Common Weakness Enumeration

CWE-770

Allowed

Allocation 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.

3030 vulnerabilities reference this CWE, most recent first.

GHSA-8M93-MJ72-8J4J

Vulnerability from github – Published: 2026-01-31 00:30 – Updated: 2026-01-31 00:30
VLAI
Details

Frigate 2.02 contains a denial of service vulnerability that allows attackers to crash the application by sending oversized input to the command line interface. Attackers can generate a payload of 8000 repeated characters and paste it into the application's command line field to trigger an application crash.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2020-37039"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-770"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2026-01-30T23:16:09Z",
    "severity": "MODERATE"
  },
  "details": "Frigate 2.02 contains a denial of service vulnerability that allows attackers to crash the application by sending oversized input to the command line interface. Attackers can generate a payload of 8000 repeated characters and paste it into the application\u0027s command line field to trigger an application crash.",
  "id": "GHSA-8m93-mj72-8j4j",
  "modified": "2026-01-31T00:30:29Z",
  "published": "2026-01-31T00:30:29Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2020-37039"
    },
    {
      "type": "WEB",
      "url": "https://web.archive.org/web/20190623044943/http://www.frigate3.com/index.php"
    },
    {
      "type": "WEB",
      "url": "https://www.exploit-db.com/exploits/48613"
    },
    {
      "type": "WEB",
      "url": "https://www.vulncheck.com/advisories/frigate-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:H",
      "type": "CVSS_V3"
    },
    {
      "score": "CVSS:4.0/AV:L/AC:L/AT:N/PR:N/UI:A/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"
    }
  ]
}

GHSA-8MQG-G8G6-FVW6

Vulnerability from github – Published: 2026-06-25 15:31 – Updated: 2026-06-25 15:31
VLAI
Details

An attacker can send crafted DNS over HTTP/3 queries, triggering an exception that prevents some buffer from being freed right away. The buffer will be freed at the end of the QUIC connection, but on some setups it might be possible to open enough concurrent DoH3 streams to trigger an out-of-memory condition, resulting in a denial of service.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2026-40211"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-770"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2026-06-25T13:16:39Z",
    "severity": "MODERATE"
  },
  "details": "An attacker can send crafted DNS over HTTP/3 queries, triggering an exception that prevents some buffer from being freed right away. The buffer will be freed at the end of the QUIC connection, but on some setups it might be possible to open enough concurrent DoH3 streams to trigger an out-of-memory condition, resulting in a denial of service.",
  "id": "GHSA-8mqg-g8g6-fvw6",
  "modified": "2026-06-25T15:31:59Z",
  "published": "2026-06-25T15:31:59Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-40211"
    },
    {
      "type": "WEB",
      "url": "https://www.dnsdist.org/security-advisories/powerdns-advisory-for-dnsdist-2026-09.html"
    }
  ],
  "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"
    }
  ]
}

GHSA-8MX2-GQX9-RM7F

Vulnerability from github – Published: 2022-08-24 00:00 – Updated: 2022-08-30 20:50
VLAI
Summary
Uncontrolled Resource Consumption in opcua
Details

The package opcua from 0.0.0 are vulnerable to Denial of Service (DoS) due to a missing limitation on the number of received chunks - per single session or in total for all concurrent sessions. An attacker can exploit this vulnerability by sending an unlimited number of huge chunks (e.g. 2GB each) without sending the Final closing chunk.

