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.
3900 vulnerabilities reference this CWE, most recent first.
GHSA-PJ6Q-4VQ4-R8CG
Vulnerability from github – Published: 2026-05-07 21:23 – Updated: 2026-05-07 21:23Summary
PUT /api/echo/like/:id at internal/router/echo.go:12 is registered on PublicRouterGroup with no authentication and no rate limit. Anonymous callers increment the fav_count counter on any echo (including private echoes) by UUID, repeat the request without deduplication, and trigger a database write plus a four-key cache invalidation on every call. Alice harvests echo UUIDs from the public GET /api/echo/page response, inflates fav counts at will, and spams writes to amplify load on the DB and cache layers.
Details
Route registration at internal/router/echo.go:12:
appRouterGroup.PublicRouterGroup.PUT("/echo/like/:id", h.EchoHandler.LikeEcho())
PublicRouterGroup is r.Group("/api") without the JWT middleware that AuthRouterGroup applies. The handler passes through to EchoService.LikeEcho, which calls EchoRepository.LikeEcho at internal/repository/echo/echo.go:270:
func (echoRepository *EchoRepository) LikeEcho(ctx context.Context, id string) error {
var exists bool
if err := echoRepository.getDB(ctx).Model(&model.Echo{}).
Select("count(*) > 0").Where("id = ?", id).Find(&exists).Error; err != nil {
return err
}
if !exists {
return errors.New(commonModel.ECHO_NOT_FOUND)
}
if err := echoRepository.getDB(ctx).Model(&model.Echo{}).
Where("id = ?", id).
UpdateColumn("fav_count", gorm.Expr("fav_count + ?", 1)).Error; err != nil {
return err
}
return nil
}
No viewer check, no ownership check, no private-flag check. Compare the read path at EchoService.GetEchoById (internal/service/echo/echo.go:275-300) which rejects anonymous readers on private echoes; the like path skips that gate. InvalidateEchoCaches (internal/repository/echo/echo.go:51-58) clears the page cache, today cache, RSS cache, and per-echo cache on every like. Comment creation on the same router group runs behind checkRateLimit (internal/service/comment/comment.go:731-766, 3 per 60 s per IP plus 20 per 3600 s); the like endpoint has no such middleware.
Proof of Concept
Default install, anonymous caller on the network:
import requests
TARGET = "http://localhost:8300"
# 1) Discover an echo UUID from the public feed (no auth).
page = requests.get(f"{TARGET}/api/echo/page?page=1&pageSize=1").json()
echo_id = page["data"]["items"][0]["id"]
# 2) Like it. Repeat without deduplication.
for i in range(3):
r = requests.put(f"{TARGET}/api/echo/like/{echo_id}")
print(f"public like #{i+1}: HTTP {r.status_code} {r.text}")
# 3) Like a private echo by UUID. Private echoes never appear in /api/echo/page,
# but the UUID arrives via other channels (logs, referer, shared drafts).
private_id = "019daf77-4a97-7c4c-a63c-791b10ecfd0b" # admin-created private echo
r = requests.put(f"{TARGET}/api/echo/like/{private_id}")
print(f"private like: HTTP {r.status_code} {r.text}")
Observed on v4.5.6 in the test container:
public like #1: HTTP 200 {"code":1,"msg":"点赞Echo成功","data":null}
public like #2: HTTP 200 {"code":1,"msg":"点赞Echo成功","data":null}
public like #3: HTTP 200 {"code":1,"msg":"点赞Echo成功","data":null}
private like: HTTP 200 {"code":1,"msg":"点赞Echo成功","data":null}
The same IP likes the same echo three times without 429 or dedup. The private-echo like (UUID 019daf77-4a97...) succeeded even though GetEchosById would refuse to read that echo for an anonymous caller.
Impact
Anonymous, rate-limit-free writes against any echo's fav_count. Direct impact:
- Popularity signal destruction. fav_count powers the
hotfeed; a single script skews the ranking at will. - Private-boundary bypass. Private-flagged echoes remain non-readable, but they accept likes from anyone who knows the UUID. UUIDs leak through logs, referer headers on shared drafts, and the owner's browser history.
- Server and cache load. Every call triggers a SQLite
UPDATEtransaction plus four cache-key invalidations. A single attacker from one IP drives sustained writes and forces cache stampedes for every concurrent reader.
Reachability is anonymous. No credentials, no tokens, no session. Every Ech0 deployment that exposes port 6277 is reachable.
