CWE-770
AllowedAllocation of Resources Without Limits or Throttling
Abstraction: Base · Status: Incomplete
The product allocates a reusable resource or group of resources on behalf of an actor without imposing any intended restrictions on the size or number of resources that can be allocated.
3023 vulnerabilities reference this CWE, most recent first.
GHSA-9XHM-RCRP-WQ9J
Vulnerability from github – Published: 2024-08-16 15:31 – Updated: 2024-08-16 15:31A denial-of-service vulnerability was reported in some Lenovo printers that could allow an unauthenticated attacker on a shared network to crash printer communications until the system is rebooted.
{
"affected": [],
"aliases": [
"CVE-2024-4781"
],
"database_specific": {
"cwe_ids": [
"CWE-400",
"CWE-770"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2024-08-16T15:15:30Z",
"severity": "MODERATE"
},
"details": "A denial-of-service vulnerability was reported in some Lenovo printers that could allow an unauthenticated attacker on a shared network to crash printer communications until the system is rebooted.",
"id": "GHSA-9xhm-rcrp-wq9j",
"modified": "2024-08-16T15:31:42Z",
"published": "2024-08-16T15:31:42Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2024-4781"
},
{
"type": "WEB",
"url": "https://iknow.lenovo.com.cn/detail/422688"
}
],
"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"
}
]
}
GHSA-9XVV-3V2J-FMMM
Vulnerability from github – Published: 2026-07-14 18:32 – Updated: 2026-07-14 18:32Allocation of resources without limits or throttling in ASP.NET Core allows an unauthorized attacker to deny service over a network.
{
"affected": [],
"aliases": [
"CVE-2026-50506"
],
"database_specific": {
"cwe_ids": [
"CWE-770"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2026-07-14T17:17:01Z",
"severity": "HIGH"
},
"details": "Allocation of resources without limits or throttling in ASP.NET Core allows an unauthorized attacker to deny service over a network.",
"id": "GHSA-9xvv-3v2j-fmmm",
"modified": "2026-07-14T18:32:05Z",
"published": "2026-07-14T18:32:05Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-50506"
},
{
"type": "WEB",
"url": "https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-50506"
}
],
"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-9XXQ-VVGH-V3R9
Vulnerability from github – Published: 2024-07-23 15:31 – Updated: 2024-07-31 12:31Resolver caches and authoritative zone databases that hold significant numbers of RRs for the same hostname (of any RTYPE) can suffer from degraded performance as content is being added or updated, and also when handling client queries for this name. This issue affects BIND 9 versions 9.11.0 through 9.11.37, 9.16.0 through 9.16.50, 9.18.0 through 9.18.27, 9.19.0 through 9.19.24, 9.11.4-S1 through 9.11.37-S1, 9.16.8-S1 through 9.16.50-S1, and 9.18.11-S1 through 9.18.27-S1.
{
"affected": [],
"aliases": [
"CVE-2024-1737"
],
"database_specific": {
"cwe_ids": [
"CWE-770"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2024-07-23T15:15:03Z",
"severity": "HIGH"
},
"details": "Resolver caches and authoritative zone databases that hold significant numbers of RRs for the same hostname (of any RTYPE) can suffer from degraded performance as content is being added or updated, and also when handling client queries for this name.\nThis issue affects BIND 9 versions 9.11.0 through 9.11.37, 9.16.0 through 9.16.50, 9.18.0 through 9.18.27, 9.19.0 through 9.19.24, 9.11.4-S1 through 9.11.37-S1, 9.16.8-S1 through 9.16.50-S1, and 9.18.11-S1 through 9.18.27-S1.",
"id": "GHSA-9xxq-vvgh-v3r9",
"modified": "2024-07-31T12:31:47Z",
"published": "2024-07-23T15:31:09Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2024-1737"
},
{
"type": "WEB",
"url": "https://kb.isc.org/docs/cve-2024-1737"
},
{
"type": "WEB",
"url": "https://kb.isc.org/docs/rrset-limits-in-zones"
},
{
"type": "WEB",
"url": "http://www.openwall.com/lists/oss-security/2024/07/23/1"
},
{
"type": "WEB",
"url": "http://www.openwall.com/lists/oss-security/2024/07/31/2"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H",
"type": "CVSS_V3"
}
]
}
GHSA-C2F9-4MC8-J656
Vulnerability from github – Published: 2026-07-09 13:35 – Updated: 2026-07-09 13:35Description:
The EventManager module in pyload manages a list of Client instances for subscribing to events. The addition of each unique uuid from the get_events API causes the creation of a Client instance that gets appended to the clients list. Although there is a clean() method available in the EventManager module for removing non-responding Client instances, this method is never used in the EventManager or in the entire core application code. Consequently, this causes an uncontrolled growth in memory consumption until it becomes exhausted, resulting in a DoS attack.
