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.
3702 vulnerabilities reference this CWE, most recent first.
GHSA-F24F-GF52-825J
Vulnerability from github – Published: 2026-08-27 18:32 – Updated: 2026-08-31 18:31An issue in the RechargePut function of free5gc v4.0.1 allows attackers to cause a Denial of Service (DoS) via a crafted input.
{
"affected": [],
"aliases": [
"CVE-2026-30071"
],
"database_specific": {
"cwe_ids": [
"CWE-770"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2026-08-27T17:17:52Z",
"severity": "HIGH"
},
"details": "An issue in the RechargePut function of free5gc v4.0.1 allows attackers to cause a Denial of Service (DoS) via a crafted input.",
"id": "GHSA-f24f-gf52-825j",
"modified": "2026-08-31T18:31:22Z",
"published": "2026-08-27T18:32:23Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-30071"
},
{
"type": "WEB",
"url": "https://github.com/free5gc/free5gc/issues/760"
}
],
"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-F26W-GH5M-QQ77
Vulnerability from github – Published: 2025-06-09 20:29 – Updated: 2025-06-10 14:45Impact
Pion Interceptor versions v0.1.36 through v0.1.38 contain a bug in a RTP packet factory that can be exploited to trigger a panic with Pion based SFU via crafted RTP packets, This only affect users that use pion/interceptor.
Patches
Upgrade to v0.1.39 or later, which includes PR #338 which validates that: padLen > 0 && padLen <= payloadLength and return error on overflow, avoiding panic.
If upgrading is not possible, apply the patch from the pull request manually or drop packets whose P-bit is set but whose padLen is zero or larger than the remaining payload.
Workarounds
At the application layer, reject any RTP packet where:
hasPadding (P-bit field) == true && (padLen == 0 || padLen > packetLen – headerLen)
before passing it to Pion’s packet factories.
References
Commit fixing the bug: https://github.com/pion/interceptor/commit/fa5b35ea867389cec33a9c82fffbd459ca8958e5 Pull request: https://github.com/pion/interceptor/pull/338 Issue: https://github.com/pion/webrtc/issues/3148
{
"affected": [
{
"package": {
"ecosystem": "Go",
"name": "github.com/pion/interceptor"
},
"ranges": [
{
"events": [
{
"introduced": "0.1.36"
},
{
"fixed": "0.1.39"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"aliases": [
"CVE-2025-49140"
],
"database_specific": {
"cwe_ids": [
"CWE-770"
],
"github_reviewed": true,
"github_reviewed_at": "2025-06-09T20:29:40Z",
"nvd_published_at": "2025-06-09T22:15:22Z",
"severity": "HIGH"
},
"details": "### Impact\nPion Interceptor versions v0.1.36 through v0.1.38 contain a bug in a RTP packet factory that can be exploited to trigger a panic with Pion based SFU via crafted RTP packets, This only affect users that use pion/interceptor.\n\n### Patches\n\nUpgrade to v0.1.39 or later, which includes PR [#338](https://github.com/pion/interceptor/pull/338) which validates that: `padLen \u003e 0 \u0026\u0026 padLen \u003c= payloadLength` and return error on overflow, avoiding panic.\n\nIf upgrading is not possible, apply the patch from the pull request manually or drop packets whose P-bit is set but whose padLen is zero or larger than the remaining payload.\n\n### Workarounds\nAt the application layer, reject any RTP packet where:\n```\nhasPadding (P-bit field) == true \u0026\u0026 (padLen == 0 || padLen \u003e packetLen \u2013 headerLen)\n```\n\nbefore passing it to Pion\u2019s packet factories.\n\n### References\nCommit fixing the bug: https://github.com/pion/interceptor/commit/fa5b35ea867389cec33a9c82fffbd459ca8958e5\nPull request: https://github.com/pion/interceptor/pull/338\nIssue: https://github.com/pion/webrtc/issues/3148",
"id": "GHSA-f26w-gh5m-qq77",
"modified": "2025-06-10T14:45:07Z",
"published": "2025-06-09T20:29:40Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/pion/interceptor/security/advisories/GHSA-f26w-gh5m-qq77"
},
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2025-49140"
},
{
"type": "WEB",
"url": "https://github.com/pion/webrtc/issues/3148"
},
{
"type": "WEB",
"url": "https://github.com/pion/interceptor/pull/338"
},
{
"type": "WEB",
"url": "https://github.com/pion/interceptor/commit/fa5b35ea867389cec33a9c82fffbd459ca8958e5"
},
{
"type": "PACKAGE",
"url": "https://github.com/pion/interceptor"
}
],
"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": "Pion Interceptor\u0027s improper RTP padding handling allows remote crash for SFU users (DoS)"
}
GHSA-F283-GHQC-FG79
Vulnerability from github – Published: 2026-07-20 23:27 – Updated: 2026-08-04 12:58Impact
In affected versions, Guzzle's built-in CookieJar accepts any number of Set-Cookie header fields from one response, with no limit on the size of each field. When a later request matches the stored cookies, Guzzle places every match into one generated Cookie header without limiting the number of cookies or the total header length.
