumstances in which resources are not released after they have expired, or if too much of a resource is requested at once, as can occur with memory. Automated analysis of configuration files may be able to detect settings that do not specify a maximum value.
Automated static analysis tools will not be appropriate for detecting exhaustion of custom resources, such as an intended security policy in which a bulletin board user is only allowed to make a limited number of posts per day.
Notes
Relationship
This entry is different from uncontrolled resource consumption (CWE-400) in that there are other weaknesses that are related to inability to control resource consumption, such as holding on to a resource too long after use, or not correctly keeping track of active resources so that they can be managed and released when they are finished (CWE-771).
Theoretical
Vulnerability theory is largely about how behaviors and resources interact. "Resource exhaustion" can be regarded as either a consequence or an attack, depending on the perspective. This entry is an attempt to reflect one of the underlying weaknesses that enable these attacks (or consequences) to take place.
Content history
Contributed or reviewed taxonomy mappings for ISA/IEC 62443
updated Related_Attack_Patterns
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updated Demonstrative_Examples, Likelihood_of_Exploit, Modes_of_Introduction, Potential_Mitigations, References, Relationships, Taxonomy_Mappings
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updated Demonstrative_Examples, Description, Relationships, Taxonomy_Mappings
updated Related_Attack_Patterns, Relationships
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updated Applicable_Platforms, Description, Maintenance_Notes, Potential_Mitigations, Relationship_Notes, Relationships
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updated Description, Detection_Factors
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updated Applicable_Platforms, Relationships, Weakness_Ordinalities
updated Demonstrative_Examples, Dimensions
4410 vulnerabilities reference this CWE, most recent first.
GHSA-F96H-PMFR-66VW
Vulnerability from github – Published: 2024-10-15 18:12 – Updated: 2024-10-15 19:56Summary
Starlette treats multipart/form-data parts without a filename as text form fields and buffers those in byte strings with no size limit. This allows an attacker to upload arbitrary large form fields and cause Starlette to both slow down significantly due to excessive memory allocations and copy operations, and also consume more and more memory until the server starts swapping and grinds to a halt, or the OS terminates the server process with an OOM error. Uploading multiple such requests in parallel may be enough to render a service practically unusable, even if reasonable request size limits are enforced by a reverse proxy in front of Starlette.
PoC
from starlette.applications import Starlette
from starlette.routing import Route
async def poc(request):
async with request.form():
pass
app = Starlette(routes=[
Route('/', poc, methods=["POST"]),
])
curl http://localhost:8000 -F 'big=</dev/urandom'
Impact
This Denial of service (DoS) vulnerability affects all applications built with Starlette (or FastAPI) accepting form requests.
{
"affected": [
{
"package": {
"ecosystem": "PyPI",
"name": "starlette"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "0.40.0"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"aliases": [
"CVE-2024-47874"
],
"database_specific": {
"cwe_ids": [
"CWE-770"
],
"github_reviewed": true,
"github_reviewed_at": "2024-10-15T18:12:57Z",
"nvd_published_at": "2024-10-15T16:15:05Z",
"severity": "HIGH"
},
"details": "### Summary\nStarlette treats `multipart/form-data` parts without a `filename` as text form fields and buffers those in byte strings with no size limit. This allows an attacker to upload arbitrary large form fields and cause Starlette to both slow down significantly due to excessive memory allocations and copy operations, and also consume more and more memory until the server starts swapping and grinds to a halt, or the OS terminates the server process with an OOM error. Uploading multiple such requests in parallel may be enough to render a service practically unusable, even if reasonable request size limits are enforced by a reverse proxy in front of Starlette.\n\n### PoC\n\n```python\nfrom starlette.applications import Starlette\nfrom starlette.routing import Route\n\nasync def poc(request):\n async with request.form():\n pass\n\napp = Starlette(routes=[\n Route(\u0027/\u0027, poc, methods=[\"POST\"]),\n])\n```\n\n```sh\ncurl http://localhost:8000 -F \u0027big=\u003c/dev/urandom\u0027\n```\n\n### Impact\nThis Denial of service (DoS) vulnerability affects all applications built with Starlette (or FastAPI) accepting form requests.\n",
"id": "GHSA-f96h-pmfr-66vw",
"modified": "2024-10-15T19:56:06Z",
"published": "2024-10-15T18:12:57Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/encode/starlette/security/advisories/GHSA-f96h-pmfr-66vw"
},
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2024-47874"
},
{
"type": "WEB",
"url": "https://github.com/encode/starlette/commit/fd038f3070c302bff17ef7d173dbb0b007617733"
},
{
"type": "PACKAGE",
"url": "https://github.com/encode/starlette"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:N",
"type": "CVSS_V3"
},
{
"score": "CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N",
"type": "CVSS_V4"
}
],
"summary": "Starlette Denial of service (DoS) via multipart/form-data"
}
GHSA-F96P-JHRP-872G
Vulnerability from github – Published: 2022-05-13 01:04 – Updated: 2022-05-13 01:04An issue was discovered in the Binary File Descriptor (BFD) library (aka libbfd), as distributed in GNU Binutils 2.32. It is an attempted excessive memory allocation in setup_group in elf.c.