Vulnerable Code:
https://github.com/pyload/pyload/blob/355c3f8d78a91f72d049e58f1edee8a972f845eb/src/pyload/core/managers/event_manager.py#L16-L17
Here the client is added to the
clientslist but never cleared the inactive clients.
Exploitation:
- Start pyLoad server (Ensure the
pyloadserver is running) - Authenticate: Obtain a session cookie or an API key (Here i used the API key).
- Send Requests: Run the below poc script to send a large number of requests to the
getEventsAPI endpoint, each with a uniqueuuid.
import requests
import uuid
import time
# Configuration
URL = "http://localhost:8000/api/getEvents"
NUM_REQUESTS = 100000
headers = {
"X-API-Key" : "<YOUR_APIKEY>"
}
print(f"Starting DoS attack: sending {NUM_REQUESTS} unique UUIDs...")
for i in range(NUM_REQUESTS):
# Generating a new UUID
uid = str(uuid.uuid4())
try:
# Sending request
requests.get(URL, params={"uuid": uid}, headers=headers, timeout=5)
if i % 1000 == 0:
print(f"Sent {i} requests...")
except requests.exceptions.RequestException as e:
print(f"Error at request {i}: {e}")
break
print("Attack complete. Check memory usage.")
- Monitor Memory: Monitor the memory usage of the
pyloadprocess (e.g., usingtop,psor the following commands).
PID=$(pgrep -f "pyload"); while true; do ps -o rss= -p $PID; sleep 1; done
- Observe Growth: Notice that the memory consumption increases and never decreases, even after the requests stop and 30 seconds.
https://github.com/user-attachments/assets/28d460c9-655d-45a1-a47f-c0f4d196f686
Impact:
- Denial of Service (DoS). The
pyloadprocess will consume all available system memory, leading to an Out-of-Memory (OOM) kill by the operating system or system-wide instability, affecting other services on the host.
Mitigations:
- Invoke
clean(): Callself.clean()at the beginning of theget_eventsmethod to purge inactive clients before processing new ones. - Rate Limiting: Implement rate limiting on the
getEventsendpoint to prevent a single client from flooding the server with unique UUIDs.
{
"affected": [
{
"package": {
"ecosystem": "PyPI",
"name": "pyload-ng"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"last_affected": "0.5.0b3.dev100"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"aliases": [
"CVE-2026-48987"
],
"database_specific": {
"cwe_ids": [
"CWE-400",
"CWE-401",
"CWE-770"
],
"github_reviewed": true,
"github_reviewed_at": "2026-07-09T13:35:28Z",
"nvd_published_at": null,
"severity": "MODERATE"
},
"details": "## Description:\nThe `EventManager` module in `pyload` manages a list of `Client` instances for subscribing to events. The addition of each unique `uuid` from the `get_events` API causes the creation of a `Client` instance that gets appended to the `clients` list. Although there is a `clean()` method available in the `EventManager` module for removing non-responding `Client` instances, this method is never used in the `EventManager` or in the entire core application code. Consequently, this causes an uncontrolled growth in memory consumption until it becomes exhausted, resulting in a DoS attack.\n\n## Vulnerable Code:\nhttps://github.com/pyload/pyload/blob/355c3f8d78a91f72d049e58f1edee8a972f845eb/src/pyload/core/managers/event_manager.py#L16-L17\n\n\u003e Here the client is added to the `clients` list but never cleared the inactive clients.\n\n## Exploitation:\n1. **Start pyLoad server** (Ensure the `pyload` server is running)\n2. **Authenticate**: Obtain a session cookie or an API key (Here i used the API key).