Recommended Fix
Move the route to AuthRouterGroup so JWT middleware applies, add a per-user dedup gate, and rate-limit at the middleware layer:
appRouterGroup.AuthRouterGroup.PUT(
"/echo/like/:id",
middleware.RateLimit(5, 10),
h.EchoHandler.LikeEcho(),
)
At the service layer, check the private flag and record the user/echo pair in a join table to prevent repeat increments from the same user:
func (s *EchoService) LikeEcho(ctx context.Context, id string) error {
userID := viewer.MustFromContext(ctx).UserID()
if userID == "" {
return errors.New(commonModel.NO_PERMISSION_DENIED)
}
echo, err := s.echoRepository.GetEchosById(ctx, id)
if err != nil || echo == nil {
return errors.New(commonModel.ECHO_NOT_FOUND)
}
if echo.Private {
user, err := s.commonService.CommonGetUserByUserId(ctx, userID)
if err != nil || !user.IsAdmin {
return errors.New(commonModel.NO_PERMISSION_DENIED)
}
}
return s.echoRepository.LikeEchoOnce(ctx, id, userID)
}
Found by aisafe.io
{
"affected": [
{
"package": {
"ecosystem": "Go",
"name": "github.com/lin-snow/Ech0"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "1.4.8-0.20260503035905-cecc2c19b590"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"aliases": [],
"database_specific": {
"cwe_ids": [
"CWE-770",
"CWE-862"
],
"github_reviewed": true,
"github_reviewed_at": "2026-05-07T21:23:57Z",
"nvd_published_at": null,
"severity": "MODERATE"
},
"details": "## Summary\n\n`PUT /api/echo/like/:id` at `internal/router/echo.go:12` is registered on `PublicRouterGroup` with no authentication and no rate limit. Anonymous callers increment the `fav_count` counter on any echo (including private echoes) by UUID, repeat the request without deduplication, and trigger a database write plus a four-key cache invalidation on every call. Alice harvests echo UUIDs from the public `GET /api/echo/page` response, inflates fav counts at will, and spams writes to amplify load on the DB and cache layers.\n\n## Details\n\nRoute registration at `internal/router/echo.go:12`:\n\n```go\nappRouterGroup.PublicRouterGroup.PUT(\"/echo/like/:id\", h.EchoHandler.LikeEcho())\n```\n\n`PublicRouterGroup` is `r.Group(\"/api\")` without the JWT middleware that `AuthRouterGroup` applies. The handler passes through to `EchoService.LikeEcho`, which calls `EchoRepository.LikeEcho` at `internal/repository/echo/echo.go:270`:\n\n```go\nfunc (echoRepository *EchoRepository) LikeEcho(ctx context.Context, id string) error {\n var exists bool\n if err := echoRepository.getDB(ctx).Model(\u0026model.Echo{}).\n Select(\"count(*) \u003e 0\").Where(\"id = ?\", id).Find(\u0026exists).Error; err != nil {\n return err\n }\n if !exists {\n return errors.New(commonModel.ECHO_NOT_FOUND)\n }\n if err := echoRepository.getDB(ctx).Model(\u0026model.Echo{}).\n Where(\"id = ?\", id).\n UpdateColumn(\"fav_count\", gorm.Expr(\"fav_count + ?\", 1)).Error; err != nil {\n return err\n }\n return nil\n}\n```\n\nNo viewer check, no ownership check, no private-flag check. Compare the read path at `EchoService.GetEchoById` (`internal/service/echo/echo.go:275-300`) which rejects anonymous readers on private echoes; the like path skips that gate. `InvalidateEchoCaches` (`internal/repository/echo/echo.go:51-58`) clears the page cache, today cache, RSS cache, and per-echo cache on every like. Comment creation on the same router group runs behind `checkRateLimit` (`internal/service/comment/comment.go:731-766`, 3 per 60 s per IP plus 20 per 3600 s); the like endpoint has no such middleware.\n\n## Proof of Concept\n\nDefault install, anonymous caller on the network:\n\n```python\nimport requests\nTARGET = \"http://localhost:8300\"\n\n# 1) Discover an echo UUID from the public feed (no auth).\npage = requests.get(f\"{TARGET}/api/echo/page?page=1\u0026pageSize=1\").json()\necho_id = page[\"data\"][\"items\"][0][\"id\"]\n\n# 2) Like it. Repeat without deduplication.\nfor i in range(3):\n r = requests.put(f\"{TARGET}/api/echo/like/{echo_id}\")\n print(f\"public like #{i+1}: HTTP {r.status_code} {r.text}\")\n\n# 3) Like a private echo by UUID. Private echoes never appear in /api/echo/page,\n# but the UUID arrives via other channels (logs, referer, shared drafts).\nprivate_id = \"019daf77-4a97-7c4c-a63c-791b10ecfd0b\" # admin-created private echo\nr = requests.put(f\"{TARGET}/api/echo/like/{private_id}\")\nprint(f\"private like: HTTP {r.status_code} {r.text}\")\n```\n\nObserved on v4.5.6 in the test container:\n\n```\npublic like #1: HTTP 200 {\"code\":1,\"msg\":\"\u70b9\u8d5eEcho\u6210\u529f\",\"data\":null}\npublic like #2: HTTP 200 {\"code\":1,\"msg\":\"\u70b9\u8d5eEcho\u6210\u529f\",\"data\":null}\npublic like #3: HTTP 200 {\"code\":1,\"msg\":\"\u70b9\u8d5eEcho\u6210\u529f\",\"data\":null}\nprivate like: HTTP 200 {\"code\":1,\"msg\":\"\u70b9\u8d5eEcho\u6210\u529f\",\"data\":null}\n```\n\nThe same IP likes the same echo three times without 429 or dedup. The private-echo like (UUID `019daf77-4a97...