A malicious or compromised server can therefore return many large cookies, causing Guzzle to store attacker-controlled data in memory and copy it into later request headers. This can increase memory use and processing time. It can also make later requests fail when the generated header exceeds a limit in a handler, HTTP implementation, proxy, or destination server. A server on one sibling host, such as attacker.example.com, can also set parent-domain cookies that are later selected for another sibling, such as service.example.com. The denial can therefore affect a different service that uses the same jar.
An application is affected when it enables the built-in cookie support, receives an attacker-controlled response, and retains or reuses the jar. The issue affects both built-in handlers because Guzzle manages these cookies itself instead of using libcurl's native cookie engine. cURL addressed a similar denial-of-service issue in CVE-2022-32205 by limiting the cookies it accepts and sends, but those native limits do not protect Guzzle's separate jar. Applications that do not use cookies, use separate jars for untrusted origins, or use a third-party CookieJarInterface with suitable limits are not affected by this behavior. The demonstrated direct impact is limited to availability. The patch does not impose a lifetime limit on a jar built up over an unlimited number of responses or populated directly by application code.
Patches
The issue is patched in 7.15.1 and later. Starting in that release, the built-in CookieJar ignores a Set-Cookie field value longer than 8,190 bytes and applies at most 50 successful cookie insertions or replacements from one response. When generating a request, it emits at most 150 matching name=value pairs and limits the complete Cookie: header line to 8,190 bytes, including the field name and following space.
These limits follow the same practical shape as cURL's response to CVE-2022-32205. Both bound cookies accepted from one response, cookies added to one request, and generated header size. Guzzle's 8,190-byte incoming field limit is more generous than cURL's current 5,000-byte cookie-line limit. Neither approach adds a global jar quota or an eviction policy. The 8,190-byte incoming boundary is inclusive. Invalid, unrelated, identical, oversized, and deletion fields do not consume the 50-cookie limit. For outgoing requests, Guzzle preserves its existing matching and iteration order. It stops after 150 pairs or before the first matching cookie that would exceed the line limit. The output limits also apply to directly imported cookie state, but that state is not limited when it is added to the jar. Explicit caller-supplied Cookie headers and third-party jar implementations remain the caller's responsibility. Versions before 7.15.1 are affected.
Workarounds
If you cannot upgrade immediately, do not enable a shared built-in cookie jar for requests to untrusted origins. Use separate jars per host or trust boundary, disable cookie handling for untrusted requests, and discard or clear a jar after receiving an untrusted response before it is reused. Applications that must accept cookies from untrusted peers can provide a custom CookieJarInterface implementation that enforces suitable limits.
Guzzle does not use libcurl's cookie engine for cookies stored in a CookieJar. The cURL handler sends the Cookie header that Guzzle's cookie middleware has already built, so libcurl's cookie limits do not apply. Upgrading libcurl therefore does not fix this issue.