\n3. **Send Requests**: Run the below poc script to send a large number of requests to the `getEvents` API endpoint, each with a unique `uuid`.\n```python\nimport requests\nimport uuid\nimport time\n\n# Configuration\nURL = \"http://localhost:8000/api/getEvents\"\nNUM_REQUESTS = 100000\n\nheaders = {\n\t\"X-API-Key\" : \"\u003cYOUR_APIKEY\u003e\"\n}\n\nprint(f\"Starting DoS attack: sending {NUM_REQUESTS} unique UUIDs...\")\n\nfor i in range(NUM_REQUESTS):\n # Generating a new UUID\n uid = str(uuid.uuid4())\n try:\n # Sending request\n requests.get(URL, params={\"uuid\": uid}, headers=headers, timeout=5)\n if i % 1000 == 0:\n print(f\"Sent {i} requests...\")\n except requests.exceptions.RequestException as e:\n print(f\"Error at request {i}: {e}\")\n break\n\nprint(\"Attack complete. Check memory usage.\")\n\n```\n5. **Monitor Memory**: Monitor the memory usage of the `pyload` process (e.g., using `top`, `ps` or the following commands).\n```bash\nPID=$(pgrep -f \"pyload\"); while true; do ps -o rss= -p $PID; sleep 1; done\n```\n\n6. **Observe Growth**: Notice that the memory consumption increases and never decreases, even after the requests stop and 30 seconds.\n\nhttps://github.com/user-attachments/assets/28d460c9-655d-45a1-a47f-c0f4d196f686\n\n## Impact:\n- Denial of Service (DoS). The `pyload` process will consume all available system memory, leading to an Out-of-Memory (OOM) kill by the operating system or system-wide instability, affecting other services on the host.\n\n## Mitigations:\n- **Invoke `clean()`**: Call `self.clean()` at the beginning of the `get_events` method to purge inactive clients before processing new ones.\n- **Rate Limiting**: Implement rate limiting on the `getEvents` endpoint to prevent a single client from flooding the server with unique UUIDs.",
"id": "GHSA-c2f9-4mc8-j656",
"modified": "2026-07-09T13:35:28Z",
"published": "2026-07-09T13:35:28Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/pyload/pyload/security/advisories/GHSA-c2f9-4mc8-j656"
},
{
"type": "PACKAGE",
"url": "https://github.com/pyload/pyload"
}
],
"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": "pyLoad: Unbounded Memory Growth Leading to DoS and Potential DDoS in EventManager"
}
GHSA-C2G8-HM2C-64MQ
Vulnerability from github – Published: 2025-01-21 21:30 – Updated: 2025-11-03 21:32Vulnerability in the MySQL Server product of Oracle MySQL (component: Server: DDL). Supported versions that are affected are 8.4.3 and prior and 9.1.0 and prior. 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-2025-21499"
],
"database_specific": {
"cwe_ids": [
"CWE-770"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2025-01-21T21:15:14Z",
"severity": "MODERATE"
},
"details": "Vulnerability in the MySQL Server product of Oracle MySQL (component: Server: DDL). Supported versions that are affected are 8.4.3 and prior and 9.1.0 and prior. 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-c2g8-hm2c-64mq",
"modified": "2025-11-03T21:32:18Z",
"published": "2025-01-21T21:30:55Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2025-21499"
},
{
"type": "WEB",
"url": "https://security.netapp.com/advisory/ntap-20250124-0013"
},
{
"type": "WEB",
"url": "https://www.oracle.com/security-alerts/cpujan2025.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-C2QP-FWX3-8W48
Vulnerability from github – Published: 2022-05-13 01:04 – Updated: 2022-05-13 01:04An issue was discovered in the Binary File Descriptor (BFD) library (aka libbfd), as distributed in GNU Binutils 2.32. It is an attempted excessive memory allocation in elf_read_notes in elf.c.