{
"affected": [],
"aliases": [
"CVE-2019-9072"
],
"database_specific": {
"cwe_ids": [
"CWE-770"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2019-02-24T00:29:00Z",
"severity": "MODERATE"
},
"details": "An issue was discovered in the Binary File Descriptor (BFD) library (aka libbfd), as distributed in GNU Binutils 2.32. It is an attempted excessive memory allocation in setup_group in elf.c.",
"id": "GHSA-f96p-jhrp-872g",
"modified": "2022-05-13T01:04:41Z",
"published": "2022-05-13T01:04:41Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2019-9072"
},
{
"type": "WEB",
"url": "https://gcc.gnu.org/bugzilla/show_bug.cgi?id=89396"
},
{
"type": "WEB",
"url": "https://security.gentoo.org/glsa/202107-24"
},
{
"type": "WEB",
"url": "https://security.netapp.com/advisory/ntap-20190314-0003"
},
{
"type": "WEB",
"url": "https://sourceware.org/bugzilla/show_bug.cgi?id=24232"
},
{
"type": "WEB",
"url": "https://sourceware.org/bugzilla/show_bug.cgi?id=24237"
},
{
"type": "WEB",
"url": "https://support.f5.com/csp/article/K12541829"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:U/C:N/I:N/A:H",
"type": "CVSS_V3"
}
]
}
GHSA-F9QC-QG88-7PQ5
Vulnerability from github – Published: 2026-08-28 18:34 – Updated: 2026-08-28 18:34The decode_unknown_field function in buffa's protobuf decoder allocated heap memory in proportion to untrusted input (unknown fields in the serialized protobuf) without enforcing an allocation budget. Any message decoded from untrusted input using code generated with preserve_unknown_fields=true (the default) was affected. A small, well-formed payload of nested unknown fields inside a StartGroup could trigger roughly 22× memory amplification (e.g., a 64 MiB input forcing ~1.4 GB of heap allocation), and length-delimited unknown fields could be sized arbitrarily, enabling an unauthenticated attacker to crash a process via memory exhaustion. This was reachable from the default decode APIs, since the top-level message size cap did not account for in-decode amplification.
For users of connectrpc - the DEFAULT_MAX_MESSAGE_SIZE for connectrpc is 4MiB, which limits amplification in the worst case to ~88 MiB of memory. A flood of concurrent requests with this pattern could still be used to exhaust available memory, however.
Users are advised to either set preserve_unknown_fields=false on their current generated code, or upgrade to 0.8.0, which enforces per-message unknown field count limits - this is configurable, with a default of 1 million unknown fields, or ~40MiB of allocation overhead per message.
Users are advised to update to the latest version, which enforces per-message unknown field count limits.
Thank you to @p80n-sec for reporting this issue.