References
- https://curl.se/docs/CVE-2022-32205.html
- https://www.rfc-editor.org/rfc/rfc10025.html#section-5.7
- https://www.rfc-editor.org/rfc/rfc10025.html#section-5.8.3
- https://www.rfc-editor.org/rfc/rfc10025.html#section-6.1
{
"affected": [
{
"package": {
"ecosystem": "Packagist",
"name": "guzzlehttp/guzzle"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "7.15.1"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"aliases": [
"CVE-2026-67353"
],
"database_specific": {
"cwe_ids": [
"CWE-1325",
"CWE-770"
],
"github_reviewed": true,
"github_reviewed_at": "2026-07-20T23:27:02Z",
"nvd_published_at": null,
"severity": "MODERATE"
},
"details": "### Impact\n\nIn affected versions, Guzzle\u0027s built-in `CookieJar` accepts any number of `Set-Cookie` header fields from one response, with no limit on the size of each field. When a later request matches the stored cookies, Guzzle places every match into one generated `Cookie` header without limiting the number of cookies or the total header length.\n\nA malicious or compromised server can therefore return many large cookies, causing Guzzle to store attacker-controlled data in memory and copy it into later request headers. This can increase memory use and processing time. It can also make later requests fail when the generated header exceeds a limit in a handler, HTTP implementation, proxy, or destination server. A server on one sibling host, such as `attacker.example.com`, can also set parent-domain cookies that are later selected for another sibling, such as `service.example.com`. The denial can therefore affect a different service that uses the same jar.\n\nAn application is affected when it enables the built-in cookie support, receives an attacker-controlled response, and retains or reuses the jar. The issue affects both built-in handlers because Guzzle manages these cookies itself instead of using libcurl\u0027s native cookie engine. cURL addressed a similar denial-of-service issue in CVE-2022-32205 by limiting the cookies it accepts and sends, but those native limits do not protect Guzzle\u0027s separate jar. Applications that do not use cookies, use separate jars for untrusted origins, or use a third-party `CookieJarInterface` with suitable limits are not affected by this behavior. The demonstrated direct impact is limited to availability. The patch does not impose a lifetime limit on a jar built up over an unlimited number of responses or populated directly by application code.\n\n### Patches\n\nThe issue is patched in `7.15.1` and later. Starting in that release, the built-in `CookieJar` ignores a `Set-Cookie` field value longer than 8,190 bytes and applies at most 50 successful cookie insertions or replacements from one response. When generating a request, it emits at most 150 matching `name=value` pairs and limits the complete `Cookie: ` header line to 8,190 bytes, including the field name and following space.\n\nThese limits follow the same practical shape as cURL\u0027s response to CVE-2022-32205. Both bound cookies accepted from one response, cookies added to one request, and generated header size. Guzzle\u0027s 8,190-byte incoming field limit is more generous than cURL\u0027s current 5,000-byte cookie-line limit. Neither approach adds a global jar quota or an eviction policy. The 8,190-byte incoming boundary is inclusive. Invalid, unrelated, identical, oversized, and deletion fields do not consume the 50-cookie limit. For outgoing requests, Guzzle preserves its existing matching and iteration order. It stops after 150 pairs or before the first matching cookie that would exceed the line limit. The output limits also apply to directly imported cookie state, but that state is not limited when it is added to the jar. Explicit caller-supplied `Cookie` headers and third-party jar implementations remain the caller\u0027s responsibility. Versions before `7.15.1` are affected.