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.
3039 vulnerabilities reference this CWE, most recent first.
GHSA-3738-JVGH-JH3H
Vulnerability from github – Published: 2026-05-08 00:31 – Updated: 2026-05-11 18:31A denial of service vulnerability was identified in GitHub Enterprise Server that allowed an unauthenticated attacker to cause service disruption by sending crafted requests with deeply nested JSON payloads to an unauthenticated API endpoint. The endpoint parsed user-controlled JSON request bodies without size or depth limits, causing excessive CPU and memory consumption. This vulnerability affected all versions of GitHub Enterprise Server prior to 3.21 and was fixed in versions 3.20.2, 3.19.6, 3.18.9, 3.17.15, and 3.16.18. This vulnerability was reported via the GitHub Bug Bounty program.
{
"affected": [],
"aliases": [
"CVE-2026-7541"
],
"database_specific": {
"cwe_ids": [
"CWE-770"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2026-05-07T22:16:36Z",
"severity": "MODERATE"
},
"details": "A denial of service vulnerability was identified in GitHub Enterprise Server that allowed an unauthenticated attacker to cause service disruption by sending crafted requests with deeply nested JSON payloads to an unauthenticated API endpoint. The endpoint parsed user-controlled JSON request bodies without size or depth limits, causing excessive CPU and memory consumption. This vulnerability affected all versions of GitHub Enterprise Server prior to 3.21 and was fixed in versions 3.20.2, 3.19.6, 3.18.9, 3.17.15, and 3.16.18. This vulnerability was reported via the GitHub Bug Bounty program.",
"id": "GHSA-3738-jvgh-jh3h",
"modified": "2026-05-11T18:31:36Z",
"published": "2026-05-08T00:31:34Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-7541"
},
{
"type": "WEB",
"url": "https://docs.github.com/en/enterprise-server@3.16/admin/release-notes#3.16.18"
},
{
"type": "WEB",
"url": "https://docs.github.com/en/enterprise-server@3.17/admin/release-notes#3.17.15"
},
{
"type": "WEB",
"url": "https://docs.github.com/en/enterprise-server@3.18/admin/release-notes#3.18.9"
},
{
"type": "WEB",
"url": "https://docs.github.com/en/enterprise-server@3.19/admin/release-notes#3.19.6"
},
{
"type": "WEB",
"url": "https://docs.github.com/en/enterprise-server@3.20/admin/release-notes#3.20.2"
}
],
"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:P/PR:N/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:H/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-376J-8F52-GP2X
Vulnerability from github – Published: 2026-04-21 21:31 – Updated: 2026-04-21 21:31Vulnerability in the Oracle Java SE, Oracle GraalVM for JDK, Oracle GraalVM Enterprise Edition product of Oracle Java SE (component: Libraries). Supported versions that are affected are Oracle Java SE: 8u481, 8u481-b50, 8u481-perf, 11.0.30, 17.0.18, 21.0.10, 25.0.2, 26; Oracle GraalVM for JDK: 17.0.18 and 21.0.10; Oracle GraalVM Enterprise Edition: 21.3.17. Difficult to exploit vulnerability allows unauthenticated attacker with network access via multiple protocols to compromise Oracle Java SE, Oracle GraalVM for JDK, Oracle GraalVM Enterprise Edition. Successful attacks of this vulnerability can result in unauthorized ability to cause a partial denial of service (partial DOS) of Oracle Java SE, Oracle GraalVM for JDK, Oracle GraalVM Enterprise Edition. Note: This vulnerability can be exploited by using APIs in the specified Component, e.g., through a web service which supplies data to the APIs. This vulnerability also applies to Java deployments, typically in clients running sandboxed Java Web Start applications or sandboxed Java applets, that load and run untrusted code (e.g., code that comes from the internet) and rely on the Java sandbox for security. CVSS 3.1 Base Score 3.7 (Availability impacts). CVSS Vector: (CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:L).
