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.
3619 vulnerabilities reference this CWE, most recent first.
GHSA-3F74-CM4W-65C4
Vulnerability from github – Published: 2026-05-13 18:30 – Updated: 2026-05-13 18:30When a SIP profile is configured on a virtual server, undisclosed traffic can cause the Traffic Management Microkernel (TMM) to terminate.
Note: Software versions which have reached End of Technical Support (EoTS) are not evaluated.
{
"affected": [],
"aliases": [
"CVE-2026-40423"
],
"database_specific": {
"cwe_ids": [
"CWE-770"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2026-05-13T16:16:42Z",
"severity": "HIGH"
},
"details": "When a SIP profile is configured on a virtual server, undisclosed traffic can cause the Traffic Management Microkernel (TMM) to terminate.\n\n\u00a0Note: Software versions which have reached End of Technical Support (EoTS) are not evaluated.",
"id": "GHSA-3f74-cm4w-65c4",
"modified": "2026-05-13T18:30:55Z",
"published": "2026-05-13T18:30:55Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-40423"
},
{
"type": "WEB",
"url": "https://my.f5.com/manage/s/article/K000161023"
}
],
"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"
},
{
"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-3FHQ-72HW-JQWV
Vulnerability from github – Published: 2022-10-01 00:00 – Updated: 2024-10-25 21:39rdiffweb prior to 2.5.0a3 is vulnerable to Allocation of Resources Without Limits or Throttling. A lack of limit in the length of the Token name parameter can result in denial of service or memory corruption. Version 2.5.0a3 fixes this issue.
{
"affected": [
{
"package": {
"ecosystem": "PyPI",
"name": "rdiffweb"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "2.5.0a3"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"aliases": [
"CVE-2022-3371"
],
"database_specific": {
"cwe_ids": [
"CWE-770"
],
"github_reviewed": true,
"github_reviewed_at": "2022-10-03T22:19:03Z",
"nvd_published_at": "2022-09-30T14:15:00Z",
"severity": "HIGH"
},
"details": "rdiffweb prior to 2.5.0a3 is vulnerable to Allocation of Resources Without Limits or Throttling. A lack of limit in the length of the `Token name` parameter can result in denial of service or memory corruption. Version 2.5.0a3 fixes this issue.",
"id": "GHSA-3fhq-72hw-jqwv",
"modified": "2024-10-25T21:39:31Z",
"published": "2022-10-01T00:00:21Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2022-3371"
},
{
"type": "WEB",
"url": "https://github.com/ikus060/rdiffweb/commit/b62c479ff6979563c7c23e7182942bc4f460a2c7"
},
{
"type": "PACKAGE",
"url": "https://github.com/ikus060/rdiffweb"
},
{
"type": "WEB",
"url": "https://github.com/pypa/advisory-database/tree/main/vulns/rdiffweb/PYSEC-2022-299.yaml"
},
{
"type": "WEB",
"url": "https://huntr.dev/bounties/4e8f6136-50c7-4fa1-ac98-699bcb7b35ce"
}
],
"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"
},
{
"score": "CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N",
"type": "CVSS_V4"
}
],
"summary": "rdiffweb\u0027s lack of token name length limit can result in DoS or memory corruption"
}
GHSA-3FP5-98PF-7937
Vulnerability from github – Published: 2022-08-06 00:00 – Updated: 2022-08-12 00:01The Uniwill SparkIO.sys driver 1.0 is vulnerable to a stack-based buffer overflow via IOCTL 0x40002008.