{
"affected": [],
"aliases": [
"CVE-2019-9076"
],
"database_specific": {
"cwe_ids": [
"CWE-770"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2019-02-24T00:29:00Z",
"severity": "MODERATE"
},
"details": "An issue was discovered in the Binary File Descriptor (BFD) library (aka libbfd), as distributed in GNU Binutils 2.32. It is an attempted excessive memory allocation in elf_read_notes in elf.c.",
"id": "GHSA-c2qp-fwx3-8w48",
"modified": "2022-05-13T01:04:40Z",
"published": "2022-05-13T01:04:40Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2019-9076"
},
{
"type": "WEB",
"url": "https://security.gentoo.org/glsa/202107-24"
},
{
"type": "WEB",
"url": "https://security.netapp.com/advisory/ntap-20190314-0003"
},
{
"type": "WEB",
"url": "https://sourceware.org/bugzilla/show_bug.cgi?id=24238"
},
{
"type": "WEB",
"url": "https://support.f5.com/csp/article/K44650639"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:U/C:N/I:N/A:H",
"type": "CVSS_V3"
}
]
}
GHSA-C2QR-W9P6-CXGR
Vulnerability from github – Published: 2025-03-20 12:32 – Updated: 2025-03-20 12:32In danny-avila/librechat version git 0c2a583, there is an improper input validation vulnerability. The application uses multer middleware for handling multipart file uploads. When using in-memory storage (the default setting for multer), there is no limit on the upload file size. This can lead to a server crash due to out-of-memory errors when handling large files. An attacker without any privileges can exploit this vulnerability to cause a complete denial of service. The issue is fixed in version 0.7.6.
{
"affected": [],
"aliases": [
"CVE-2024-11171"
],
"database_specific": {
"cwe_ids": [
"CWE-20",
"CWE-770"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2025-03-20T10:15:24Z",
"severity": "HIGH"
},
"details": "In danny-avila/librechat version git 0c2a583, there is an improper input validation vulnerability. The application uses multer middleware for handling multipart file uploads. When using in-memory storage (the default setting for multer), there is no limit on the upload file size. This can lead to a server crash due to out-of-memory errors when handling large files. An attacker without any privileges can exploit this vulnerability to cause a complete denial of service. The issue is fixed in version 0.7.6.",
"id": "GHSA-c2qr-w9p6-cxgr",
"modified": "2025-03-20T12:32:41Z",
"published": "2025-03-20T12:32:41Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2024-11171"
},
{
"type": "WEB",
"url": "https://github.com/danny-avila/librechat/commit/bb58a2d0662ef86dc75a9d2f6560125c018e3836"
},
{
"type": "WEB",
"url": "https://huntr.com/bounties/91717a5a-d653-4e35-b186-9e8d00aa4285"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H",
"type": "CVSS_V3"
}
]
}
GHSA-C33X-XQRF-C478
Vulnerability from github – Published: 2024-04-02 14:16 – Updated: 2024-04-05 18:53An attacker can cause its peer to run out of memory by sending a large number of NEW_CONNECTION_ID frames that retire old connection IDs. The receiver is supposed to respond to each retirement frame with a RETIRE_CONNECTION_ID frame. The attacker can prevent the receiver from sending out (the vast majority of) these RETIRE_CONNECTION_ID frames by collapsing the peers congestion window (by selectively acknowledging received packets) and by manipulating the peer's RTT estimate.
I published a more detailed description of the attack and its mitigation in this blog post: https://seemann.io/posts/2024-03-19-exploiting-quics-connection-id-management/. I also presented this attack in the IETF QUIC working group session at IETF 119: https://youtu.be/JqXtYcZAtIA?si=nJ31QKLBSTRXY35U&t=3683
There's no way to mitigate this attack, please update quic-go to a version that contains the fix.