`) succeeded even though `GetEchosById` would refuse to read that echo for an anonymous caller.\n\n## Impact\n\nAnonymous, rate-limit-free writes against any echo\u0027s `fav_count`. Direct impact:\n\n- **Popularity signal destruction.** fav_count powers the `hot` feed; a single script skews the ranking at will.\n- **Private-boundary bypass.** Private-flagged echoes remain non-readable, but they accept likes from anyone who knows the UUID. UUIDs leak through logs, referer headers on shared drafts, and the owner\u0027s browser history.\n- **Server and cache load.** Every call triggers a SQLite `UPDATE` transaction plus four cache-key invalidations. A single attacker from one IP drives sustained writes and forces cache stampedes for every concurrent reader.\n\nReachability is anonymous. No credentials, no tokens, no session. Every Ech0 deployment that exposes port 6277 is reachable.\n\n## Recommended Fix\n\nMove the route to `AuthRouterGroup` so JWT middleware applies, add a per-user dedup gate, and rate-limit at the middleware layer:\n\n```go\nappRouterGroup.AuthRouterGroup.PUT(\n \"/echo/like/:id\",\n middleware.RateLimit(5, 10),\n h.EchoHandler.LikeEcho(),\n)\n```\n\nAt the service layer, check the private flag and record the user/echo pair in a join table to prevent repeat increments from the same user:\n\n```go\nfunc (s *EchoService) LikeEcho(ctx context.Context, id string) error {\n userID := viewer.MustFromContext(ctx).UserID()\n if userID == \"\" {\n return errors.New(commonModel.NO_PERMISSION_DENIED)\n }\n echo, err := s.echoRepository.GetEchosById(ctx, id)\n if err != nil || echo == nil {\n return errors.New(commonModel.ECHO_NOT_FOUND)\n }\n if echo.Private {\n user, err := s.commonService.CommonGetUserByUserId(ctx, userID)\n if err != nil || !user.IsAdmin {\n return errors.New(commonModel.NO_PERMISSION_DENIED)\n }\n }\n return s.echoRepository.LikeEchoOnce(ctx, id, userID)\n}\n```\n\n---\n*Found by [aisafe.io](https://aisafe.io)*",
"id": "GHSA-pj6q-4vq4-r8cg",
"modified": "2026-05-07T21:23:57Z",
"published": "2026-05-07T21:23:57Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/lin-snow/Ech0/security/advisories/GHSA-pj6q-4vq4-r8cg"
},
{
"type": "WEB",
"url": "https://github.com/lin-snow/Ech0/commit/cecc2c19b590df85d79ea98457faa143130cd620"
},
{
"type": "PACKAGE",
"url": "https://github.com/lin-snow/Ech0"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:L/A:L",
"type": "CVSS_V3"
}
],
"summary": "Ech0 allows PUT /api/echo/like/:id unauthenticated: anonymous callers to modify any echo\u0027s fav_count"
}
GHSA-PJ8Q-V235-P5PV
Vulnerability from github – Published: 2022-05-24 19:07 – Updated: 2022-05-24 19:07A vulnerability has been identified in RWG1.M12 (All versions < V1.16.16), RWG1.M12D (All versions < V1.16.16), RWG1.M8 (All versions < V1.16.16). Sending specially crafted ARP packets to an affected device could cause a partial denial-of-service, preventing the device to operate normally. A restart is needed to restore normal operations.
{
"affected": [],
"aliases": [
"CVE-2021-25671"
],
"database_specific": {
"cwe_ids": [
"CWE-770"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2021-07-13T11:15:00Z",
"severity": "MODERATE"
},
"details": "A vulnerability has been identified in RWG1.M12 (All versions \u003c V1.16.16), RWG1.M12D (All versions \u003c V1.16.16), RWG1.M8 (All versions \u003c V1.16.16). Sending specially crafted ARP packets to an affected device could cause a partial denial-of-service, preventing the device to operate normally. A restart is needed to restore normal operations.",
"id": "GHSA-pj8q-v235-p5pv",
"modified": "2022-05-24T19:07:44Z",
"published": "2022-05-24T19:07:44Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2021-25671"
},
{
"type": "WEB",
"url": "https://cert-portal.siemens.com/productcert/pdf/ssa-448291.pdf"
}
],
"schema_version": "1.4.0",
"severity": []
}
GHSA-PJFV-46PV-9Q9C
Vulnerability from github – Published: 2022-05-24 19:17 – Updated: 2022-08-13 00:00A vulnerability has been identified in RUGGEDCOM ROX MX5000 (All versions < V2.14.1), RUGGEDCOM ROX RX1400 (All versions < V2.14.1), RUGGEDCOM ROX RX1500 (All versions < V2.14.1), RUGGEDCOM ROX RX1501 (All versions < V2.14.1), RUGGEDCOM ROX RX1510 (All versions < V2.14.1), RUGGEDCOM ROX RX1511 (All versions < V2.14.1), RUGGEDCOM ROX RX1512 (All versions < V2.14.1), RUGGEDCOM ROX RX1524 (All versions < V2.14.1), RUGGEDCOM ROX RX1536 (All versions < V2.14.1), RUGGEDCOM ROX RX5000 (All versions < V2.14.1). Affected devices write crashdumps without checking if enough space is available on the filesystem. Once the crashdump fills the entire root filesystem, affected devices fail to boot successfully. An attacker can leverage this vulnerability to cause a permanent Denial-of-Service.