{
"affected": [
{
"package": {
"ecosystem": "crates.io",
"name": "buffa"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "0.8.0"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"aliases": [
"CVE-2026-55407"
],
"database_specific": {
"cwe_ids": [
"CWE-400",
"CWE-770",
"CWE-789"
],
"github_reviewed": true,
"github_reviewed_at": "2026-08-28T18:34:22Z",
"nvd_published_at": "2026-07-16T17:16:57Z",
"severity": "MODERATE"
},
"details": "The `decode_unknown_field` function in buffa\u0027s protobuf decoder allocated heap memory in proportion to untrusted input (unknown fields in the serialized protobuf) without enforcing an allocation budget. Any message decoded from untrusted input using code generated with `preserve_unknown_fields=true` (the default) was affected. A small, well-formed payload of nested unknown fields inside a StartGroup could trigger roughly 22\u00d7 memory amplification (e.g., a 64 MiB input forcing ~1.4 GB of heap allocation), and length-delimited unknown fields could be sized arbitrarily, enabling an unauthenticated attacker to crash a process via memory exhaustion. This was reachable from the default decode APIs, since the top-level message size cap did not account for in-decode amplification. \n\nFor users of connectrpc - the DEFAULT_MAX_MESSAGE_SIZE for connectrpc is 4MiB, which limits amplification in the worst case to ~88 MiB of memory. A flood of concurrent requests with this pattern could still be used to exhaust available memory, however.\n\nUsers are advised to either set `preserve_unknown_fields=false` on their current generated code, or upgrade to 0.8.0, which enforces per-message unknown field count limits - this is configurable, with a default of 1 million unknown fields, or ~40MiB of allocation overhead per message.\nUsers are advised to update to the latest version, which enforces per-message unknown field count limits.\n\nThank you to @p80n-sec for reporting this issue.",
"id": "GHSA-f9qc-qg88-7pq5",
"modified": "2026-08-28T18:34:22Z",
"published": "2026-08-28T18:34:22Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/anthropics/buffa/security/advisories/GHSA-f9qc-qg88-7pq5"
},
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-55407"
},
{
"type": "WEB",
"url": "https://github.com/anthropics/buffa/pull/184"
},
{
"type": "WEB",
"url": "https://github.com/anthropics/buffa/commit/278fa43fcff661d4ee6bd83b75955a153d4281fc"
},
{
"type": "PACKAGE",
"url": "https://github.com/anthropics/buffa"
},
{
"type": "WEB",
"url": "https://github.com/anthropics/buffa/releases/tag/v0.8.0"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:4.0/AV:N/AC:L/AT:P/PR:N/UI:N/VC:N/VI:N/VA:L/SC:N/SI:N/SA:N",
"type": "CVSS_V4"
}
],
"summary": "Buffa Vulnerable to Memory Exhaustion Denial of Service in decode_unknown_field via Unbounded Allocation"
}
GHSA-FC2V-VCWJ-269V
Vulnerability from github – Published: 2025-11-13 00:10 – Updated: 2025-11-13 00:10Impact
In affected versions, brotli "bombs" (highly compressed brotli streams, such as many zeros) can be sent to the server. Since the server will attempt to decompress these streams before applying various maximums, this can lead to exhaustion of the available memory and thus a Denial of Service.
This can be done if the DSN is known, which it is in many common setups (JavaScript, Mobile Apps).
Patches
Patched in Bugsink 2.0.5
{
"affected": [
{
"package": {
"ecosystem": "PyPI",
"name": "bugsink"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "2.0.5"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"aliases": [
"CVE-2025-64508"
],
"database_specific": {
"cwe_ids": [
"CWE-770"
],
"github_reviewed": true,
"github_reviewed_at": "2025-11-13T00:10:50Z",
"nvd_published_at": "2025-11-10T22:15:39Z",
"severity": "HIGH"
},
"details": "### Impact\n\nIn affected versions, brotli \"bombs\" (highly compressed brotli streams, such as many zeros) can be sent to the server. Since the server will attempt to decompress these streams before applying various maximums, this can lead to exhaustion of the available memory and thus a Denial of Service.\n\nThis can be done if the `DSN` is known, which it is in many common setups (JavaScript, Mobile Apps).\n\n### Patches\n\nPatched in Bugsink `2.0.5`",
"id": "GHSA-fc2v-vcwj-269v",
"modified": "2025-11-13T00:10:50Z",
"published": "2025-11-13T00:10:50Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/bugsink/bugsink/security/advisories/GHSA-fc2v-vcwj-269v"
},
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2025-64508"
},
{
"type": "WEB",
"url": "https://github.com/google/brotli/issues/1327"
},
{
"type": "WEB",
"url": "https://github.com/google/brotli/issues/1375"
},
{
"type": "WEB",
"url": "https://github.com/bugsink/bugsink/pull/266"
},
{
"type": "WEB",
"url": "https://github.com/google/brotli/pull/1234"
},
{
"type": "WEB",
"url": "https://github.com/bugsink/bugsink/commit/3f65544aab3ad5303d97009136640de97b0676a5"
},
{
"type": "WEB",
"url": "https://github.com/google/brotli/commit/67d78bc41db1a0d03f2e763497748f2f69946627"
},
{
"type": "PACKAGE",
"url": "https://github.com/bugsink/bugsink"
},
{
"type": "WEB",
"url": "https://github.com/google/brotli/releases/tag/v1.2.0"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H",
"type": "CVSS_V3"
}
],
"summary": "Bugsink is vulnerable to unauthenticated remote DoS via crafted Brotli input"
}
GHSA-FC3H-CC99-762G
Vulnerability from github – Published: 2025-06-06 09:30 – Updated: 2025-06-06 09:30Resource allocation control failure vulnerability in the ArkUI framework Impact: Successful exploitation of this vulnerability may affect availability.