Show details on source website

{
  "affected": [
    {
      "package": {
        "ecosystem": "crates.io",
        "name": "opcua"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "0.11.0"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    }
  ],
  "aliases": [
    "CVE-2022-25888"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-400",
      "CWE-770"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2022-08-30T20:50:35Z",
    "nvd_published_at": "2022-08-23T05:15:00Z",
    "severity": "HIGH"
  },
  "details": "The package opcua from 0.0.0 are vulnerable to Denial of Service (DoS) due to a missing limitation on the number of received chunks - per single session or in total for all concurrent sessions. An attacker can exploit this vulnerability by sending an unlimited number of huge chunks (e.g. 2GB each) without sending the Final closing chunk.",
  "id": "GHSA-8mx2-gqx9-rm7f",
  "modified": "2022-08-30T20:50:35Z",
  "published": "2022-08-24T00:00:31Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2022-25888"
    },
    {
      "type": "WEB",
      "url": "https://github.com/locka99/opcua/pull/216"
    },
    {
      "type": "WEB",
      "url": "https://github.com/locka99/opcua/pull/216/commits/6fb683c5fec46c6dd347824491c4d93a229da695"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/locka99/opcua"
    },
    {
      "type": "WEB",
      "url": "https://security.snyk.io/vuln/SNYK-RUST-OPCUA-2988751"
    }
  ],
  "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": "Uncontrolled Resource Consumption in opcua"
}

GHSA-8MXM-4GJM-VRC7

Vulnerability from github – Published: 2024-02-13 15:31 – Updated: 2024-05-03 15:30
VLAI
Details

To keep its cache database efficient, named running as a recursive resolver occasionally attempts to clean up the database. It uses several methods, including some that are asynchronous: a small chunk of memory pointing to the cache element that can be cleaned up is first allocated and then queued for later processing. It was discovered that if the resolver is continuously processing query patterns triggering this type of cache-database maintenance, named may not be able to handle the cleanup events in a timely manner. This in turn enables the list of queued cleanup events to grow infinitely large over time, allowing the configured max-cache-size limit to be significantly exceeded. This issue affects BIND 9 versions 9.16.0 through 9.16.45 and 9.16.8-S1 through 9.16.45-S1.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2023-6516"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-770",
      "CWE-789"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2024-02-13T14:15:46Z",
    "severity": "HIGH"
  },
  "details": "To keep its cache database efficient, `named` running as a recursive resolver occasionally attempts to clean up the database. It uses several methods, including some that are asynchronous: a small chunk of memory pointing to the cache element that can be cleaned up is first allocated and then queued for later processing. It was discovered that if the resolver is continuously processing query patterns triggering this type of cache-database maintenance, `named` may not be able to handle the cleanup events in a timely manner. This in turn enables the list of queued cleanup events to grow infinitely large over time, allowing the configured `max-cache-size` limit to be significantly exceeded.\nThis issue affects BIND 9 versions 9.16.0 through 9.16.45 and 9.16.8-S1 through 9.16.45-S1.",
  "id": "GHSA-8mxm-4gjm-vrc7",
  "modified": "2024-05-03T15:30:36Z",
  "published": "2024-02-13T15:31:12Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2023-6516"
    },
    {
      "type": "WEB",
      "url": "https://kb.isc.org/docs/cve-2023-6516"
    },
    {
      "type": "WEB",
      "url": "https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/PNNHZSZPG2E7NBMBNYPGHCFI4V4XRWNQ"
    },
    {
      "type": "WEB",
      "url": "https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/ZDZFMEKQTZ4L7RY46FCENWFB5MDT263R"
    },
    {
      "type": "WEB",
      "url": "https://security.netapp.com/advisory/ntap-20240503-0008"
    },
    {
      "type": "WEB",
      "url": "http://www.openwall.com/lists/oss-security/2024/02/13/1"
    }
  ],
  "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"
    }
  ]
}

GHSA-8MXQ-7XR7-2FXJ

Vulnerability from github – Published: 2026-04-03 21:42 – Updated: 2026-04-06 23:10
VLAI
Summary
LTI JupyterHub Authenticator: Unbounded Memory Growth via Nonce Storage (Denial of Service)
Details

Summary

The LTI 1.1 validator stores OAuth nonces in a class-level dictionary that grows without bounds. Nonces are added before signature validation, so an attacker with knowledge of a valid consumer key can send repeated requests with unique nonces to gradually exhaust server memory, causing a denial of service.