{
"affected": [],
"aliases": [
"CVE-2021-41546"
],
"database_specific": {
"cwe_ids": [
"CWE-400",
"CWE-770"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2021-10-12T10:15:00Z",
"severity": "HIGH"
},
"details": "A vulnerability has been identified in RUGGEDCOM ROX MX5000 (All versions \u003c V2.14.1), RUGGEDCOM ROX RX1400 (All versions \u003c V2.14.1), RUGGEDCOM ROX RX1500 (All versions \u003c V2.14.1), RUGGEDCOM ROX RX1501 (All versions \u003c V2.14.1), RUGGEDCOM ROX RX1510 (All versions \u003c V2.14.1), RUGGEDCOM ROX RX1511 (All versions \u003c V2.14.1), RUGGEDCOM ROX RX1512 (All versions \u003c V2.14.1), RUGGEDCOM ROX RX1524 (All versions \u003c V2.14.1), RUGGEDCOM ROX RX1536 (All versions \u003c V2.14.1), RUGGEDCOM ROX RX5000 (All versions \u003c V2.14.1). Affected devices write crashdumps without checking if enough space is available on the filesystem. Once the crashdump fills the entire root filesystem, affected devices fail to boot successfully. An attacker can leverage this vulnerability to cause a permanent Denial-of-Service.",
"id": "GHSA-pjfv-46pv-9q9c",
"modified": "2022-08-13T00:00:37Z",
"published": "2022-05-24T19:17:20Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2021-41546"
},
{
"type": "WEB",
"url": "https://cert-portal.siemens.com/productcert/pdf/ssa-173565.pdf"
}
],
"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-PM2P-78R8-WJH9
Vulnerability from github – Published: 2026-08-27 18:32 – Updated: 2026-08-31 18:31An issue in the NF Discovery endpoint of free5gc v4.0.1 allows attackers to cause a Denial of Service (DoS) via a crafted snssais query.
{
"affected": [],
"aliases": [
"CVE-2026-30063"
],
"database_specific": {
"cwe_ids": [
"CWE-770"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2026-08-27T17:17:51Z",
"severity": "HIGH"
},
"details": "An issue in the NF Discovery endpoint of free5gc v4.0.1 allows attackers to cause a Denial of Service (DoS) via a crafted snssais query.",
"id": "GHSA-pm2p-78r8-wjh9",
"modified": "2026-08-31T18:31:21Z",
"published": "2026-08-27T18:32:22Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-30063"
},
{
"type": "WEB",
"url": "https://github.com/free5gc/free5gc/issues/758"
}
],
"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-PM3X-JRHH-QCR7
Vulnerability from github – Published: 2025-11-13 22:58 – Updated: 2026-05-14 20:54Impact
Users who
1. use the exclusion operator somewhere in their authorization schema
1. have configured their SpiceDB server such that --write-relationships-max-updates-per-call is bigger than 6500
1. issue calls to WriteRelationships with a large enough number of updates that cause the payload to be bigger than what their datastore allows
will
- receive a successful response from their
WriteRelationshipscall, when in reality that call failed, - receive incorrect permission check results, if those relationships had to be read to resolve the relation involving the exclusion
Patches
Upgrade to v.145.2.
Workarounds
Set --write-relationships-max-updates-per-call to 1000.
{
"affected": [
{
"package": {
"ecosystem": "Go",
"name": "github.com/authzed/spicedb"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "1.45.2"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"aliases": [
"CVE-2025-64529"
],
"database_specific": {
"cwe_ids": [
"CWE-770"
],
"github_reviewed": true,
"github_reviewed_at": "2025-11-13T22:58:20Z",
"nvd_published_at": "2025-11-10T23:15:42Z",
"severity": "LOW"
},
"details": "### Impact\n\nUsers who \n1. use the exclusion operator somewhere in their authorization schema\n1. have configured their SpiceDB server such that `--write-relationships-max-updates-per-call` is bigger than 6500\n1. issue calls to WriteRelationships with a large enough number of updates that cause the payload to be bigger than what their datastore allows\n\nwill \n\n1. receive a successful response from their `WriteRelationships` call, when in reality that call failed,\n2. receive incorrect permission check results, if those relationships had to be read to resolve the relation involving the exclusion\n\n### Patches\n\nUpgrade to v.145.2.\n\n### Workarounds\n\nSet `--write-relationships-max-updates-per-call` to `1000`.",
"id": "GHSA-pm3x-jrhh-qcr7",
"modified": "2026-05-14T20:54:58Z",
"published": "2025-11-13T22:58:20Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/authzed/spicedb/security/advisories/GHSA-pm3x-jrhh-qcr7"
},
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2025-64529"
},
{
"type": "WEB",
"url": "https://github.com/authzed/spicedb/commit/d0cd103a92cc1915636733fb1d1730c2c7f74851"
},
{
"type": "PACKAGE",
"url": "https://github.com/authzed/spicedb"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:L/A:L",
"type": "CVSS_V3"
},
{
"score": "CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:N/VI:L/VA:L/SC:N/SI:N/SA:N/E:U",
"type": "CVSS_V4"
}
],
"summary": "SpiceDB WriteRelationships fails silently if payload is too big"
}
GHSA-PM6H-6RWH-XXG7
Vulnerability from github – Published: 2025-11-07 18:30 – Updated: 2025-11-14 21:30An allocation of resources without limits or throttling vulnerability has been reported to affect File Station 5. If a remote attacker gains a user account, they can then exploit the vulnerability to prevent other systems, applications, or processes from accessing the same type of resource.