{
"affected": [],
"aliases": [
"CVE-2024-58114"
],
"database_specific": {
"cwe_ids": [
"CWE-770"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2025-06-06T07:15:24Z",
"severity": "MODERATE"
},
"details": "Resource allocation control failure vulnerability in the ArkUI framework\nImpact: Successful exploitation of this vulnerability may affect availability.",
"id": "GHSA-fc3h-cc99-762g",
"modified": "2025-06-06T09:30:23Z",
"published": "2025-06-06T09:30:23Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2024-58114"
},
{
"type": "WEB",
"url": "https://consumer.huawei.com/en/support/bulletin/2025/6"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:L/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:L",
"type": "CVSS_V3"
}
]
}
GHSA-FC4Q-WR43-J7J5
Vulnerability from github – Published: 2024-10-11 18:32 – Updated: 2024-10-11 18:32An Allocation of Resources Without Limits or Throttling vulnerability in the PFE management daemon (evo-pfemand) of Juniper Networks Junos OS Evolved allows an authenticated, network-based attacker to cause an FPC crash leading to a Denial of Service (DoS).When specific SNMP GET operations or specific low-priviledged CLI commands are executed, a GUID resource leak will occur, eventually leading to exhaustion and resulting in FPCs to hang. Affected FPCs need to be manually restarted to recover.
GUID exhaustion will trigger a syslog message like one of the following:
evo-pfemand[]: get_next_guid: Ran out of Guid Space ... evo-aftmand-zx[]: get_next_guid: Ran out of Guid Space ... The leak can be monitored by running the following command and taking note of the values in the rightmost column labeled Guids:
user@host> show platform application-info allocations app evo-pfemand/evo-pfemand
In case one or more of these values are constantly increasing the leak is happening.
This issue affects Junos OS Evolved:
- All versions before 21.2R3-S8-EVO,
- 21.3 versions before 21.3R3-EVO;
-
21.4 versions before 22.1R2-EVO,
-
22.1 versions before 22.1R1-S1-EVO, 22.1R2-EVO.
Please note that this issue is similar to, but different from CVE-2024-47505 and CVE-2024-47509.
{
"affected": [],
"aliases": [
"CVE-2024-47508"
],
"database_specific": {
"cwe_ids": [
"CWE-770"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2024-10-11T16:15:12Z",
"severity": "HIGH"
},
"details": "An Allocation of Resources Without Limits or Throttling\u00a0vulnerability in the PFE management daemon (evo-pfemand) of Juniper Networks Junos OS Evolved allows an authenticated, network-based attacker to cause an FPC crash leading to a Denial of Service (DoS).When specific SNMP GET operations or specific low-priviledged CLI commands are executed, a GUID resource leak will occur, eventually leading to exhaustion and resulting in FPCs to hang. Affected FPCs need to be manually restarted to recover.\n\nGUID exhaustion will trigger a syslog message like one of the following:\n\nevo-pfemand[\u003cpid\u003e]: get_next_guid: Ran out of Guid Space ...\nevo-aftmand-zx[\u003cpid\u003e]: get_next_guid: Ran out of Guid Space ...\nThe leak can be monitored by running the following command and taking note of the values in the rightmost column labeled Guids:\n\n\n\n\n\nuser@host\u003e show platform application-info allocations app evo-pfemand/evo-pfemand\n\n\n\nIn case one or more of these values are constantly increasing the leak is happening.\n\nThis issue affects Junos OS Evolved:\n\n\n\n * All versions before 21.2R3-S8-EVO,\n * 21.3 versions before 21.3R3-EVO;\n * 21.4 versions before 22.1R2-EVO,\n\n * 22.1 versions before\u00a022.1R1-S1-EVO, 22.1R2-EVO.\n\n\n\n\n\nPlease note that this issue is similar to, but different from CVE-2024-47505 and CVE-2024-47509.",
"id": "GHSA-fc4q-wr43-j7j5",
"modified": "2024-10-11T18:32:49Z",
"published": "2024-10-11T18:32:49Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2024-47508"
},
{
"type": "WEB",
"url": "https://supportportal.juniper.net"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H",
"type": "CVSS_V3"
},
{
"score": "CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:L/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:Y/R:X/V:X/RE:M/U:X",
"type": "CVSS_V4"
}
]
}
GHSA-FC6J-W9HX-R5XV
Vulnerability from github – Published: 2023-12-07 09:30 – Updated: 2023-12-09 06:30A lack of rate limiting in pjActionAJaxSend in Availability Booking Calendar 5.0 allows attackers to cause resource exhaustion.