{
"affected": [],
"aliases": [
"CVE-2026-22018"
],
"database_specific": {
"cwe_ids": [
"CWE-770"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2026-04-21T21:16:28Z",
"severity": "LOW"
},
"details": "Vulnerability in the Oracle Java SE, Oracle GraalVM for JDK, Oracle GraalVM Enterprise Edition product of Oracle Java SE (component: Libraries). Supported versions that are affected are Oracle Java SE: 8u481, 8u481-b50, 8u481-perf, 11.0.30, 17.0.18, 21.0.10, 25.0.2, 26; Oracle GraalVM for JDK: 17.0.18 and 21.0.10; Oracle GraalVM Enterprise Edition: 21.3.17. Difficult to exploit vulnerability allows unauthenticated attacker with network access via multiple protocols to compromise Oracle Java SE, Oracle GraalVM for JDK, Oracle GraalVM Enterprise Edition. Successful attacks of this vulnerability can result in unauthorized ability to cause a partial denial of service (partial DOS) of Oracle Java SE, Oracle GraalVM for JDK, Oracle GraalVM Enterprise Edition. Note: This vulnerability can be exploited by using APIs in the specified Component, e.g., through a web service which supplies data to the APIs. This vulnerability also applies to Java deployments, typically in clients running sandboxed Java Web Start applications or sandboxed Java applets, that load and run untrusted code (e.g., code that comes from the internet) and rely on the Java sandbox for security. CVSS 3.1 Base Score 3.7 (Availability impacts). CVSS Vector: (CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:L).",
"id": "GHSA-376j-8f52-gp2x",
"modified": "2026-04-21T21:31:25Z",
"published": "2026-04-21T21:31:25Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-22018"
},
{
"type": "WEB",
"url": "https://www.oracle.com/security-alerts/cpuapr2026.html"
}
],
"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:L",
"type": "CVSS_V3"
}
]
}
GHSA-378J-3JFJ-8R9F
Vulnerability from github – Published: 2026-04-06 23:08 – Updated: 2026-04-07 20:00The DAG-CBOR decoder uses collection sizes declared in CBOR headers as Go preallocation hints for maps and lists. The decoder does not cap these size hints or account for their cost in its allocation budget, allowing small payloads to cause excessive memory allocation.
A CBOR map or list header can declare an arbitrarily large number of entries, causing the decoder to preallocate proportionally large backing structures before any entries are actually read. Because the allocation budget is only decremented as entries are decoded (not when sizes are declared), this cost is effectively invisible to the budget system. This is compounded by nesting: each level of a nested structure triggers its own unchecked preallocation while consuming minimal budget (one entry per parent level), so a payload under 100 bytes with 10 levels of nesting can cause over 9GB of allocation.
Schema-free decoding (i.e. using basicnode.Prototype.Any) allows arbitrary nesting depth. Schema-bound decoding limits nesting to the schema's structure, but any field typed as Any in the schema permits unconstrained nesting within that field.
The fix caps the preallocation size hint to 1024 entries and decrements the allocation budget when collection sizes are declared. The declared length is still used for entry-count validation, and collections grow dynamically as entries are decoded, so correctly-formed data is unaffected, even beyond the preallocation limit.