We have already fixed the vulnerability in the following version: File Station 5 5.5.6.5018 and later
{
"affected": [],
"aliases": [
"CVE-2025-53413"
],
"database_specific": {
"cwe_ids": [
"CWE-770"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2025-11-07T16:15:39Z",
"severity": "MODERATE"
},
"details": "An allocation of resources without limits or throttling vulnerability has been reported to affect File Station 5. If a remote attacker gains a user account, they can then exploit the vulnerability to prevent other systems, applications, or processes from accessing the same type of resource.\n\nWe have already fixed the vulnerability in the following version:\nFile Station 5 5.5.6.5018 and later",
"id": "GHSA-pm6h-6rwh-xxg7",
"modified": "2025-11-14T21:30:28Z",
"published": "2025-11-07T18:30:29Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2025-53413"
},
{
"type": "WEB",
"url": "https://www.qnap.com/en/security-advisory/qsa-25-38"
}
],
"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:N/E:U/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-PMCC-WJFP-VCHV
Vulnerability from github – Published: 2026-08-11 03:31 – Updated: 2026-08-11 03:31SAP Approuter does not sufficiently handle certain requests under specific conditions. An unauthenticated attacker could send specially crafted input that causes the component to crash and restart. Successful exploitation requires specific runtime conditions to be met, making the attack complex to execute. This results in a high impact on availability. There is no impact on confidentiality and integrity.
{
"affected": [],
"aliases": [
"CVE-2026-58238"
],
"database_specific": {
"cwe_ids": [
"CWE-770"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2026-08-11T01:17:21Z",
"severity": "MODERATE"
},
"details": "SAP Approuter does not sufficiently handle certain requests under specific conditions. An unauthenticated attacker could send specially crafted input that causes the component to crash and restart. Successful exploitation requires specific runtime conditions to be met, making the attack complex to execute. This results in a high impact on availability. There is no impact on confidentiality and integrity.",
"id": "GHSA-pmcc-wjfp-vchv",
"modified": "2026-08-11T03:31:56Z",
"published": "2026-08-11T03:31:56Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-58238"
},
{
"type": "WEB",
"url": "https://me.sap.com/notes/3786038"
},
{
"type": "WEB",
"url": "https://url.sap/sapsecuritypatchday"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H",
"type": "CVSS_V3"
}
]
}
GHSA-PMPJ-JGH3-696Q
Vulnerability from github – Published: 2026-06-09 18:31 – Updated: 2026-06-16 18:32Unrestricted resource allocation in AMD uProf may be exploitable to consume excessive system resources, potentially leading to a loss of availability.
{
"affected": [],
"aliases": [
"CVE-2026-28237"
],
"database_specific": {
"cwe_ids": [
"CWE-770"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2026-06-09T18:16:37Z",
"severity": "MODERATE"
},
"details": "Unrestricted resource allocation in AMD uProf may be exploitable to consume excessive system resources, potentially leading to a loss of availability.",
"id": "GHSA-pmpj-jgh3-696q",
"modified": "2026-06-16T18:32:29Z",
"published": "2026-06-09T18:31:02Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-28237"
},
{
"type": "WEB",
"url": "https://www.amd.com/en/resources/product-security/bulletin/AMD-SB-9025.html"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H",
"type": "CVSS_V3"
},
{
"score": "CVSS:4.0/AV:L/AC:L/AT:N/PR:L/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-PMV8-RQ9R-6J72
Vulnerability from github – Published: 2026-07-20 17:48 – Updated: 2026-08-31 20:03Summary
Axios versions starting with 0.28.0 contain uncontrolled recursion in formDataToJSON, which is exposed as axios.formToJSON() and used internally when axios serialises FormData with Content-Type: application/json.
If an application passes attacker-controlled FormData field names to this functionality, a field name with thousands of nested bracket segments can exhaust the JavaScript call stack and cause denial of service for that request or, in applications without appropriate error handling, process termination.
Impact
Applications are affected only when untrusted users can control FormData key names that are converted through axios.
Affected paths include direct use of axios.formToJSON() on untrusted FormData and axios requests in which attacker-controlled FormData is sent with Content-Type: application/json.
The observed failure is RangeError: Maximum call stack size exceeded. In local testing, this error is catchable, so process-wide crash depends on the consuming application's error handling and runtime behaviour.
Affected Functionality
Affected functionality:
- axios.formToJSON(formData)
- Named ESM export formToJSON
- Default transformRequest behaviour for FormData when Content-Type contains application/json
Unaffected functionality:
- Normal multipart FormData submission without JSON serialisation
- toFormData, which already enforces a maxDepth guard
- Axios versions <=0.27.2, where formDataToJSON was not present
Technical Details
The vulnerable code is in lib/helpers/formDataToJSON.js.
parsePropPath() splits a field name such as a[x][x][x] into path segments. buildPath() then recursively processes one segment per call without enforcing a maximum depth:
const result = buildPath(path, value, target[name], index);
A key with thousands of bracket-delimited segments causes thousands of recursive calls and can exceed the JavaScript engine's call stack limit.
Relevant source locations:
- lib/helpers/formDataToJSON.js contains the unbounded recursive buildPath().