{
"affected": [],
"aliases": [
"CVE-2022-37415"
],
"database_specific": {
"cwe_ids": [
"CWE-770"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2022-08-05T04:15:00Z",
"severity": "HIGH"
},
"details": "The Uniwill SparkIO.sys driver 1.0 is vulnerable to a stack-based buffer overflow via IOCTL 0x40002008.",
"id": "GHSA-3fp5-98pf-7937",
"modified": "2022-08-12T00:01:19Z",
"published": "2022-08-06T00:00:51Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2022-37415"
},
{
"type": "WEB",
"url": "https://gist.github.com/alfarom256/220cb75816ca2b5556e7fc8d8d2803a0"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H",
"type": "CVSS_V3"
}
]
}
GHSA-3FQ3-9257-PPM7
Vulnerability from github – Published: 2026-08-13 21:36 – Updated: 2026-08-13 21:36Allocation of Resources Without Limits or Throttling (CWE-770) in Kibana can lead to denial of service via Excessive Allocation (CAPEC-130). An authenticated user with read-only privileges to the alerting feature could submit a specially crafted, malformed payload that causes the Kibana process to consume excessive resources. A single request is sufficient to leave Kibana unable to serve requests for all users until the process is restarted.
{
"affected": [],
"aliases": [
"CVE-2026-72651"
],
"database_specific": {
"cwe_ids": [
"CWE-770"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2026-08-13T20:17:25Z",
"severity": "MODERATE"
},
"details": "Allocation of Resources Without Limits or Throttling (CWE-770) in Kibana can lead to denial of service via Excessive Allocation (CAPEC-130). An authenticated user with read-only privileges to the alerting feature could submit a specially crafted, malformed payload that causes the Kibana process to consume excessive resources. A single request is sufficient to leave Kibana unable to serve requests for all users until the process is restarted.",
"id": "GHSA-3fq3-9257-ppm7",
"modified": "2026-08-13T21:36:08Z",
"published": "2026-08-13T21:36:08Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-72651"
},
{
"type": "WEB",
"url": "https://discuss.elastic.co/t/kibana-8-19-20-9-4-5-security-update-esa-2026-106/389522"
}
],
"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"
}
]
}
GHSA-3FVR-2JW6-CRQ4
Vulnerability from github – Published: 2026-08-01 15:30 – Updated: 2026-08-04 12:58Duplicate Advisory
This advisory has been withdrawn because it is a duplicate of GHSA-f283-ghqc-fg79. This link is maintained to preserve external references.
Original Description
guzzlehttp/guzzle versions before 7.15.1 contain a denial of service vulnerability in the CookieJar that accepts unlimited Set-Cookie header fields with no size restrictions. Attackers can return many large cookies from a malicious server, causing Guzzle to store excessive data in memory and generate oversized Cookie headers that fail in handlers or destination servers.
{
"affected": [
{
"database_specific": {
"last_known_affected_version_range": "\u003c 7.15.1"
},
"package": {
"ecosystem": "Packagist",
"name": "guzzlehttp/guzzle"
},
"ranges": [
{
"events": [
{
"introduced": "0"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"aliases": [],
"database_specific": {
"cwe_ids": [
"CWE-770"
],
"github_reviewed": true,
"github_reviewed_at": "2026-08-04T12:58:31Z",
"nvd_published_at": "2026-08-01T13:17:06Z",
"severity": "MODERATE"
},
"details": "## Duplicate Advisory\n\nThis advisory has been withdrawn because it is a duplicate of\u00a0GHSA-f283-ghqc-fg79. This link is maintained to preserve external references.\n\n## Original Description\nguzzlehttp/guzzle versions before 7.15.1 contain a denial of service vulnerability in the CookieJar that accepts unlimited Set-Cookie header fields with no size restrictions. Attackers can return many large cookies from a malicious server, causing Guzzle to store excessive data in memory and generate oversized Cookie headers that fail in handlers or destination servers.",
"id": "GHSA-3fvr-2jw6-crq4",
"modified": "2026-08-04T12:58:32Z",
"published": "2026-08-01T15:30:30Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/guzzle/guzzle/security/advisories/GHSA-f283-ghqc-fg79"
},
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-67353"
},
{
"type": "WEB",
"url": "https://www.vulncheck.com/advisories/guzzlehttp-guzzle-before-unbounded-cookie-denial-of-service"
}
],
"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:L",
"type": "CVSS_V3"
},
{
"score": "CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:N/VI:N/VA:L/SC:N/SI:N/SA:N/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"
}
],
"summary": "Duplicate Advisory: Guzzle: Unbounded response cookies risk denial of service",
"withdrawn": "2026-08-04T12:58:31Z"
}
GHSA-3G76-F9XQ-8VP6
Vulnerability from github – Published: 2026-05-09 00:38 – Updated: 2026-06-02 22:07Potential unbounded server-side SNI SslContext cache growth in Vert.x TLS handling, with = resource-exhaustion / DoS impact. On affected versions, matching server-side SNI names are cached via computeIfAbsent(serverName, ...) in a serverName-keyed SslContext cache.