{
"affected": [
{
"package": {
"ecosystem": "Go",
"name": "github.com/ipld/go-ipld-prime"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "0.22.0"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"aliases": [
"CVE-2026-35480"
],
"database_specific": {
"cwe_ids": [
"CWE-770"
],
"github_reviewed": true,
"github_reviewed_at": "2026-04-06T23:08:24Z",
"nvd_published_at": "2026-04-07T15:17:45Z",
"severity": "MODERATE"
},
"details": "The DAG-CBOR decoder uses collection sizes declared in CBOR headers as Go preallocation hints for maps and lists. The decoder does not cap these size hints or account for their cost in its allocation budget, allowing small payloads to cause excessive memory allocation.\n\nA CBOR map or list header can declare an arbitrarily large number of entries, causing the decoder to preallocate proportionally large backing structures before any entries are actually read. Because the allocation budget is only decremented as entries are decoded (not when sizes are declared), this cost is effectively invisible to the budget system. This is compounded by nesting: each level of a nested structure triggers its own unchecked preallocation while consuming minimal budget (one entry per parent level), so a payload under 100 bytes with 10 levels of nesting can cause over 9GB of allocation.\n\nSchema-free decoding (i.e. using `basicnode.Prototype.Any`) allows arbitrary nesting depth. Schema-bound decoding limits nesting to the schema\u0027s structure, but any field typed as `Any` in the schema permits unconstrained nesting within that field.\n\nThe fix caps the preallocation size hint to 1024 entries and decrements the allocation budget when collection sizes are declared. The declared length is still used for entry-count validation, and collections grow dynamically as entries are decoded, so correctly-formed data is unaffected, even beyond the preallocation limit.",
"id": "GHSA-378j-3jfj-8r9f",
"modified": "2026-04-07T20:00:26Z",
"published": "2026-04-06T23:08:24Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/ipld/go-ipld-prime/security/advisories/GHSA-378j-3jfj-8r9f"
},
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-35480"
},
{
"type": "WEB",
"url": "https://github.com/ipld/go-ipld-prime/commit/e43bf4a27055fe8d895671a731ee5041e2d983a9"
},
{
"type": "PACKAGE",
"url": "https://github.com/ipld/go-ipld-prime"
},
{
"type": "WEB",
"url": "https://github.com/ipld/go-ipld-prime/releases/tag/v0.22.0"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:L/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H",
"type": "CVSS_V3"
}
],
"summary": "go-ipld-prime: DAG-CBOR decoder unbounded memory allocation from CBOR headers"
}
GHSA-37RH-77HJ-3PMR
Vulnerability from github – Published: 2026-01-19 18:30 – Updated: 2026-01-19 18:30An Allocation of Resources Without Limits or Throttling vulnerability in the ANSL-Server component of B&R Automation Runtime versions prior to 6.5 and prior to R4.93 could be exploited by an unauthenti-cated attacker on the network to win a race condition, resulting in permanent denial-of-service (DoS) conditions on affected devices.
{
"affected": [],
"aliases": [
"CVE-2025-11044"
],
"database_specific": {
"cwe_ids": [
"CWE-770"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2026-01-19T16:15:53Z",
"severity": "HIGH"
},
"details": "An Allocation of Resources Without Limits or Throttling vulnerability in the ANSL-Server component of B\u0026R Automation Runtime versions prior to 6.5 and prior to R4.93 could be exploited by an unauthenti-cated attacker on the network to win a race condition, resulting in permanent denial-of-service (DoS) conditions on affected devices.",
"id": "GHSA-37rh-77hj-3pmr",
"modified": "2026-01-19T18:30:25Z",
"published": "2026-01-19T18:30:25Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2025-11044"
},
{
"type": "WEB",
"url": "https://www.br-automation.com/fileadmin/SA25P005-26597bd0.pdf"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:C/C:N/I:N/A:H",
"type": "CVSS_V3"
},
{
"score": "CVSS:4.0/AV:N/AC:L/AT:P/PR:N/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:H/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X",
"type": "CVSS_V4"
}
]
}
GHSA-3824-QMFQ-2QV7
Vulnerability from github – Published: 2025-04-11 14:08 – Updated: 2025-04-11 14:08Through enabling the scripting capability. SurrealDB allows for advanced functions with complicated logic, by allowing embedded functions to be written in JavaScript.
These functions are bounded for memory and stack size, but not in time. An attacker could launch a number of long running functions that could potentially facilitate a Denial Of Service attack.
This vulnerability can only affect SurrealDB servers explicitly enabling the scripting capability with --allow-scripting or
--allow-all and equivalent environment variables SURREAL_CAPS_ALLOW_SCRIPT=true and SURREAL_CAPS_ALLOW_ALL=true.
This issue was discovered and patched during an code audit and penetration test of SurrealDB by cure53, the severity defined within cure53's preliminary finding is Low, matched by our CVSS v4 assessment.
Impact
An attacker can use the scripting capabilities of SurrealDB to run a series of long running functions to facilitate a Denial Of Service attack.