Patches

  • upgrade jupyterhub-litauthenticator to 1.6.3
Show details on source website

{
  "affected": [
    {
      "database_specific": {
        "last_known_affected_version_range": "\u003c= 1.6.2"
      },
      "package": {
        "ecosystem": "PyPI",
        "name": "jupyterhub-ltiauthenticator"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "1.6.3"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    }
  ],
  "aliases": [
    "CVE-2026-34052"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-401",
      "CWE-770"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2026-04-03T21:42:35Z",
    "nvd_published_at": "2026-04-03T23:17:03Z",
    "severity": "MODERATE"
  },
  "details": "## Summary\n\nThe LTI 1.1 validator stores OAuth nonces in a class-level dictionary that grows without bounds. Nonces are added before signature validation, so an attacker with knowledge of a valid consumer key can send repeated requests with unique nonces to gradually exhaust server memory, causing a denial of service.\n\n## Patches\n\n- upgrade jupyterhub-litauthenticator to 1.6.3",
  "id": "GHSA-8mxq-7xr7-2fxj",
  "modified": "2026-04-06T23:10:01Z",
  "published": "2026-04-03T21:42:35Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/jupyterhub/ltiauthenticator/security/advisories/GHSA-8mxq-7xr7-2fxj"
    },
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-34052"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/jupyterhub/ltiauthenticator"
    },
    {
      "type": "WEB",
      "url": "https://github.com/jupyterhub/ltiauthenticator/releases/tag/1.6.3"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H",
      "type": "CVSS_V3"
    }
  ],
  "summary": "LTI JupyterHub Authenticator: Unbounded Memory Growth via Nonce Storage (Denial of Service)"
}

GHSA-8P8V-WH79-9R56

Vulnerability from github – Published: 2026-03-03 15:31 – Updated: 2026-03-04 20:24
VLAI
Summary
Django vulnerable to Uncontrolled Resource Consumption
Details

An issue was discovered in 6.0 before 6.0.3, 5.2 before 5.2.12, and 4.2 before 4.2.29.

URLField.to_python() in Django calls urllib.parse.urlsplit(), which performs NFKC normalization on Windows that is disproportionately slow for certain Unicode characters, allowing a remote attacker to cause denial of service via large URL inputs containing these characters.

Earlier, unsupported Django series (such as 5.0.x, 4.1.x, and 3.2.x) were not evaluated and may also be affected. Django would like to thank Seokchan Yoon for reporting this issue.

Show details on source website

{
  "affected": [
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "Django"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "6.0"
            },
            {
              "fixed": "6.0.3"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "Django"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "5.2"
            },
            {
              "fixed": "5.2.12"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "Django"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "4.2"
            },
            {
              "fixed": "4.2.29"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    }
  ],
  "aliases": [
    "CVE-2026-25673"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-400",
      "CWE-770"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2026-03-04T20:24:02Z",
    "nvd_published_at": "2026-03-03T15:16:19Z",
    "severity": "HIGH"
  },
  "details": "An issue was discovered in 6.0 before 6.0.3, 5.2 before 5.2.12, and 4.2 before 4.2.29.\n\n`URLField.to_python()` in Django calls `urllib.parse.urlsplit()`, which performs NFKC normalization on Windows that is disproportionately slow for certain Unicode characters, allowing a remote attacker to cause denial of service via large URL inputs containing these characters.\n\nEarlier, unsupported Django series (such as 5.0.x, 4.1.x, and 3.2.x) were not evaluated and may also be affected.\nDjango would like to thank Seokchan Yoon for reporting this issue.",
  "id": "GHSA-8p8v-wh79-9r56",
  "modified": "2026-03-04T20:24:02Z",
  "published": "2026-03-03T15:31:41Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-25673"
    },
    {
      "type": "WEB",
      "url": "https://docs.djangoproject.com/en/dev/releases/security"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/django/django"
    },
    {
      "type": "WEB",
      "url": "https://groups.google.com/g/django-announce"
    },
    {
      "type": "WEB",
      "url": "https://www.djangoproject.com/weblog/2026/mar/03/security-releases"
    }
  ],
  "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": "Django vulnerable to Uncontrolled Resource Consumption"
}