\n\n### Workarounds\n\nIf you cannot upgrade immediately, do not enable a shared built-in cookie jar for requests to untrusted origins. Use separate jars per host or trust boundary, disable cookie handling for untrusted requests, and discard or clear a jar after receiving an untrusted response before it is reused. Applications that must accept cookies from untrusted peers can provide a custom `CookieJarInterface` implementation that enforces suitable limits.\n\nGuzzle does not use libcurl\u0027s cookie engine for cookies stored in a `CookieJar`. The cURL handler sends the `Cookie` header that Guzzle\u0027s cookie middleware has already built, so libcurl\u0027s cookie limits do not apply. Upgrading libcurl therefore does not fix this issue.\n\n### References\n\n* https://curl.se/docs/CVE-2022-32205.html\n* https://www.rfc-editor.org/rfc/rfc10025.html#section-5.7\n* https://www.rfc-editor.org/rfc/rfc10025.html#section-5.8.3\n* https://www.rfc-editor.org/rfc/rfc10025.html#section-6.1",
"id": "GHSA-f283-ghqc-fg79",
"modified": "2026-08-04T12:58:41Z",
"published": "2026-07-20T23:27:02Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/guzzle/guzzle/security/advisories/GHSA-f283-ghqc-fg79"
},
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-67353"
},
{
"type": "WEB",
"url": "https://github.com/guzzle/guzzle/pull/3901"
},
{
"type": "WEB",
"url": "https://github.com/guzzle/guzzle/commit/7b68220d6543f6f80fe62e633361fc9d4ead14d4"
},
{
"type": "PACKAGE",
"url": "https://github.com/guzzle/guzzle"
},
{
"type": "WEB",
"url": "https://github.com/guzzle/guzzle/releases/tag/7.15.1"
},
{
"type": "WEB",
"url": "https://www.vulncheck.com/advisories/guzzlehttp-guzzle-before-unbounded-cookie-denial-of-service"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:L",
"type": "CVSS_V3"
}
],
"summary": "Guzzle: Unbounded response cookies risk denial of service"
}
GHSA-F2HR-7QXV-2PWM
Vulnerability from github – Published: 2026-09-04 12:30 – Updated: 2026-09-04 12:30SiYuan versions before v3.8.2 contain a denial of service vulnerability in the publish-service Basic Auth throttle that stores failed-attempt state using attacker-controlled usernames without enforcing capacity limits or eviction policies. Unauthenticated attackers can submit repeated authentication requests with unique invalid usernames to exhaust memory and increase synchronization overhead, degrading service availability.
{
"affected": [],
"aliases": [
"CVE-2026-85584"
],
"database_specific": {
"cwe_ids": [
"CWE-770"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2026-09-04T12:17:20Z",
"severity": "HIGH"
},
"details": "SiYuan versions before v3.8.2 contain a denial of service vulnerability in the publish-service Basic Auth throttle that stores failed-attempt state using attacker-controlled usernames without enforcing capacity limits or eviction policies. Unauthenticated attackers can submit repeated authentication requests with unique invalid usernames to exhaust memory and increase synchronization overhead, degrading service availability.",
"id": "GHSA-f2hr-7qxv-2pwm",
"modified": "2026-09-04T12:30:59Z",
"published": "2026-09-04T12:30:58Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/siyuan-note/siyuan/security/advisories/GHSA-2x7j-p79w-7744"
},
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-85584"
},
{
"type": "WEB",
"url": "https://www.vulncheck.com/advisories/siyuan-before-3.8.2-denial-of-service-via-auth-throttle"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H",
"type": "CVSS_V3"
},
{
"score": "CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X",
"type": "CVSS_V4"
}
]
}
GHSA-F2R5-5M7W-P5CX
Vulnerability from github – Published: 2026-06-23 22:16 – Updated: 2026-06-23 22:16Summary
An unprivileged process can easily trigger the processPIDEvents goroutine to be blocked indefinitely, preventing the goroutine from analyzing any new ELF file. The goroutine stays blocked in the openat2 syscall forever and the profiler can no longer work properly, it is a denial of service.
Impact
The impact is limited to denial-of-service on the ebpf-profiler agent: - There has to be a malicious workload albeit unprivileged. - No exfiltration of data. No loss of data.
Fix
Fixed in https://github.com/open-telemetry/opentelemetry-ebpf-profiler/commit/234b685cab31c2cb2f79e966caeab168bcc489e4.
Fix is part of v.0.0.202622.