{
"affected": [],
"aliases": [
"CVE-2023-48831"
],
"database_specific": {
"cwe_ids": [
"CWE-400",
"CWE-770"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2023-12-07T07:15:11Z",
"severity": "HIGH"
},
"details": "A lack of rate limiting in pjActionAJaxSend in Availability Booking Calendar 5.0 allows attackers to cause resource exhaustion.",
"id": "GHSA-fc6j-w9hx-r5xv",
"modified": "2023-12-09T06:30:20Z",
"published": "2023-12-07T09:30:44Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2023-48831"
},
{
"type": "WEB",
"url": "https://www.phpjabbers.com/availability-booking-calendar/#sectionDemo"
},
{
"type": "WEB",
"url": "http://packetstormsecurity.com/files/176039"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H",
"type": "CVSS_V3"
}
]
}
GHSA-FC83-9JWQ-GC2M
Vulnerability from github – Published: 2025-03-24 19:39 – Updated: 2025-03-24 19:39Prior to version 0.10.3, the built-in clients of the web-push crate eagerly allocated memory based on the Content-Length header returned by the Web Push endpoint. Malicious Web Push endpoints could return a large Content-Length without ever having to send as much data, leading to denial of service by memory exhaustion.
Services providing Web Push notifications typically allow the user to register an arbitrary endpoint, so the endpoint should not be trusted.
The fixed version 0.10.3 now limits the amount of memory it will allocate for each response, limits the amount of data it will read from the endpoint, and returns an error if the endpoint sends too much data.
As before, it is recommended that services add a timeout for each request to Web Push endpoints.
{
"affected": [
{
"package": {
"ecosystem": "crates.io",
"name": "web-push"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "0.10.4"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"aliases": [],
"database_specific": {
"cwe_ids": [
"CWE-770"
],
"github_reviewed": true,
"github_reviewed_at": "2025-03-24T19:39:27Z",
"nvd_published_at": null,
"severity": "MODERATE"
},
"details": "Prior to version 0.10.3, the built-in clients of the `web-push` crate eagerly allocated memory based on the `Content-Length` header returned by the Web Push endpoint. Malicious Web Push endpoints could return a large `Content-Length` without ever having to send as much data, leading to denial of service by memory exhaustion.\n\nServices providing Web Push notifications typically allow the user to register an arbitrary endpoint, so the endpoint should not be trusted.\n\nThe fixed version 0.10.3 now limits the amount of memory it will allocate for each response, limits the amount of data it will read from the endpoint, and returns an error if the endpoint sends too much data.\n\nAs before, it is recommended that services add a timeout for each request to Web Push endpoints.",
"id": "GHSA-fc83-9jwq-gc2m",
"modified": "2025-03-24T19:39:27Z",
"published": "2025-03-24T19:39:27Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/pimeys/rust-web-push/pull/68"
},
{
"type": "PACKAGE",
"url": "https://github.com/pimeys/rust-web-push"
},
{
"type": "WEB",
"url": "https://rustsec.org/advisories/RUSTSEC-2025-0015.html"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:N/VI:N/VA:L/SC:N/SI:N/SA:N",
"type": "CVSS_V4"
}
],
"summary": "Web Push Denial of Service via malicious Web Push endpoint"
}
GHSA-FCCC-8M69-8R78
Vulnerability from github – Published: 2025-03-20 12:32 – Updated: 2025-03-21 23:59A vulnerability in ollama/ollama <=0.3.14 allows a malicious user to create a customized GGUF model file, upload it to the Ollama server, and create it. This can cause the server to allocate unlimited memory, leading to a Denial of Service (DoS) attack.