GHSA-8PCM-89J4-MRM2

Vulnerability from github – Published: 2022-07-02 00:00 – Updated: 2022-07-13 00:01
VLAI
Details

TOTOLINK T6 V4.1.9cu.5179_B20201015 was discovered to contain a stack overflow via the command parameter in the function FUN_0041cc88.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2022-32048"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-770"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2022-07-01T18:15:00Z",
    "severity": "HIGH"
  },
  "details": "TOTOLINK T6 V4.1.9cu.5179_B20201015 was discovered to contain a stack overflow via the command parameter in the function FUN_0041cc88.",
  "id": "GHSA-8pcm-89j4-mrm2",
  "modified": "2022-07-13T00:01:52Z",
  "published": "2022-07-02T00:00:20Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2022-32048"
    },
    {
      "type": "WEB",
      "url": "https://github.com/d1tto/IoT-vuln/tree/main/Totolink/T6-v2/10.setTracerouteCfg"
    }
  ],
  "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-8PF8-F3WP-VF64

Vulnerability from github – Published: 2024-06-28 18:31 – Updated: 2024-06-28 18:31
VLAI
Details

IBM MQ 9.0 LTS, 9.1 LTS, 9.2 LTS, 9.3 LTS and 9.3 CD, in certain configurations, is vulnerable to a denial of service attack caused by an error processing messages when an API Exit using MQBUFMH is used. IBM X-Force ID: 290259.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2024-31919"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-770"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2024-06-28T18:15:03Z",
    "severity": "MODERATE"
  },
  "details": "IBM MQ 9.0 LTS, 9.1 LTS, 9.2 LTS, 9.3 LTS and 9.3 CD, in certain configurations, is vulnerable to a denial of service attack caused by an error processing messages when an API Exit using MQBUFMH is used.  IBM X-Force ID:  290259.",
  "id": "GHSA-8pf8-f3wp-vf64",
  "modified": "2024-06-28T18:31:42Z",
  "published": "2024-06-28T18:31:42Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2024-31919"
    },
    {
      "type": "WEB",
      "url": "https://exchange.xforce.ibmcloud.com/vulnerabilities/290259"
    },
    {
      "type": "WEB",
      "url": "https://www.ibm.com/support/pages/node/7157979"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H",
      "type": "CVSS_V3"
    }
  ]
}

GHSA-8PGV-569H-W5RW

Vulnerability from github – Published: 2023-11-12 15:55 – Updated: 2025-10-28 18:22
VLAI
Summary
otelgrpc DoS vulnerability due to unbound cardinality metrics
Details

Summary

The grpc Unary Server Interceptor opentelemetry-go-contrib/instrumentation/google.golang.org/grpc/otelgrpc/interceptor.go

// UnaryServerInterceptor returns a grpc.UnaryServerInterceptor suitable
// for use in a grpc.NewServer call.
func UnaryServerInterceptor(opts ...Option) grpc.UnaryServerInterceptor {

out of the box adds labels

  • net.peer.sock.addr
  • net.peer.sock.port

that have unbound cardinality. It leads to the server's potential memory exhaustion when many malicious requests are sent.

Details

An attacker can easily flood the peer address and port for requests.

PoC

Apply the attached patch to the example and run the client multiple times. Observe how each request will create a unique histogram and how the memory consumption increases during it.

Impact

In order to be affected, the program has to configure a metrics pipeline, use UnaryServerInterceptor, and does not filter any client IP address and ports via middleware or proxies, etc.

Others

It is similar to already reported vulnerabilities.