Patches
A default timeout for the scripting functions has been implemented with a configurable SURREAL_SCRIPTING_MAX_TIME_LIMIT environment variable
- Versions 2.0.5, 2.1.5, 2.2.2 and later are not affected by this issue.
Workarounds
For users that cannot upgrade. Deny execution of embedded scripting functions through the configuration of capabilities by starting SurrealDB with the --deny-scripting flag or the equivalent environment variable SURREAL_CAPS_DENY_SCRIPT=true. This has a usability implication, although scripting functions are disabled by default.
References
5597 SurrealDB Documentation - Capabilities SurrealQL Documentation - Scripting Functions
{
"affected": [
{
"package": {
"ecosystem": "crates.io",
"name": "surrealdb"
},
"ranges": [
{
"events": [
{
"introduced": "2.2.0"
},
{
"fixed": "2.2.2"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "crates.io",
"name": "surrealdb"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "2.0.5"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "crates.io",
"name": "surrealdb"
},
"ranges": [
{
"events": [
{
"introduced": "2.1.0"
},
{
"fixed": "2.1.5"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"aliases": [],
"database_specific": {
"cwe_ids": [
"CWE-770"
],
"github_reviewed": true,
"github_reviewed_at": "2025-04-11T14:08:45Z",
"nvd_published_at": null,
"severity": "LOW"
},
"details": "Through enabling the scripting capability. SurrealDB allows for advanced functions with complicated logic, by allowing embedded functions to be written in JavaScript.\n\nThese functions are bounded for memory and stack size, but not in time. An attacker could launch a number of long running functions that could potentially facilitate a Denial Of Service attack.\n\nThis vulnerability can only affect SurrealDB servers explicitly enabling the scripting capability with `--allow-scripting` or\n`--allow-all` and equivalent environment variables `SURREAL_CAPS_ALLOW_SCRIPT=true` and `SURREAL_CAPS_ALLOW_ALL=true`.\n\nThis issue was discovered and patched during an code audit and penetration test of SurrealDB by cure53, the severity defined within cure53\u0027s preliminary finding is Low, matched by our CVSS v4 assessment.\n\n### Impact\nAn attacker can use the scripting capabilities of SurrealDB to run a series of long running functions to facilitate a Denial Of Service attack.\n\n### Patches\nA default timeout for the scripting functions has been implemented with a configurable `SURREAL_SCRIPTING_MAX_TIME_LIMIT` environment variable\n\n- Versions 2.0.5, 2.1.5, 2.2.2 and later are not affected by this issue.\n\n### Workarounds\nFor users that cannot upgrade. Deny execution of embedded scripting functions through the configuration of [capabilities](https://surrealdb.com/docs/surrealdb/security/capabilities#capabilities) by starting SurrealDB with the `--deny-scripting` flag or the equivalent environment variable `SURREAL_CAPS_DENY_SCRIPT=true`. This has a usability implication, although scripting functions are disabled by default.\n\n### References\n[5597](https://github.com/surrealdb/surrealdb/pull/5597)\n[SurrealDB Documentation - Capabilities](https://surrealdb.com/docs/surrealdb/security/capabilities)\n[SurrealQL Documentation - Scripting Functions](https://surrealdb.com/docs/surrealql/functions/script)",
"id": "GHSA-3824-qmfq-2qv7",
"modified": "2025-04-11T14:08:45Z",
"published": "2025-04-11T14:08:45Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/surrealdb/surrealdb/security/advisories/GHSA-3824-qmfq-2qv7"
},
{
"type": "WEB",
"url": "https://github.com/surrealdb/surrealdb/pull/5597"
},
{
"type": "PACKAGE",
"url": "https://github.com/surrealdb/surrealdb"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:4.0/AV:N/AC:L/AT:P/PR:L/UI:N/VC:N/VI:N/VA:L/SC:N/SI:N/SA:N",
"type": "CVSS_V4"
}
],
"summary": "SurrealDB no JavaScript script function default timeout could facilitate DoS"
}
GHSA-384M-RPVV-4RW6
Vulnerability from github – Published: 2024-02-23 09:30 – Updated: 2026-02-23 12:31Denial of service condition in M-Files Server in versions before 24.2 (excluding 23.2 SR7 and 23.8 SR5) allows anonymous user to cause denial of service against other anonymous users.