{
"affected": [
{
"package": {
"ecosystem": "Go",
"name": "github.com/ollama/ollama"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"last_affected": "0.3.14"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"aliases": [
"CVE-2025-0315"
],
"database_specific": {
"cwe_ids": [
"CWE-770"
],
"github_reviewed": true,
"github_reviewed_at": "2025-03-21T23:59:26Z",
"nvd_published_at": "2025-03-20T10:15:52Z",
"severity": "HIGH"
},
"details": "A vulnerability in ollama/ollama \u003c=0.3.14 allows a malicious user to create a customized GGUF model file, upload it to the Ollama server, and create it. This can cause the server to allocate unlimited memory, leading to a Denial of Service (DoS) attack.",
"id": "GHSA-fccc-8m69-8r78",
"modified": "2025-03-21T23:59:26Z",
"published": "2025-03-20T12:32:52Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2025-0315"
},
{
"type": "PACKAGE",
"url": "https://github.com/ollama/ollama"
},
{
"type": "WEB",
"url": "https://huntr.com/bounties/da414d29-b55a-496f-b135-17e0fcec67bc"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H",
"type": "CVSS_V3"
}
],
"summary": "Ollama Allocation of Resources Without Limits or Throttling vulnerability"
}
GHSA-FCM2-6C3H-PG6J
Vulnerability from github – Published: 2022-06-06 21:50 – Updated: 2023-07-24 19:33Description
An ExecSync request runs a command in a container and returns the output to the Kubelet. It is used for readiness and liveness probes within a pod. The way CRI-O runs ExecSync commands is through conmon. CRI-O asks conmon to start the process, and conmon writes the output to disk. CRI-O then reads the output and returns it to the Kubelet.
If the output of the command is large enough, it is possible to exhaust the memory (or disk usage) of the node. The following deployment is an example yaml file that will output around 8GB of ‘A’ characters, which would be written to disk by conmon and read by CRI-O.
apiVersion: apps/v1
kind: Deployment
metadata:
name: nginx-deployment100
spec:
selector:
matchLabels:
app: nginx
replicas: 2
template:
metadata:
labels:
app: nginx
spec:
containers:
- name: nginx
image: nginx:1.14.2
lifecycle:
postStart:
exec:
command: ["/bin/sh", "-c", "seq 1 50000000`; do echo -n 'aaaaaaaaaaaaaaaa'; done"]
Impact
It is possible for the node to be exhausted of memory or disk space, depending on the node the command is being run on. What is further problematic is that the memory and disk usage aren't attributed to the container, as this file and its processing are implementation details of CRI-O. The consequence of the exhaustion is that other services on the node, e.g. other containers, will be unable to allocate memory and thus causing a denial of service.
Patches
This vulnerability will be fixed in 1.24.1, 1.23.3, 1.22.5, v1.21.8, v1.20.8, v1.19.7
Workarounds
At the time of writing, no workaround exists other than ensuring only trusted images are used.
References
https://github.com/containerd/containerd/security/advisories/GHSA-5ffw-gxpp-mxpf
For more information
If you have any questions or comments about this advisory: * Open an issue in the CRI-O repo * To make a report, email your vulnerability to the private cncf-crio-security@lists.cncf.io list with the security details and the details expected for all CRI-O bug reports.
Credits
Disclosed by Ada Logics in a security audit sponsored by CNCF and facilitated by OSTIF.