Workaround for affected versions

As a workaround to stop being affected, a view removing the attributes can be used.

The other possibility is to disable grpc metrics instrumentation by passing otelgrpc.WithMeterProvider option with noop.NewMeterProvider.

Solution provided by upgrading

In PR #4322, to be released with v0.46.0, the attributes were removed.

References

Show details on source website

{
  "affected": [
    {
      "package": {
        "ecosystem": "Go",
        "name": "go.opentelemetry.io/contrib/instrumentation/google.golang.org/grpc/otelgrpc"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0.37.0"
            },
            {
              "fixed": "0.46.0"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    }
  ],
  "aliases": [
    "CVE-2023-47108"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-770"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2023-11-12T15:55:39Z",
    "nvd_published_at": "2023-11-10T19:15:16Z",
    "severity": "HIGH"
  },
  "details": "### Summary\n\nThe grpc Unary Server Interceptor [opentelemetry-go-contrib/instrumentation/google.golang.org/grpc/otelgrpc/interceptor.go](https://github.com/open-telemetry/opentelemetry-go-contrib/blob/9d4eb7e7706038b07d33f83f76afbe13f53d171d/instrumentation/google.golang.org/grpc/otelgrpc/interceptor.go#L327)\n\n```\n// UnaryServerInterceptor returns a grpc.UnaryServerInterceptor suitable\n// for use in a grpc.NewServer call.\nfunc UnaryServerInterceptor(opts ...Option) grpc.UnaryServerInterceptor {\n```\n  \nout of the box adds labels\n\n- `net.peer.sock.addr`\n- `net.peer.sock.port`\n\nthat have unbound cardinality. It leads to the server\u0027s potential memory exhaustion when many malicious requests are sent.\n\n### Details\n\nAn attacker can easily flood the peer address and port for requests.  \n\n### PoC\n\nApply the attached patch to the example and run the client multiple times.  Observe how each request will create a unique histogram and how the memory consumption increases during it.\n### Impact\n\nIn order to be affected, the program has to configure a metrics pipeline, use  [UnaryServerInterceptor](https://github.com/open-telemetry/opentelemetry-go-contrib/blob/9d4eb7e7706038b07d33f83f76afbe13f53d171d/instrumentation/google.golang.org/grpc/otelgrpc/interceptor.go#L327), and does not filter any client IP address and ports via middleware or proxies, etc.\n\n### Others\n\nIt is similar to already reported vulnerabilities.\n\n* [GHSA-rcjv-mgp8-qvmr](https://github.com/open-telemetry/opentelemetry-go-contrib/security/advisories/GHSA-rcjv-mgp8-qvmr) ([open-telemetry/opentelemetry-go-contrib](https://github.com/open-telemetry/opentelemetry-go-contrib))\n- [GHSA-5r5m-65gx-7vrh](https://github.com/open-telemetry/opentelemetry-go-contrib/security/advisories/GHSA-5r5m-65gx-7vrh \"GHSA-5r5m-65gx-7vrh\") ([open-telemetry/opentelemetry-go-contrib](https://github.com/open-telemetry/opentelemetry-go-contrib))\n- [GHSA-cg3q-j54f-5p7p](https://github.com/advisories/GHSA-cg3q-j54f-5p7p \"GHSA-cg3q-j54f-5p7p\") ([prometheus/client_golang](https://github.com/prometheus/client_golang))\n\n### Workaround for affected versions\n\nAs a workaround to stop being affected, a view removing the attributes can be used.\n\nThe other possibility is to disable grpc metrics instrumentation by passing [`otelgrpc.WithMeterProvider`](https://github.com/open-telemetry/opentelemetry-go-contrib/blob/instrumentation/google.golang.org/grpc/otelgrpc/v0.45.0/instrumentation/google.golang.org/grpc/otelgrpc/config.go#L138) option with [`noop.NewMeterProvider`](https://pkg.go.dev/go.opentelemetry.io/otel/metric/noop#NewMeterProvider).\n\n### Solution provided by upgrading\n\nIn PR [#4322](https://github.com/open-telemetry/opentelemetry-go-contrib/pull/4322), to be released with v0.46.0, the attributes were removed.\n\n### References\n\n- [#4322](https://github.com/open-telemetry/opentelemetry-go-contrib/pull/4322)",
  "id": "GHSA-8pgv-569h-w5rw",
  "modified": "2025-10-28T18:22:23Z",
  "published": "2023-11-12T15:55:39Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/open-telemetry/opentelemetry-go-contrib/security/advisories/GHSA-8pgv-569h-w5rw"
    },
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2023-47108"
    },
    {
      "type": "WEB",
      "url": "https://github.com/open-telemetry/opentelemetry-go-contrib/pull/4322"
    },
    {
      "type": "WEB",
      "url": "https://github.com/open-telemetry/opentelemetry-go-contrib/commit/04c5dcbb5b35f14b4e6793b245919c72addbc7d0"
    },
    {
      "type": "WEB",
      "url": "https://github.com/open-telemetry/opentelemetry-go-contrib/commit/b44dfc9092b157625a5815cb437583cee663333b"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/open-telemetry/opentelemetry-go-contrib"
    },
    {
      "type": "WEB",
      "url": "https://github.com/open-telemetry/opentelemetry-go-contrib/blob/9d4eb7e7706038b07d33f83f76afbe13f53d171d/instrumentation/google.golang.org/grpc/otelgrpc/interceptor.go#L327"
    },
    {
      "type": "WEB",
      "url": "https://github.com/open-telemetry/opentelemetry-go-contrib/blob/instrumentation/google.golang.org/grpc/otelgrpc/v0.45.0/instrumentation/google.golang.org/grpc/otelgrpc/config.go#L138"
    },
    {
      "type": "WEB",
      "url": "https://pkg.go.dev/go.opentelemetry.io/otel/metric/noop#NewMeterProvider"
    }
  ],
  "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": "otelgrpc DoS vulnerability due to unbound cardinality metrics "
}