{
"affected": [
{
"package": {
"ecosystem": "Go",
"name": "go.opentelemetry.io/ebpf-profiler"
},
"ranges": [
{
"events": [
{
"introduced": "0.0.202527"
},
{
"fixed": "0.0.202622"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"aliases": [
"CVE-2026-48496"
],
"database_specific": {
"cwe_ids": [
"CWE-770"
],
"github_reviewed": true,
"github_reviewed_at": "2026-06-23T22:16:14Z",
"nvd_published_at": null,
"severity": "MODERATE"
},
"details": "### Summary\n\nAn unprivileged process can easily trigger the `processPIDEvents` goroutine to be blocked indefinitely, preventing the goroutine from analyzing any new ELF file. The goroutine stays blocked in the `openat2` syscall forever and the profiler can no longer work properly, it is a denial of service.\n\n### Impact\n\nThe impact is limited to denial-of-service on the ebpf-profiler agent:\n- There has to be a malicious workload albeit unprivileged.\n- No exfiltration of data. No loss of data.\n\n### Fix\n\nFixed in https://github.com/open-telemetry/opentelemetry-ebpf-profiler/commit/234b685cab31c2cb2f79e966caeab168bcc489e4.\n\nFix is part of [v.0.0.202622](https://github.com/open-telemetry/opentelemetry-ebpf-profiler/releases/tag/v0.0.202622).",
"id": "GHSA-f2r5-5m7w-p5cx",
"modified": "2026-06-23T22:16:14Z",
"published": "2026-06-23T22:16:14Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/open-telemetry/opentelemetry-ebpf-profiler/security/advisories/GHSA-f2r5-5m7w-p5cx"
},
{
"type": "WEB",
"url": "https://github.com/open-telemetry/opentelemetry-ebpf-profiler/commit/234b685cab31c2cb2f79e966caeab168bcc489e4"
},
{
"type": "PACKAGE",
"url": "https://github.com/open-telemetry/opentelemetry-ebpf-profiler"
},
{
"type": "WEB",
"url": "https://github.com/open-telemetry/opentelemetry-ebpf-profiler/releases/tag/v0.0.202622"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:L/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H",
"type": "CVSS_V3"
}
],
"summary": "opentelemetry-ebpf-profiler: Unprivileged process can trigger a denial of service on the ebpf-profiler agent"
}
GHSA-F33J-XHH7-R2CJ
Vulnerability from github – Published: 2022-05-13 01:36 – Updated: 2022-05-13 01:36A high rate of VLAN authentication attempts sent from an adjacent host on the local broadcast domain can trigger high memory utilization by the BBE subscriber management daemon (bbe-smgd), and lead to a denial of service condition. The issue was caused by attempting to process an unbounded number of pending VLAN authentication requests, leading to excessive memory allocation. This issue only affects devices configured for DHCPv4/v6 over AE auto-sensed VLANs, utilized in Broadband Edge (BBE) deployments. Other configurations are unaffected by this issue. Affected releases are Juniper Networks Junos OS: 15.1 versions prior to 15.1R6-S2, 15.1R7; 16.1 versions prior to 16.1R5-S1, 16.1R6; 16.2 versions prior to 16.2R2-S2, 16.2R3; 17.1 versions prior to 17.1R2-S5, 17.1R3; 17.2 versions prior to 17.2R2.