The implementation differs slightly by branch, but the same sink appears to be present in released versions 4.3.4 through 5.0.11:
- 4.3.x: SSLHelper
- 4.4.x / 4.5.x: SslChannelProvider
- 5.0.x and current master: SslContextProvider
When server-side SNI is enabled and wildcard or otherwise broad hostname mappings are used, an unauthenticated client can send many distinct matching SNI names and cause the server to retain increasing numbers of SslContext entries over time, leading to increasing memory consumption and possible DoS conditions.
Steps to reproduce
- Configure a Vert.x server with
setSsl(true)andsetSni(true). - Use a keystore or mapping where many distinct SNI names match a wildcard or similarly broad rule.
- Send repeated connections with distinct matching SNI values.
- Observe that the SNI cache size grows with the number of unique matching names.
What are the affected versions?
Affected released versions confirmed on origin:
- 4.3.4 through 4.3.8
- 4.4.0 through 4.4.9
- 4.5.0 through 4.5.26
- 5.0.0 through 5.0.11
Not affected by the same sink:
- 4.0.x through 4.2.x
- 4.3.0 through 4.3.3
{
"affected": [
{
"package": {
"ecosystem": "Maven",
"name": "io.vertx:vertx-core"
},
"ranges": [
{
"events": [
{
"introduced": "4.3.4"
},
{
"last_affected": "4.3.8"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "Maven",
"name": "io.vertx:vertx-core"
},
"ranges": [
{
"events": [
{
"introduced": "4.4.0"
},
{
"last_affected": "4.4.9"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"database_specific": {
"last_known_affected_version_range": "\u003c= 4.5.26"
},
"package": {
"ecosystem": "Maven",
"name": "io.vertx:vertx-core"
},
"ranges": [
{
"events": [
{
"introduced": "4.5.0"
},
{
"fixed": "4.5.27"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"database_specific": {
"last_known_affected_version_range": "\u003c= 5.0.11"
},
"package": {
"ecosystem": "Maven",
"name": "io.vertx:vertx-core"
},
"ranges": [
{
"events": [
{
"introduced": "5.0.0"
},
{
"fixed": "5.0.12"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"aliases": [
"CVE-2026-6860"
],
"database_specific": {
"cwe_ids": [
"CWE-295",
"CWE-770"
],
"github_reviewed": true,
"github_reviewed_at": "2026-05-09T00:38:30Z",
"nvd_published_at": "2026-05-06T10:16:26Z",
"severity": "MODERATE"
},
"details": "Potential unbounded server-side SNI `SslContext` cache growth in Vert.x TLS handling, with = resource-exhaustion / DoS impact. On affected versions, matching server-side SNI names are cached via `computeIfAbsent(serverName, ...)` in a serverName-keyed `SslContext` cache.\n\nThe implementation differs slightly by branch, but the same sink appears to be present in released versions `4.3.4` through `5.0.11`:\n- `4.3.x`: `SSLHelper`\n- `4.4.x` / `4.5.x`: `SslChannelProvider`\n- `5.0.x` and current `master`: `SslContextProvider`\n\nWhen server-side SNI is enabled and wildcard or otherwise broad hostname mappings are used, an unauthenticated client can send many distinct matching SNI names and cause the server to retain increasing numbers of `SslContext` entries over time, leading to increasing memory consumption and possible DoS conditions.\n\n## Steps to reproduce\n\n1. Configure a Vert.x server with `setSsl(true)` and `setSni(true)`.\n2. Use a keystore or mapping where many distinct SNI names match a wildcard or similarly broad rule.\n3. Send repeated connections with distinct matching SNI values.\n4. Observe that the SNI cache size grows with the number of unique matching names.\n\n## What are the affected versions?\n\nAffected released versions confirmed on `origin`:\n- `4.3.4` through `4.3.8`\n- `4.4.0` through `4.4.9`\n- `4.5.0` through `4.5.26`\n- `5.0.0` through `5.0.11`\n\nNot affected by the same sink:\n- `4.0.x` through `4.2.x`\n- `4.3.0` through `4.3.3`",