{
"affected": [],
"aliases": [
"CVE-2024-0563"
],
"database_specific": {
"cwe_ids": [
"CWE-400",
"CWE-770"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2024-02-23T09:15:22Z",
"severity": "MODERATE"
},
"details": "Denial of service condition in M-Files Server in\u00a0versions before 24.2 (excluding 23.2 SR7 and 23.8 SR5) allows anonymous user to cause denial of service against other anonymous users.",
"id": "GHSA-384m-rpvv-4rw6",
"modified": "2026-02-23T12:31:28Z",
"published": "2024-02-23T09:30:38Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2024-0563"
},
{
"type": "WEB",
"url": "https://empower.m-files.com/security-advisories/CVE-2024-0563"
},
{
"type": "WEB",
"url": "https://product.m-files.com/security-advisories/cve-2024-0563"
},
{
"type": "WEB",
"url": "https://www.m-files.com/about/trust-center/security-advisories/cve-2024-0563"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:L",
"type": "CVSS_V3"
}
]
}
GHSA-386P-V9X3-GXPM
Vulnerability from github – Published: 2026-05-05 18:33 – Updated: 2026-05-06 18:30An issue was discovered in MM in Samsung Mobile Processor, Wearable Processor, and Modem Exynos 980, 990, 850, 2100, 1280, 2200, 1330, 1380, 1480, 2400, 1580, 2500, W920, W930, W1000, Modem 5123, Modem 5300, and Modem 5400. Incorrect handling of 5G NR NAS registration accept messages leads to a Denial of Service.
{
"affected": [],
"aliases": [
"CVE-2025-66369"
],
"database_specific": {
"cwe_ids": [
"CWE-770"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2026-05-05T16:16:10Z",
"severity": "HIGH"
},
"details": "An issue was discovered in MM in Samsung Mobile Processor, Wearable Processor, and Modem Exynos 980, 990, 850, 2100, 1280, 2200, 1330, 1380, 1480, 2400, 1580, 2500, W920, W930, W1000, Modem 5123, Modem 5300, and Modem 5400. Incorrect handling of 5G NR NAS registration accept messages leads to a Denial of Service.",
"id": "GHSA-386p-v9x3-gxpm",
"modified": "2026-05-06T18:30:30Z",
"published": "2026-05-05T18:33:24Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2025-66369"
},
{
"type": "WEB",
"url": "https://semiconductor.samsung.com/support/quality-support/product-security-updates"
},
{
"type": "WEB",
"url": "https://semiconductor.samsung.com/support/quality-support/product-security-updates/cve-2025-66369"
}
],
"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-389X-67PX-MJG3
Vulnerability from github – Published: 2025-04-09 13:08 – Updated: 2026-06-08 20:04Summary
Xgrammar includes a cache for compiled grammars to increase performance with repeated use of the same grammar. This cache is held in memory. Since the cache is unbounded, a system making use of xgrammar can be abused to fill up a host's memory and case a denial of service. For example, sending many small requests to an LLM inference server with unique JSON schemas would eventually cause this denial of service to occur.
Details
The fix is to add a limit to the cache size. This was done in https://github.com/mlc-ai/xgrammar/pull/243
An example of making use of the new cache size limit can be found in vLLM here: https://github.com/vllm-project/vllm/pull/16283
Impact
Any system making use of Xgrammar and taking requests as input from potentially untrusted parties would be vulnerable to this denial of service issue.