{
"affected": [
{
"package": {
"ecosystem": "Go",
"name": "github.com/quic-go/quic-go"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "0.42.0"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"aliases": [
"CVE-2024-22189"
],
"database_specific": {
"cwe_ids": [
"CWE-400",
"CWE-770"
],
"github_reviewed": true,
"github_reviewed_at": "2024-04-02T14:16:05Z",
"nvd_published_at": "2024-04-04T15:15:37Z",
"severity": "HIGH"
},
"details": "An attacker can cause its peer to run out of memory by sending a large number of NEW_CONNECTION_ID frames that retire old connection IDs. The receiver is supposed to respond to each retirement frame with a RETIRE_CONNECTION_ID frame. The attacker can prevent the receiver from sending out (the vast majority of) these RETIRE_CONNECTION_ID frames by collapsing the peers congestion window (by selectively acknowledging received packets) and by manipulating the peer\u0027s RTT estimate.\n\nI published a more detailed description of the attack and its mitigation in this blog post: https://seemann.io/posts/2024-03-19-exploiting-quics-connection-id-management/.\nI also presented this attack in the IETF QUIC working group session at IETF 119: https://youtu.be/JqXtYcZAtIA?si=nJ31QKLBSTRXY35U\u0026t=3683\n\nThere\u0027s no way to mitigate this attack, please update quic-go to a version that contains the fix.",
"id": "GHSA-c33x-xqrf-c478",
"modified": "2024-04-05T18:53:25Z",
"published": "2024-04-02T14:16:05Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/quic-go/quic-go/security/advisories/GHSA-c33x-xqrf-c478"
},
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2024-22189"
},
{
"type": "WEB",
"url": "https://github.com/quic-go/quic-go/commit/4a99b816ae3ab03ae5449d15aac45147c85ed47a"
},
{
"type": "PACKAGE",
"url": "https://github.com/quic-go/quic-go"
},
{
"type": "WEB",
"url": "https://seemann.io/posts/2024-03-19-exploiting-quics-connection-id-management"
},
{
"type": "WEB",
"url": "https://www.youtube.com/watch?v=JqXtYcZAtIA\u0026t=3683s"
}
],
"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": "QUIC\u0027s Connection ID Mechanism vulnerable to Memory Exhaustion Attack"
}
GHSA-C34H-7MJF-54VF
Vulnerability from github – Published: 2022-05-13 01:34 – Updated: 2022-05-13 01:34It was found that vdsm before version 4.20.37 invokes qemu-img on untrusted inputs without limiting resources. By uploading a specially crafted image, an attacker could cause the qemu-img process to consume unbounded amounts of memory of CPU time, causing a denial of service condition that could potentially impact other users of the host.
{
"affected": [],
"aliases": [
"CVE-2018-10908"
],
"database_specific": {
"cwe_ids": [
"CWE-770"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2018-08-09T19:29:00Z",
"severity": "HIGH"
},
"details": "It was found that vdsm before version 4.20.37 invokes qemu-img on untrusted inputs without limiting resources. By uploading a specially crafted image, an attacker could cause the qemu-img process to consume unbounded amounts of memory of CPU time, causing a denial of service condition that could potentially impact other users of the host.",
"id": "GHSA-c34h-7mjf-54vf",
"modified": "2022-05-13T01:34:54Z",
"published": "2022-05-13T01:34:54Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2018-10908"
},
{
"type": "WEB",
"url": "https://access.redhat.com/errata/RHEA-2018:2624"
},
{
"type": "WEB",
"url": "https://bugzilla.redhat.com/show_bug.cgi?id=CVE-2018-10908"
},
{
"type": "WEB",
"url": "https://gerrit.ovirt.org/#/c/93195"
},
{
"type": "WEB",
"url": "http://lists.nongnu.org/archive/html/qemu-block/2018-07/msg00488.html"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.0/AV:L/AC:L/PR:N/UI:R/S:C/C:N/I:N/A:H",
"type": "CVSS_V3"
}
]
}
GHSA-C35X-4RQV-GX65
Vulnerability from github – Published: 2023-04-21 15:30 – Updated: 2024-04-04 03:37Bento4 v1.6.0-639 was discovered to contain an out-of-memory bug in the mp42aac component.
{
"affected": [],
"aliases": [
"CVE-2023-29575"
],
"database_specific": {
"cwe_ids": [
"CWE-770"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2023-04-21T14:15:07Z",
"severity": "MODERATE"
},
"details": "Bento4 v1.6.0-639 was discovered to contain an out-of-memory bug in the mp42aac component.",
"id": "GHSA-c35x-4rqv-gx65",
"modified": "2024-04-04T03:37:43Z",
"published": "2023-04-21T15:30:18Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2023-29575"
},
{
"type": "WEB",
"url": "https://github.com/axiomatic-systems/Bento4/issues/842"
},
{
"type": "WEB",
"url": "https://github.com/z1r00/fuzz_vuln/blob/main/Bento4/mp42aac/readme.md"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:L/AC:L/PR:N/UI:R/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:
- 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.