"id": "GHSA-3g76-f9xq-8vp6",
"modified": "2026-06-02T22:07:06Z",
"published": "2026-05-09T00:38:30Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/eclipse-vertx/vert.x/security/advisories/GHSA-3g76-f9xq-8vp6"
},
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-6860"
},
{
"type": "WEB",
"url": "https://github.com/eclipse-vertx/vert.x/pull/6102"
},
{
"type": "PACKAGE",
"url": "https://github.com/eclipse-vertx/vert.x"
},
{
"type": "WEB",
"url": "https://github.com/vert-x3/wiki/wiki/4.5.27-Release-Notes"
},
{
"type": "WEB",
"url": "https://gitlab.eclipse.org/security/vulnerability-reports/-/issues/381"
},
{
"type": "WEB",
"url": "https://vertx.io/blog/eclipse-vert-x-4-5-27"
},
{
"type": "WEB",
"url": "https://vertx.io/blog/eclipse-vert-x-5-0-12"
}
],
"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:L",
"type": "CVSS_V3"
},
{
"score": "CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:N/VI:N/VA:L/SC:N/SI:N/SA:L",
"type": "CVSS_V4"
}
],
"summary": "Vert.x has a DoS via unbounded server-side SNI SslContext cache growth"
}
GHSA-3G7C-253J-WHP9
Vulnerability from github – Published: 2022-05-24 17:37 – Updated: 2022-05-24 17:37An attacker-controlled memory allocation size can be passed to the C++ new operator in the CServerManager::HandleBrowseLoadIconStreamRequest in messaging.dll. This can be done by sending a specially crafted message to 127.0.0.1:7153. Observed in FactoryTalk Linx 6.11. All versions of FactoryTalk Linx are affected.
{
"affected": [],
"aliases": [
"CVE-2020-5806"
],
"database_specific": {
"cwe_ids": [
"CWE-770"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2020-12-29T16:15:00Z",
"severity": "MODERATE"
},
"details": "An attacker-controlled memory allocation size can be passed to the C++ new operator in the CServerManager::HandleBrowseLoadIconStreamRequest in messaging.dll. This can be done by sending a specially crafted message to 127.0.0.1:7153. Observed in FactoryTalk Linx 6.11. All versions of FactoryTalk Linx are affected.",
"id": "GHSA-3g7c-253j-whp9",
"modified": "2022-05-24T17:37:29Z",
"published": "2022-05-24T17:37:29Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2020-5806"
},
{
"type": "WEB",
"url": "https://www.tenable.com/security/research/tra-2020-71"
}
],
"schema_version": "1.4.0",
"severity": []
}
GHSA-3G96-V3MG-9XP9
Vulnerability from github – Published: 2026-02-25 15:31 – Updated: 2026-02-25 15:31USB HID protocol dissector memory exhaustion in Wireshark 4.6.0 to 4.6.3 and 4.4.0 to 4.4.13 allows denial of service
{
"affected": [],
"aliases": [
"CVE-2026-3201"
],
"database_specific": {
"cwe_ids": [
"CWE-1325",
"CWE-770"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2026-02-25T15:20:55Z",
"severity": "MODERATE"
},
"details": "USB HID protocol dissector memory exhaustion in Wireshark 4.6.0 to 4.6.3 and 4.4.0 to 4.4.13 allows denial of service",
"id": "GHSA-3g96-v3mg-9xp9",
"modified": "2026-02-25T15:31:43Z",
"published": "2026-02-25T15:31:43Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-3201"
},
{
"type": "WEB",
"url": "https://gitlab.com/wireshark/wireshark/-/issues/20972"
},
{
"type": "WEB",
"url": "https://www.wireshark.org/security/wnpa-sec-2026-05.html"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:L/AC:H/PR:N/UI:R/S:U/C:N/I:N/A:H",
"type": "CVSS_V3"
}
]
}
GHSA-3G9Q-V48F-HH9W
Vulnerability from github – Published: 2026-09-10 22:44 – Updated: 2026-09-10 22:44Summary