{
"affected": [],
"aliases": [
"CVE-2018-0006"
],
"database_specific": {
"cwe_ids": [
"CWE-770"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2018-01-10T22:29:00Z",
"severity": "MODERATE"
},
"details": "A high rate of VLAN authentication attempts sent from an adjacent host on the local broadcast domain can trigger high memory utilization by the BBE subscriber management daemon (bbe-smgd), and lead to a denial of service condition. The issue was caused by attempting to process an unbounded number of pending VLAN authentication requests, leading to excessive memory allocation. This issue only affects devices configured for DHCPv4/v6 over AE auto-sensed VLANs, utilized in Broadband Edge (BBE) deployments. Other configurations are unaffected by this issue. Affected releases are Juniper Networks Junos OS: 15.1 versions prior to 15.1R6-S2, 15.1R7; 16.1 versions prior to 16.1R5-S1, 16.1R6; 16.2 versions prior to 16.2R2-S2, 16.2R3; 17.1 versions prior to 17.1R2-S5, 17.1R3; 17.2 versions prior to 17.2R2.",
"id": "GHSA-f33j-xhh7-r2cj",
"modified": "2022-05-13T01:36:04Z",
"published": "2022-05-13T01:36:04Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2018-0006"
},
{
"type": "WEB",
"url": "https://kb.juniper.net/JSA10834"
},
{
"type": "WEB",
"url": "http://www.securitytracker.com/id/1040184"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.0/AV:A/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H",
"type": "CVSS_V3"
}
]
}
GHSA-F33M-6R3X-9GCF
Vulnerability from github – Published: 2025-07-15 21:31 – Updated: 2025-07-15 21:31Vulnerability in the MySQL Server product of Oracle MySQL (component: Server: Optimizer). Supported versions that are affected are 9.0.0-9.1.0. 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-2025-53032"
],
"database_specific": {
"cwe_ids": [
"CWE-770"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2025-07-15T20:15:49Z",
"severity": "MODERATE"
},
"details": "Vulnerability in the MySQL Server product of Oracle MySQL (component: Server: Optimizer). Supported versions that are affected are 9.0.0-9.1.0. 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-f33m-6r3x-9gcf",
"modified": "2025-07-15T21:31:44Z",
"published": "2025-07-15T21:31:44Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2025-53032"
},
{
"type": "WEB",
"url": "https://www.oracle.com/security-alerts/cpujul2025.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-F346-8RP3-4H9H
Vulnerability from github – Published: 2026-03-27 15:42 – Updated: 2026-03-27 15:42Summary
A flaw in TSPortal allowed attackers to create arbitrary user records in the database by abusing validation logic. While validation correctly rejected invalid usernames, a side effect within a validation rule caused user records to be created regardless of whether the request succeeded. This could be exploited to cause uncontrolled database growth, leading to a potential denial of service (DoS).
Details
When submitting a Data Processing Agreement (DPA) request in TSPortal, the DPAAlreadyLive validation rule previously called User::findOrCreate().
This method created a user record if one did not already exist.
Although username validation (via MirahezeUsernameRule) correctly rejected invalid usernames, the DPAAlreadyLive rule was still executed during validation. Because it performed a state-changing operation, it created user records even when the overall validation failed and no DPA was created.
As a result: - Validation correctly rejected invalid input - However, user records were still inserted into the database as a side effect
These records were created: - Without a successful DPA request - Without audit logging tied to a completed action - Without visibility into their origin
Impact
An attacker could exploit this behavior by automating requests with invalid usernames, resulting in:
- Mass creation of arbitrary user records
- Unbounded database growth
- Increased storage and indexing overhead
- Potential degradation of application performance
At scale, this could lead to a denial of service condition due to resource exhaustion.
Proof of Concept
- Submit a DPA request using an invalid username
- Ensure the request fails validation due to
MirahezeUsernameRule - Observe that a corresponding user record is still created in the database
This behavior was confirmed prior to remediation.
Root Cause
The issue stemmed from:
- Performing state-changing operations (findOrCreate) inside validation logic
- Validation rules executing regardless of overall validation success
- Lack of separation between validation and persistence layers
Mitigation
The issue has been fixed by removing database write operations from validation logic.
Specifically:
- Replaced User::findOrCreate() with a non-mutating lookup (User::firstWhere(...))