- lib/axios.js exposes the helper as axios.formToJSON.
- index.js exposes formToJSON as a named export.
- index.d.ts and index.d.cts declare the public API.
- lib/defaults/index.js calls formDataToJSON(data) when JSON-serializing FormData.
The inverse helper, toFormData, already enforces maxDepth and throws AxiosError with ERR_FORM_DATA_DEPTH_EXCEEDED, but formDataToJSON does not have an equivalent guard.
Proof of Concept of Attack
import axios from 'axios';
const fd = new FormData();
fd.append('a' + '[x]'.repeat(15000), 'value');
try {
axios.formToJSON(fd);
console.log('not vulnerable');
} catch (e) {
console.log(`${e.constructor.name}: ${e.message}`);
}
Expected result on affected versions:
RangeError: Maximum call stack size exceeded
The same condition can be reached via an axios request transformation when attacker-controlled FormData is sent with Content-Type: application/json.
Workarounds
Applications can reject or normalise untrusted form field names before calling axios.formToJSON().
Applications can avoid sending untrusted FormData through axios as JSON unless JSON conversion is required.
Applications should catch errors around formToJSON() or axios requests that transform untrusted FormData.
// lib/helpers/formDataToJSON.js, lines 50–82
function buildPath(path, value, target, index) {
let name = path[index++]; // advance one level
if (name === '__proto__') return true;
// ...
if (!isLast) {
// ...
const result = buildPath(path, value, target[name], index); // recurse — NO depth guard
// ...
}
}
import formDataToJSON from 'axios/lib/helpers/formDataToJSON.js';
// Build a FormData with a single key containing 15,000 nested bracket segments
const fd = new FormData();
const key = "a" + "[x]".repeat(15000);
fd.append(key, "value");
try {
formDataToJSON(fd);
console.log("Not vulnerable");
} catch (e) {
console.log(e.constructor.name + ": " + e.message);
// RangeError: Maximum call stack size exceeded
}
RangeError: Maximum call stack size exceeded
{
"affected": [
{
"package": {
"ecosystem": "npm",
"name": "axios"
},
"ranges": [
{
"events": [
{
"introduced": "0.28.0"
},
{
"fixed": "0.33.0"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "npm",
"name": "axios"
},
"ranges": [
{
"events": [
{
"introduced": "1.0.0"
},
{
"fixed": "1.18.0"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"aliases": [
"CVE-2026-67312"
],
"database_specific": {
"cwe_ids": [
"CWE-400",
"CWE-770"
],
"github_reviewed": true,
"github_reviewed_at": "2026-07-20T17:48:18Z",
"nvd_published_at": "2026-08-06T22:18:25Z",
"severity": "MODERATE"
},
"details": "## Summary\n\nAxios versions starting with `0.28.0` contain uncontrolled recursion in `formDataToJSON`, which is exposed as `axios.formToJSON()` and used internally when axios serialises `FormData` with `Content-Type: application/json`.\n\nIf an application passes attacker-controlled `FormData` field names to this functionality, a field name with thousands of nested bracket segments can exhaust the JavaScript call stack and cause denial of service for that request or, in applications without appropriate error handling, process termination.\n\n## Impact\n\nApplications are affected only when untrusted users can control `FormData` key names that are converted through axios.\n\nAffected paths include direct use of `axios.formToJSON()` on untrusted `FormData` and axios requests in which attacker-controlled `FormData` is sent with `Content-Type: application/json`.\n\nThe observed failure is `RangeError: Maximum call stack size exceeded`. In local testing, this error is catchable, so process-wide crash depends on the consuming application\u0027s error handling and runtime behaviour.\n\n## Affected Functionality\n\nAffected functionality:\n- `axios.formToJSON(formData)`\n- Named ESM export `formToJSON`\n- Default `transformRequest` behaviour for `FormData` when `Content-Type` contains `application/json`\n\nUnaffected functionality:\n- Normal multipart `FormData` submission without JSON serialisation\n- `toFormData`, which already enforces a `maxDepth` guard\n- Axios versions `\u003c=0.27.2`, where `formDataToJSON` was not present\n\n## Technical Details\n\nThe vulnerable code is in `lib/helpers/formDataToJSON.js`.\n\n`parsePropPath()` splits a field name such as `a[x][x][x]` into path segments. `buildPath()` then recursively processes one segment per call without enforcing a maximum depth:\n\n```js\nconst result = buildPath(path, value, target[name], index);\n```\n\nA key with thousands of bracket-delimited segments causes thousands of recursive calls and can exceed the JavaScript engine\u0027s call stack limit.\n\nRelevant source locations:\n- `lib/helpers/formDataToJSON.js` contains the unbounded recursive `buildPath()`.\n- `lib/axios.js` exposes the helper as `axios.formToJSON`.\n- `index.js` exposes `formToJSON` as a named export.\n- `index.d.ts` and `index.d.cts` declare the public API.\n- `lib/defaults/index.js` calls `formDataToJSON(data)` when JSON-serializing `FormData`.\n\nThe inverse helper, `toFormData`, already enforces `maxDepth` and throws `AxiosError` with `ERR_FORM_DATA_DEPTH_EXCEEDED`, but `formDataToJSON` does not have an equivalent guard.