The OIDC back-channel logout endpoint is unauthenticated by design, because the identity provider calls it without a browser session. Before checking whether the submitted logout token was genuine, the handler fetched the provider's discovery document and its signing keys over the network, and repeated both fetches on every request because nothing was cached. The signing-key fetch also ran as a blocking call inside the async event loop. A small number of requests carrying a worthless token was therefore enough to make the whole instance stop answering.
Preconditions
ENABLE_OAUTH_BACKCHANNEL_LOGOUT=true. The default isFalse, so a stock deployment is not affected. This setting is recommended in the Open WebUI hardening documentation, which is why the issue is treated as in scope.- At least one OIDC provider configured (
OAUTH_CLIENT_ID,OAUTH_CLIENT_SECRET,OPENID_PROVIDER_URL). - No account, credential, session or secret identifier is required. The attacker needs network access to the instance and the configured issuer string, which is published in the provider's own discovery document.
Impact
Against 0.11.0, with the identity provider answering in 150 ms, 60 concurrent requests carrying a token whose signature was four characters long stalled the async event loop for 8.3 seconds, measured against an idle baseline of 10.8 ms. For the length of that stall the process answers nothing: no chat requests, no API calls, no health check. Open WebUI runs a single worker by default, so the effect is instance-wide rather than per-connection, and no rate limit sits in front of the endpoint.
The same traffic is also amplified outward: 20 sequential requests produced 20 discovery fetches and 40 key-set fetches at the identity provider, so an attacker can drive load onto the provider through the instance.
No data is read, modified or exposed, and the forged token is still rejected. The cost is paid before the rejection.
Fix
Fixed in 0.11.1. The handler now resolves both the discovery document and the signing keys through the already-configured OAuth client, so each is fetched once per provider and reused afterwards, and both fetches are asynchronous rather than blocking the event loop. A token carrying no kid header is rejected before any key lookup happens. Upgrading is sufficient, and no configuration change is required.
Root cause
Affected component: the OIDC back-channel logout handler in backend/open_webui/utils/oauth.py, reached through POST /oauth/backchannel-logout. Affected setups: releases 0.9.0 through 0.11.0 with back-channel logout enabled and an OIDC provider configured.
The handler treated its network work as cheap preparation rather than as work worth protecting. For every request it opened a new HTTP session per configured provider to re-read the discovery document, then constructed a fresh JWKS client, whose own cache consequently started empty each time, and asked that client for the signing key through a synchronous call issued directly on the event loop. All of this ran before the token signature was verified, so an attacker unable to produce a valid token still cost the server two network round trips and a blocked loop per request. Both fetches used the library default timeout of five minutes.
Proof of concept
Reproduced by running the unmodified handler from the 0.11.0 and 0.11.1 backends against a loopback identity provider that counted every inbound request and could answer with a configured delay. The submitted token carried a valid issuer and audience, a kid naming a key the provider does not hold, and AAAA as its signature.