- Ensured validation rules only perform read operations
- Prevented user creation unless all validation passes
{
"affected": [
{
"database_specific": {
"last_known_affected_version_range": "\u003c= 33"
},
"package": {
"ecosystem": "Packagist",
"name": "miraheze/ts-portal"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "34"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"aliases": [
"CVE-2026-33541"
],
"database_specific": {
"cwe_ids": [
"CWE-400",
"CWE-770"
],
"github_reviewed": true,
"github_reviewed_at": "2026-03-27T15:42:20Z",
"nvd_published_at": "2026-03-26T21:17:05Z",
"severity": "MODERATE"
},
"details": "### Summary\nA flaw in TSPortal allowed attackers to create arbitrary user records in the database by abusing validation logic. While validation correctly rejected invalid usernames, a side effect within a validation rule caused user records to be created regardless of whether the request succeeded. This could be exploited to cause uncontrolled database growth, leading to a potential denial of service (DoS).\n\n### Details\nWhen submitting a Data Processing Agreement (DPA) request in TSPortal, the `DPAAlreadyLive` validation rule previously called `User::findOrCreate()`.\n\nThis method created a user record if one did not already exist.\n\nAlthough username validation (via `MirahezeUsernameRule`) correctly rejected invalid usernames, the `DPAAlreadyLive` rule was still executed during validation. Because it performed a state-changing operation, it created user records even when the overall validation failed and no DPA was created.\n\nAs a result:\n- Validation correctly rejected invalid input\n- However, user records were still inserted into the database as a side effect\n\nThese records were created:\n- Without a successful DPA request\n- Without audit logging tied to a completed action\n- Without visibility into their origin\n\n### Impact\nAn attacker could exploit this behavior by automating requests with invalid usernames, resulting in:\n\n- Mass creation of arbitrary user records\n- Unbounded database growth\n- Increased storage and indexing overhead\n- Potential degradation of application performance\n\nAt scale, this could lead to a denial of service condition due to resource exhaustion.\n\n### Proof of Concept\n1. Submit a DPA request using an invalid username\n2. Ensure the request fails validation due to `MirahezeUsernameRule`\n3. Observe that a corresponding user record is still created in the database\n\nThis behavior was confirmed prior to remediation.\n\n### Root Cause\nThe issue stemmed from:\n- Performing state-changing operations (`findOrCreate`) inside validation logic\n- Validation rules executing regardless of overall validation success\n- Lack of separation between validation and persistence layers\n\n### Mitigation\nThe issue has been fixed by removing database write operations from validation logic.\n\nSpecifically:\n- Replaced `User::findOrCreate()` with a non-mutating lookup (`User::firstWhere(...)`)\n- Ensured validation rules only perform read operations\n- Prevented user creation unless all validation passes",
"id": "GHSA-f346-8rp3-4h9h",
"modified": "2026-03-27T15:42:20Z",
"published": "2026-03-27T15:42:20Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/miraheze/TSPortal/security/advisories/GHSA-f346-8rp3-4h9h"
},
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-33541"
},
{
"type": "PACKAGE",
"url": "https://github.com/miraheze/TSPortal"
},
{
"type": "WEB",
"url": "https://issue-tracker.miraheze.org/T15115"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H",
"type": "CVSS_V3"
}
],
"summary": "TSPortal\u0027s Uncontrolled User Creation via Validation Side Effects Leads to Potential Denial of Service"
}
GHSA-F37P-PC7R-RGHM
Vulnerability from github – Published: 2026-07-28 12:31 – Updated: 2026-07-28 12:31Allocation of resources without limits vulnerability in ninenines cowlib allows an unauthenticated remote HTTP/2 or HTTP/3 peer to exhaust memory on the vulnerable server (or client) and cause a denial of service.
The HPACK and QPACK prefixed-integer decoder cow_hpack_common:dec_big_int/3 in src/cow_hpack_common.hrl (invoked from cow_hpack:decode/2 in src/cow_hpack.erl and from cow_qpack:decode_field_section/3 in src/cow_qpack.erl) reads continuation octets until it sees one whose high bit is clear, evaluating Int + (Value bsl M) at each step with the shift M growing by seven per octet. No limit is enforced on the number of continuation octets, on the resulting bit width, or on the value; the decoder consumes whatever encoded length the peer supplies.
Because Erlang integers are immutable, each intermediate Value bsl M and each accumulator update allocates a fresh bignum whose digit width grows linearly with the number of octets processed so far. Summed across the whole decode, the transient bignum digit materialization is on the order of the square of the encoded length. A single maximal HPACK indexed representation carried inside one HTTP/2 HEADERS plus one CONTINUATION frame at Cowboy's default max_frame_size_received can force hundreds of megabytes of transient allocation and garbage-collection churn before the resulting header-table index is rejected as invalid. Repeated or concurrent connections multiply the pressure and can drive the Erlang VM to memory exhaustion.