\n\n## Proof of Concept of Attack\n\n```js\nimport axios from \u0027axios\u0027;\n\nconst fd = new FormData();\nfd.append(\u0027a\u0027 + \u0027[x]\u0027.repeat(15000), \u0027value\u0027);\n\ntry {\n axios.formToJSON(fd);\n console.log(\u0027not vulnerable\u0027);\n} catch (e) {\n console.log(`${e.constructor.name}: ${e.message}`);\n}\n```\n\nExpected result on affected versions:\n\nRangeError: Maximum call stack size exceeded\n\nThe same condition can be reached via an axios request transformation when attacker-controlled `FormData` is sent with `Content-Type: application/json`.\n\n## Workarounds\nApplications can reject or normalise untrusted form field names before calling `axios.formToJSON()`.\n\nApplications can avoid sending untrusted `FormData` through axios as JSON unless JSON conversion is required.\n\nApplications should catch errors around `formToJSON()` or axios requests that transform untrusted `FormData`.\n\n\u003cdetails\u003e\n\u003csummary\u003eOriginal Source\u003c/summary\u003e\n\n### Summary\nAn uncontrolled recursion vulnerability in `formDataToJSON` allows any user who controls FormData input to crash a Node.js process with a single request. The function recurses once per bracket-delimited segment in a FormData key name with no depth limit, so a key like `a[x][x][x]...` with 15,000+ segments exhausts the call stack. This is a denial-of-service that kills the process via an unrecoverable `RangeError`. The inverse function `toFormData` already enforces a `maxDepth` limit (default 100) for exactly this reason \u2014 `formDataToJSON` lacks the equivalent guard.\n\n### Details\n**Vulnerable function:** `buildPath` in `lib/helpers/formDataToJSON.js`, lines 50\u201382.\n\n`buildPath(path, value, target, index)` is called recursively \u2014 once per segment in the parsed property path \u2014 with no depth check:\n\n```javascript\n// lib/helpers/formDataToJSON.js, lines 50\u201382\nfunction buildPath(path, value, target, index) {\n let name = path[index++]; // advance one level\n if (name === \u0027__proto__\u0027) return true;\n // ...\n if (!isLast) {\n // ...\n const result = buildPath(path, value, target[name], index); // recurse \u2014 NO depth guard\n // ...\n }\n}\n```\n\nThe key is first split into segments by `parsePropPath` (line 17), which extracts every `[segment]` via regex. A key with 15,000 bracket pairs produces a 15,001-element array, causing 15,001 recursive calls \u2014 well beyond the V8 default stack limit (~10,000\u201315,000 frames).\n\n**`formDataToJSON` is a public API** consumed two ways:\n\n1. **Directly by consumers** \u2014 exported as `axios.formToJSON()` (`lib/axios.js:80`), with TypeScript declarations in both `index.d.ts:699` and `index.d.cts:708`, and documented in the API reference in four languages (`docs/pages/advanced/api-reference.md`).\n\n2. **Internally by `transformRequest`** \u2014 called at `lib/defaults/index.js:56` when the request body is `FormData` and `Content-Type` contains `application/json`:\n ```javascript\n return hasJSONContentType ? JSON.stringify(formDataToJSON(data)) : data;\n ```\n\n**Contrast with `toFormData`:** The inverse function (`lib/helpers/toFormData.js:118`) enforces `maxDepth` (default 100) and throws `AxiosError` with code `ERR_FORM_DATA_DEPTH_EXCEEDED` when exceeded. `formDataToJSON` has no equivalent protection.\n\n### PoC\nRequires only Node.js and an unmodified axios v1.x install:\n\n```javascript\nimport formDataToJSON from \u0027axios/lib/helpers/formDataToJSON.js\u0027;\n\n// Build a FormData with a single key containing 15,000 nested bracket segments\nconst fd = new FormData();\nconst key = \"a\" + \"[x]\".repeat(15000);\nfd.append(key, \"value\");\n\ntry {\n formDataToJSON(fd);\n console.log(\"Not vulnerable\");\n} catch (e) {\n console.log(e.constructor.name + \": \" + e.message);\n // RangeError: Maximum call stack size exceeded\n}\n```\n\nVerified output on Node.js 22.22.3 against axios v1.16.1 (current `v1.x` HEAD):\n\n```\nRangeError: Maximum call stack size exceeded\n```\n\nThe process crashes. In a server context (e.g., Express middleware calling `axios.formToJSON()` on an uploaded form), a single crafted request terminates the process.\n\n### Impact\n**Denial of Service (process crash).** Any unauthenticated user who can submit FormData to a Node.js application that passes it through `axios.formToJSON()` \u2014 or that sends it as a JSON-serialized FormData body via axios \u2014 can crash the server process with a single request. The `RangeError` from stack exhaustion is unrecoverable in many contexts (it cannot be reliably caught when the stack is already full). No authentication or special privileges are required; the attacker only needs to control a FormData key name.\n\u003c/details\u003e",
"id": "GHSA-pmv8-rq9r-6j72",
"modified": "2026-08-31T20:03:15Z",
"published": "2026-07-20T17:48:18Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/axios/axios/security/advisories/GHSA-pmv8-rq9r-6j72"
},
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-67312"