20 sequential requests, provider answering immediately:
| Version | Discovery fetches | Key-set fetches | Response |
|---|---|---|---|
| 0.11.0 | 20 | 40 | 400 |
| 0.11.1 | 1 | 1 | 400 |
60 concurrent requests, provider answering in 150 ms:
| Version | Wall time | Discovery fetches | Key-set fetches | Worst event-loop stall |
|---|---|---|---|---|
| 0.11.0 | 18.6 s | 60 | 120 | 8255 ms |
| 0.11.1 | under 0.01 s | 0 | 0 | none measurable |
Idle event-loop stall was 10.8 ms in both cases. On 0.11.1 the first request an instance receives warms both caches, and every request after that reaches the signature check without any outbound network call.
Credits
@galanko, for reporting the issue and identifying both the missing caching and the blocking call.
{
"affected": [
{
"database_specific": {
"last_known_affected_version_range": "\u003c= 0.11.0"
},
"package": {
"ecosystem": "PyPI",
"name": "open-webui"
},
"ranges": [
{
"events": [
{
"introduced": "0.9.0"
},
{
"fixed": "0.11.1"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"aliases": [
"CVE-2026-87011"
],
"database_specific": {
"cwe_ids": [
"CWE-405",
"CWE-770"
],
"github_reviewed": true,
"github_reviewed_at": "2026-09-10T22:44:42Z",
"nvd_published_at": "2026-09-09T21:17:05Z",
"severity": "HIGH"
},
"details": "## Summary\n\nThe OIDC back-channel logout endpoint is unauthenticated by design, because the identity provider calls it without a browser session. Before checking whether the submitted logout token was genuine, the handler fetched the provider\u0027s discovery document and its signing keys over the network, and repeated both fetches on every request because nothing was cached. The signing-key fetch also ran as a blocking call inside the async event loop. A small number of requests carrying a worthless token was therefore enough to make the whole instance stop answering.\n\n## Preconditions\n\n- `ENABLE_OAUTH_BACKCHANNEL_LOGOUT=true`. The default is `False`, so a stock deployment is not affected. This setting is recommended in the Open WebUI hardening documentation, which is why the issue is treated as in scope.\n- At least one OIDC provider configured (`OAUTH_CLIENT_ID`, `OAUTH_CLIENT_SECRET`, `OPENID_PROVIDER_URL`).\n- No account, credential, session or secret identifier is required. The attacker needs network access to the instance and the configured issuer string, which is published in the provider\u0027s own discovery document.\n\n## Impact\n\nAgainst 0.11.0, with the identity provider answering in 150 ms, 60 concurrent requests carrying a token whose signature was four characters long stalled the async event loop for 8.3 seconds, measured against an idle baseline of 10.8 ms. For the length of that stall the process answers nothing: no chat requests, no API calls, no health check. Open WebUI runs a single worker by default, so the effect is instance-wide rather than per-connection, and no rate limit sits in front of the endpoint.\n\nThe same traffic is also amplified outward: 20 sequential requests produced 20 discovery fetches and 40 key-set fetches at the identity provider, so an attacker can drive load onto the provider through the instance.\n\nNo data is read, modified or exposed, and the forged token is still rejected. The cost is paid before the rejection.\n\n## Fix\n\nFixed in 0.11.1. The handler now resolves both the discovery document and the signing keys through the already-configured OAuth client, so each is fetched once per provider and reused afterwards, and both fetches are asynchronous rather than blocking the event loop. A token carrying no `kid` header is rejected before any key lookup happens. Upgrading is sufficient, and no configuration change is required.\n\n## Root cause\n\nAffected component: the OIDC back-channel logout handler in `backend/open_webui/utils/oauth.py`, reached through `POST /oauth/backchannel-logout`. Affected setups: releases 0.9.0 through 0.11.0 with back-channel logout enabled and an OIDC provider configured.