{
"affected": [
{
"package": {
"ecosystem": "PyPI",
"name": "xgrammar"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "0.1.18"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"aliases": [
"CVE-2025-32381"
],
"database_specific": {
"cwe_ids": [
"CWE-770"
],
"github_reviewed": true,
"github_reviewed_at": "2025-04-09T13:08:59Z",
"nvd_published_at": "2025-04-09T16:15:26Z",
"severity": "MODERATE"
},
"details": "### Summary\n\nXgrammar includes a cache for compiled grammars to increase performance with repeated use of the same grammar. This cache is held in memory. Since the cache is unbounded, a system making use of xgrammar can be abused to fill up a host\u0027s memory and case a denial of service. For example, sending many small requests to an LLM inference server with unique JSON schemas would eventually cause this denial of service to occur.\n\n### Details\n\nThe fix is to add a limit to the cache size. This was done in https://github.com/mlc-ai/xgrammar/pull/243\n\nAn example of making use of the new cache size limit can be found in vLLM here: https://github.com/vllm-project/vllm/pull/16283\n\n### Impact\n\nAny system making use of Xgrammar and taking requests as input from potentially untrusted parties would be vulnerable to this denial of service issue.",
"id": "GHSA-389x-67px-mjg3",
"modified": "2026-06-08T20:04:11Z",
"published": "2025-04-09T13:08:59Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/mlc-ai/xgrammar/security/advisories/GHSA-389x-67px-mjg3"
},
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2025-32381"
},
{
"type": "WEB",
"url": "https://github.com/mlc-ai/xgrammar/pull/243"
},
{
"type": "WEB",
"url": "https://github.com/vllm-project/vllm/pull/16283"
},
{
"type": "PACKAGE",
"url": "https://github.com/mlc-ai/xgrammar"
},
{
"type": "WEB",
"url": "https://github.com/pypa/advisory-database/tree/main/vulns/xgrammar/PYSEC-2025-235.yaml"
}
],
"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"
}
],
"summary": "xgrammar Vulnerable to Denial of Service (DoS) by abusing unbounded cache in memory"
}
GHSA-38H3-2333-QX47
Vulnerability from github – Published: 2026-04-18 01:05 – Updated: 2026-04-27 16:15Summary
[!IMPORTANT]
There is no plan to fix this issue asOpenTelemetry.Exporter.Jaegerwas deprecated in 2023. It is for informational purposes only.
OpenTelemetry.Exporter.Jaeger may allow sustained memory pressure when the internal pooled-list sizing grows based on a large observed span/tag set and that enlarged size is reused for subsequent allocations. Under high-cardinality or attacker-influenced telemetry input, this can increase memory consumption and potentially cause denial of service.
Details
The Jaeger exporter conversion path can append tag/event data into pooled list structures. In affected versions, pooled allocation sizing may be influenced by large observed payloads and reused globally across later allocations, resulting in persistent oversized rentals and elevated memory pressure. In environments where telemetry attributes/events can be influenced by untrusted input and limits are increased from defaults, this may lead to process instability or denial of service.
Impact
Availability impact only. Confidentiality and integrity impacts are not expected.
Workarounds / Mitigations
- Prefer maintained exporters (for example OpenTelemetry Protocol format (OTLP)) instead of the Jaeger exporter.