Cowlib is the HTTP parser used by Cowboy, RabbitMQ's management plugin, and other Erlang and Elixir HTTP/2 and HTTP/3 servers and clients, so any exposed endpoint that accepts HPACK or QPACK from an untrusted peer is reachable.
This issue affects cowlib: from 2.0.0 before 2.19.0.
{
"affected": [],
"aliases": [
"CVE-2026-59248"
],
"database_specific": {
"cwe_ids": [
"CWE-770"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2026-07-28T10:16:50Z",
"severity": "HIGH"
},
"details": "Allocation of resources without limits vulnerability in ninenines cowlib allows an unauthenticated remote HTTP/2 or HTTP/3 peer to exhaust memory on the vulnerable server (or client) and cause a denial of service.\n\nThe HPACK and QPACK prefixed-integer decoder cow_hpack_common:dec_big_int/3 in src/cow_hpack_common.hrl (invoked from cow_hpack:decode/2 in src/cow_hpack.erl and from cow_qpack:decode_field_section/3 in src/cow_qpack.erl) reads continuation octets until it sees one whose high bit is clear, evaluating Int + (Value bsl M) at each step with the shift M growing by seven per octet. No limit is enforced on the number of continuation octets, on the resulting bit width, or on the value; the decoder consumes whatever encoded length the peer supplies.\n\nBecause Erlang integers are immutable, each intermediate Value bsl M and each accumulator update allocates a fresh bignum whose digit width grows linearly with the number of octets processed so far. Summed across the whole decode, the transient bignum digit materialization is on the order of the square of the encoded length. A single maximal HPACK indexed representation carried inside one HTTP/2 HEADERS plus one CONTINUATION frame at Cowboy\u0027s default max_frame_size_received can force hundreds of megabytes of transient allocation and garbage-collection churn before the resulting header-table index is rejected as invalid. Repeated or concurrent connections multiply the pressure and can drive the Erlang VM to memory exhaustion.\n\nCowlib is the HTTP parser used by Cowboy, RabbitMQ\u0027s management plugin, and other Erlang and Elixir HTTP/2 and HTTP/3 servers and clients, so any exposed endpoint that accepts HPACK or QPACK from an untrusted peer is reachable.\n\nThis issue affects cowlib: from 2.0.0 before 2.19.0.",
"id": "GHSA-f37p-pc7r-rghm",
"modified": "2026-07-28T12:31:20Z",
"published": "2026-07-28T12:31:20Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-59248"
},
{
"type": "WEB",
"url": "https://github.com/ninenines/cowlib/commit/f582430498072a0c65ad338030321576dc13a343"
},
{
"type": "WEB",
"url": "https://cna.erlef.org/cves/CVE-2026-59248.html"
},
{
"type": "WEB",
"url": "https://osv.dev/vulnerability/EEF-CVE-2026-59248"
}
],
"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: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-F37Q-Q7P2-CCFC
Vulnerability from github – Published: 2022-04-14 00:00 – Updated: 2022-04-26 13:05The image proxy component in Mattermost version 6.4.1 and earlier allocates memory for multiple copies of a proxied image, which allows an authenticated attacker to crash the server via links to very large image files.
{
"affected": [
{
"package": {
"ecosystem": "Go",
"name": "github.com/mattermost/mattermost-server/v6"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "6.4.2"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"aliases": [
"CVE-2022-1337"
],
"database_specific": {
"cwe_ids": [
"CWE-400",
"CWE-770"
],
"github_reviewed": true,
"github_reviewed_at": "2022-04-26T13:05:37Z",
"nvd_published_at": "2022-04-13T18:15:00Z",
"severity": "MODERATE"
},
"details": "The image proxy component in Mattermost version 6.4.1 and earlier allocates memory for multiple copies of a proxied image, which allows an authenticated attacker to crash the server via links to very large image files.",
"id": "GHSA-f37q-q7p2-ccfc",
"modified": "2022-04-26T13:05:37Z",
"published": "2022-04-14T00:00:17Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2022-1337"
},
{
"type": "PACKAGE",
"url": "https://github.com/mattermost/mattermost-server"
},
{
"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"
}
],
"summary": "Resource exhaustion in Mattermost"
}
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.