\n\nThe handler treated its network work as cheap preparation rather than as work worth protecting. For every request it opened a new HTTP session per configured provider to re-read the discovery document, then constructed a fresh JWKS client, whose own cache consequently started empty each time, and asked that client for the signing key through a synchronous call issued directly on the event loop. All of this ran before the token signature was verified, so an attacker unable to produce a valid token still cost the server two network round trips and a blocked loop per request. Both fetches used the library default timeout of five minutes.\n\n## Proof of concept\n\nReproduced by running the unmodified handler from the 0.11.0 and 0.11.1 backends against a loopback identity provider that counted every inbound request and could answer with a configured delay. The submitted token carried a valid issuer and audience, a `kid` naming a key the provider does not hold, and `AAAA` as its signature.\n\n20 sequential requests, provider answering immediately:\n\n| Version | Discovery fetches | Key-set fetches | Response |\n| --- | --- | --- | --- |\n| 0.11.0 | 20 | 40 | 400 |\n| 0.11.1 | 1 | 1 | 400 |\n\n60 concurrent requests, provider answering in 150 ms:\n\n| Version | Wall time | Discovery fetches | Key-set fetches | Worst event-loop stall |\n| --- | --- | --- | --- | --- |\n| 0.11.0 | 18.6 s | 60 | 120 | 8255 ms |\n| 0.11.1 | under 0.01 s | 0 | 0 | none measurable |\n\nIdle event-loop stall was 10.8 ms in both cases. On 0.11.1 the first request an instance receives warms both caches, and every request after that reaches the signature check without any outbound network call.\n\n## Credits\n\n@galanko, for reporting the issue and identifying both the missing caching and the blocking call.",
"id": "GHSA-3g9q-v48f-hh9w",
"modified": "2026-09-10T22:44:42Z",
"published": "2026-09-10T22:44:42Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/open-webui/open-webui/security/advisories/GHSA-3g9q-v48f-hh9w"
},
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-87011"
},
{
"type": "WEB",
"url": "https://github.com/open-webui/open-webui/commit/aeda6ff13a25d3b3ba1b303609f35382db22142c"
},
{
"type": "PACKAGE",
"url": "https://github.com/open-webui/open-webui"
},
{
"type": "WEB",
"url": "https://github.com/open-webui/open-webui/releases/tag/v0.11.1"
}
],
"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": "Open WebUI: Unauthenticated requests can stall the server via uncached OIDC fetches in back-channel logout"
}
GHSA-3GFG-2V89-C3PM
Vulnerability from github – Published: 2025-02-18 18:33 – Updated: 2025-02-18 21:32Restricted Views backed objects (OSV1) could be bypassed under specific circumstances due to a software bug, this could have allowed users that didn't have permission to see such objects to view them via Object Explorer directly. This software bug did not impact or otherwise make data available across organizational boundaries nor did it allow for data to be viewed or accessed by unauthenticated users.
The affected service have been patched and automatically deployed to all Apollo-managed Foundry instances.
{
"affected": [],
"aliases": [
"CVE-2024-49589"
],
"database_specific": {
"cwe_ids": [
"CWE-770",
"CWE-862"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2025-02-18T18:15:25Z",
"severity": "MODERATE"
},
"details": "Restricted Views backed objects (OSV1) could be bypassed under specific circumstances due to a software bug, this could have allowed users that didn\u0027t have permission to see such objects to view them via Object Explorer directly. This software bug did not impact or otherwise make data available across organizational boundaries nor did it allow for data to be viewed or accessed by unauthenticated users. \nThe affected service have been patched and automatically deployed to all Apollo-managed Foundry instances.",
"id": "GHSA-3gfg-2v89-c3pm",
"modified": "2025-02-18T21:32:50Z",
"published": "2025-02-18T18:33:21Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2024-49589"
},
{
"type": "WEB",
"url": "https://palantir.safebase.us/?tcuUid=ad6b08b1-2f79-4e32-b125-406dd2b9b1c3"
},
{
"type": "WEB",
"url": "https://palantir.safebase.us/?tcuUid=b60db1ee-4b1a-475d-848e-c5a670a0da16"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:N",
"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.