{
"affected": [
{
"package": {
"ecosystem": "Go",
"name": "github.com/cri-o/cri-o"
},
"ranges": [
{
"events": [
{
"introduced": "1.24.0"
},
{
"fixed": "1.24.1"
}
],
"type": "ECOSYSTEM"
}
],
"versions": [
"1.24.0"
]
},
{
"package": {
"ecosystem": "Go",
"name": "github.com/cri-o/cri-o"
},
"ranges": [
{
"events": [
{
"introduced": "1.23.0"
},
{
"fixed": "1.23.3"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "Go",
"name": "github.com/cri-o/cri-o"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "1.22.5"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"aliases": [
"CVE-2022-1708"
],
"database_specific": {
"cwe_ids": [
"CWE-400",
"CWE-770"
],
"github_reviewed": true,
"github_reviewed_at": "2022-06-06T21:50:21Z",
"nvd_published_at": "2022-06-07T18:15:00Z",
"severity": "HIGH"
},
"details": "### Description\nAn ExecSync request runs a command in a container and returns the output to the Kubelet. It is used for readiness and liveness probes within a pod. The way CRI-O runs ExecSync commands is through conmon. CRI-O asks conmon to start the process, and conmon writes the output to disk. CRI-O then reads the output and returns it to the Kubelet.\n\nIf the output of the command is large enough, it is possible to exhaust the memory (or disk usage) of the node. The following deployment is an example yaml file that will output around 8GB of \u2018A\u2019 characters, which would be written to disk by conmon and read by CRI-O.\n\n```yaml\napiVersion: apps/v1\nkind: Deployment\nmetadata:\n name: nginx-deployment100\nspec:\n selector:\n matchLabels:\n app: nginx\n replicas: 2\n template:\n metadata:\n labels:\n app: nginx\n spec:\n containers:\n - name: nginx\n image: nginx:1.14.2\n lifecycle:\n postStart:\n exec:\n command: [\"/bin/sh\", \"-c\", \"seq 1 50000000`; do echo -n \u0027aaaaaaaaaaaaaaaa\u0027; done\"]\n```\n\n### Impact\nIt is possible for the node to be exhausted of memory or disk space, depending on the node the command is being run on. What is further problematic is that the memory and disk usage aren\u0027t attributed to the container, as this file and its processing are implementation details of CRI-O. The consequence of the exhaustion is that other services on the node, e.g. other containers, will be unable to allocate memory and thus causing a denial of service.\n\n### Patches\nThis vulnerability will be fixed in 1.24.1, 1.23.3, 1.22.5, v1.21.8, v1.20.8, v1.19.7\n\n### Workarounds\nAt the time of writing, no workaround exists other than ensuring only trusted images are used.\n\n### References\nhttps://github.com/containerd/containerd/security/advisories/GHSA-5ffw-gxpp-mxpf\n\n### For more information\nIf you have any questions or comments about this advisory:\n* Open an issue in [the CRI-O repo](http://github.com/cri-o/cri-o/issues)\n* To make a report, email your vulnerability to the private\n[cncf-crio-security@lists.cncf.io](mailto:cncf-crio-security@lists.cncf.io) list\nwith the security details and the details expected for [all CRI-O bug\nreports](https://github.com/cri-o/cri-o/blob/main/.github/ISSUE_TEMPLATE/bug-report.yml).\n\n### Credits\nDisclosed by Ada Logics in a security audit sponsored by CNCF and facilitated by OSTIF.\n",
"id": "GHSA-fcm2-6c3h-pg6j",
"modified": "2023-07-24T19:33:40Z",
"published": "2022-06-06T21:50:21Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/cri-o/cri-o/security/advisories/GHSA-fcm2-6c3h-pg6j"
},
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2022-1708"
},
{
"type": "WEB",
"url": "https://github.com/cri-o/cri-o/commit/f032cf649ecc7e0c46718bd9e7814bfb317cb544"
},
{
"type": "WEB",
"url": "https://bugzilla.redhat.com/show_bug.cgi?id=2085361"
},
{
"type": "PACKAGE",
"url": "https://github.com/cri-o/cri-o"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H",
"type": "CVSS_V3"
}
],
"summary": "Node DOS by way of memory exhaustion through ExecSync request in CRI-O"
}
Mitigation
Clearly specify the minimum and maximum expectations for capabilities, and dictate which behaviors are acceptable when resource allocation reaches limits.
Mitigation
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
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
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
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
- Mitigation of resource exhaustion attacks requires that the target system either:
- recognizes the attack and denies that user further access for a given amount of time, typically by using increasing time delays
- uniformly throttles all requests in order to make it more difficult to consume resources more quickly than they can again be freed.
- The first of these solutions is an issue in itself though, since it may allow attackers to prevent the use of the system by a particular valid user. If the attacker impersonates the valid user, they may be able to prevent the user from accessing the server in question.
- The second solution can be difficult to effectively institute -- and even when properly done, it does not provide a full solution. It simply requires more resources on the part of the attacker.
Mitigation
Ensure that protocols have specific limits of scale placed on them.
Mitigation MIT-38.1
- 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
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.