},
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-68941"
},
{
"type": "WEB",
"url": "https://github.com/axios/axios/pull/11000"
},
{
"type": "WEB",
"url": "https://github.com/axios/axios/pull/11001"
},
{
"type": "WEB",
"url": "https://github.com/axios/axios/commit/1417285c69344bbcc6420a021f67dee0c6fedb2d"
},
{
"type": "WEB",
"url": "https://github.com/axios/axios/commit/32fc489632377d214db55bfa4e2c48486a7d7ce2"
},
{
"type": "PACKAGE",
"url": "https://github.com/axios/axios"
},
{
"type": "WEB",
"url": "https://github.com/axios/axios/releases/tag/v0.33.0"
},
{
"type": "WEB",
"url": "https://github.com/axios/axios/releases/tag/v1.18.0"
},
{
"type": "WEB",
"url": "https://www.vulncheck.com/advisories/axios-before-denial-of-service-via-formtojson"
}
],
"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": "Axios: Deep formToJSON Key Recursion Can Cause Denial of Service"
}
GHSA-PP5P-9G8Q-357J
Vulnerability from github – Published: 2022-05-13 01:14 – Updated: 2022-05-13 01:14A vulnerability in the network stack of Cisco NX-OS Software could allow an unauthenticated, remote attacker to cause a denial of service (DoS) condition on the affected device. The vulnerability is due to an issue with allocating and freeing memory buffers in the network stack. An attacker could exploit this vulnerability by sending crafted TCP streams to an affected device in a sustained way. A successful exploit could cause the network stack of an affected device to run out of available buffers, impairing operations of control plane and management plane protocols, resulting in a DoS condition. Note: This vulnerability can be triggered only by traffic that is destined to an affected device and cannot be exploited using traffic that transits an affected device. Nexus 1000V Switch for Microsoft Hyper-V is affected in versions prior to 5.2(1)SM3(2.1). Nexus 1000V Switch for VMware vSphere is affected in versions prior to 5.2(1)SV3(4.1a). Nexus 3000 Series Switches are affected in versions prior to 7.0(3)I7(6) and 9.2(2). Nexus 3500 Platform Switches are affected in versions prior to 6.0(2)A8(11), 7.0(3)I7(6), and 9.2(2). Nexus 3600 Platform Switches are affected in versions prior to 7.0(3)F3(5) and 9.2(2). Nexus 5500, 5600, and 6000 Series Switches are affected in versions prior to 7.1(5)N1(1b) and 7.3(5)N1(1). Nexus 7000 and 7700 Series Switches are affected in versions prior to 6.2(22. Nexus 9500 R-Series Line Cards and Fabric Modules are affected in versions prior to 7.0(3)F3(5) and 9.2(2). UCS 6200 and 6300 Series Fabric Interconnect are affected in versions prior to 3.2(3j) and 4.0(2a). UCS 6400 Series Fabric Interconnect are affected in versions prior to 4.0(2a).
{
"affected": [],
"aliases": [
"CVE-2019-1599"
],
"database_specific": {
"cwe_ids": [
"CWE-770"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2019-03-07T20:29:00Z",
"severity": "HIGH"
},
"details": "A vulnerability in the network stack of Cisco NX-OS Software could allow an unauthenticated, remote attacker to cause a denial of service (DoS) condition on the affected device. The vulnerability is due to an issue with allocating and freeing memory buffers in the network stack. An attacker could exploit this vulnerability by sending crafted TCP streams to an affected device in a sustained way. A successful exploit could cause the network stack of an affected device to run out of available buffers, impairing operations of control plane and management plane protocols, resulting in a DoS condition. Note: This vulnerability can be triggered only by traffic that is destined to an affected device and cannot be exploited using traffic that transits an affected device. Nexus 1000V Switch for Microsoft Hyper-V is affected in versions prior to 5.2(1)SM3(2.1). Nexus 1000V Switch for VMware vSphere is affected in versions prior to 5.2(1)SV3(4.1a). Nexus 3000 Series Switches are affected in versions prior to 7.0(3)I7(6) and 9.2(2). Nexus 3500 Platform Switches are affected in versions prior to 6.0(2)A8(11), 7.0(3)I7(6), and 9.2(2). Nexus 3600 Platform Switches are affected in versions prior to 7.0(3)F3(5) and 9.2(2). Nexus 5500, 5600, and 6000 Series Switches are affected in versions prior to 7.1(5)N1(1b) and 7.3(5)N1(1). Nexus 7000 and 7700 Series Switches are affected in versions prior to 6.2(22. Nexus 9500 R-Series Line Cards and Fabric Modules are affected in versions prior to 7.0(3)F3(5) and 9.2(2). UCS 6200 and 6300 Series Fabric Interconnect are affected in versions prior to 3.2(3j) and 4.0(2a). UCS 6400 Series Fabric Interconnect are affected in versions prior to 4.0(2a).",
"id": "GHSA-pp5p-9g8q-357j",
"modified": "2022-05-13T01:14:49Z",
"published": "2022-05-13T01:14:49Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2019-1599"
},
{
"type": "WEB",
"url": "https://tools.cisco.com/security/center/content/CiscoSecurityAdvisory/cisco-sa-20190306-nxos-netstack"
},
{
"type": "WEB",
"url": "http://www.securityfocus.com/bid/107342"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:C/C:N/I:N/A:H",
"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.