{
"affected": [
{
"package": {
"ecosystem": "NuGet",
"name": "OpenTelemetry.Exporter.Jaeger"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"last_affected": "1.6.0-rc.1"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"aliases": [
"CVE-2026-41078"
],
"database_specific": {
"cwe_ids": [
"CWE-400",
"CWE-770"
],
"github_reviewed": true,
"github_reviewed_at": "2026-04-18T01:05:12Z",
"nvd_published_at": "2026-04-23T19:17:28Z",
"severity": "MODERATE"
},
"details": "### Summary\n\n\u003e [!IMPORTANT] \n\u003e There is no plan to fix this issue as `OpenTelemetry.Exporter.Jaeger` was deprecated in 2023. It is for informational purposes only.\n\n`OpenTelemetry.Exporter.Jaeger` may allow sustained memory pressure when the internal pooled-list sizing grows based on a large observed span/tag set and that enlarged size is reused for subsequent allocations. Under high-cardinality or attacker-influenced telemetry input, this can increase memory consumption and potentially cause denial of service.\n\n### Details\n\nThe Jaeger exporter conversion path can append tag/event data into pooled list structures. In affected versions, pooled allocation sizing may be influenced by large observed payloads and reused globally across later allocations, resulting in persistent oversized rentals and elevated memory pressure. In environments where telemetry attributes/events can be influenced by untrusted input and limits are increased from defaults, this may lead to process instability or denial of service.\n\n### Impact\n\nAvailability impact only. Confidentiality and integrity impacts are not expected.\n\n### Workarounds / Mitigations\n\n* Prefer maintained exporters (for example OpenTelemetry Protocol format (OTLP)) instead of the Jaeger exporter.",
"id": "GHSA-38h3-2333-qx47",
"modified": "2026-04-27T16:15:48Z",
"published": "2026-04-18T01:05:12Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/open-telemetry/opentelemetry-dotnet/security/advisories/GHSA-38h3-2333-qx47"
},
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-41078"
},
{
"type": "PACKAGE",
"url": "https://github.com/open-telemetry/opentelemetry-dotnet"
}
],
"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"
}
],
"summary": "OpenTelemetry .NET has potential memory exhaustion via unbounded pooled-list sizing in Jaeger exporter conversion path"
}
GHSA-38RV-X7PX-6HHQ
Vulnerability from github – Published: 2026-06-18 14:28 – Updated: 2026-06-18 14:28Impact
The undici WebSocket client enforces maxPayloadSize per-frame but does not enforce the cumulative size of fragmented uncompressed messages. A malicious WebSocket server can stream many small fragments that each pass per-frame validation but collectively exceed the configured limit, causing unbounded memory growth in the client process. The result is memory exhaustion and a denial of service.
Affected applications are those using the undici WebSocket client (new WebSocket(...)) that can be induced to connect to an attacker-controlled or compromised WebSocket endpoint.
This is a regression specific to undici 8.1.0. The 6.25.0 line shipped the equivalent cumulative check from the start and is unaffected. The 7.x line never had the maxPayloadSize feature and is also unaffected.
Patches
Upgrade to undici >= 8.5.0.
Workarounds
No workaround is available. The fix must be applied through an upgrade.
{
"affected": [
{
"package": {
"ecosystem": "npm",
"name": "undici"
},
"ranges": [
{
"events": [
{
"introduced": "8.0.0"
},
{
"fixed": "8.5.0"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"aliases": [
"CVE-2026-9675"
],
"database_specific": {
"cwe_ids": [
"CWE-400",
"CWE-770"
],
"github_reviewed": true,
"github_reviewed_at": "2026-06-18T14:28:10Z",
"nvd_published_at": "2026-06-17T17:17:28Z",
"severity": "HIGH"
},
"details": "## Impact\n\nThe undici WebSocket client enforces `maxPayloadSize` per-frame but does not enforce the cumulative size of fragmented uncompressed messages. A malicious WebSocket server can stream many small fragments that each pass per-frame validation but collectively exceed the configured limit, causing unbounded memory growth in the client process. The result is memory exhaustion and a denial of service.\n\nAffected applications are those using the undici WebSocket client (`new WebSocket(...)`) that can be induced to connect to an attacker-controlled or compromised WebSocket endpoint.\n\nThis is a regression specific to undici 8.1.0. The 6.25.0 line shipped the equivalent cumulative check from the start and is unaffected. The 7.x line never had the `maxPayloadSize` feature and is also unaffected.\n\n## Patches\n\nUpgrade to undici \u003e= 8.5.0.\n\n## Workarounds\n\nNo workaround is available. The fix must be applied through an upgrade.",
"id": "GHSA-38rv-x7px-6hhq",
"modified": "2026-06-18T14:28:10Z",
"published": "2026-06-18T14:28:10Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/nodejs/undici/security/advisories/GHSA-38rv-x7px-6hhq"
},
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-9675"
},
{
"type": "WEB",
"url": "https://cna.openjsf.org/security-advisories.html"
},
{
"type": "PACKAGE",
"url": "https://github.com/nodejs/undici"
}
],
"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": "undici WebSocket client vulnerable to denial of service via cumulative fragment bypass"
}
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.