GHSA-8PM6-575P-R3MV

Vulnerability from github – Published: 2024-10-11 18:32 – Updated: 2024-10-11 18:32
VLAI
Details

An Allocation of Resources Without Limits or Throttling vulnerability in the kernel of Juniper Networks Junos OS Evolved allows an unauthenticated, network based attacker to cause a Denial of Service (DoS).

In specific cases the state of TCP sessions that are terminated is not cleared, which over time leads to an exhaustion of resources, preventing new connections to the control plane from being established.

A continuously increasing number of connections shown by:

user@host > show system connections

is indicative of the problem. To recover the respective RE needs to be restarted manually.

This issue only affects IPv4 but does not affect IPv6. This issue only affects TCP sessions established in-band (over an interface on an FPC) but not out-of-band (over the management ethernet port on the routing-engine).

This issue affects Junos OS Evolved: 

  • All versions before 21.4R3-S9-EVO,
  • 22.2 versions before 22.2R3-S4-EVO,
  • 22.4 version before 22.4R3-S3-EVO,
  • 23.2 versions before 23.2R2-S1-EVO,
  • 23.4 versions before 23.4R2-EVO.
Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2024-47502"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-770"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2024-10-11T16:15:11Z",
    "severity": "HIGH"
  },
  "details": "An Allocation of Resources Without Limits or Throttling vulnerability in the kernel of Juniper Networks Junos OS Evolved allows an unauthenticated, network based attacker to cause a Denial of Service (DoS).\n\nIn specific cases the state of TCP sessions that are terminated is not cleared, which over time leads to an exhaustion of resources, preventing new connections to the control plane from being established.\n\nA continuously increasing number of connections shown by:\n\n\n\nuser@host \u003e show system connections\n\n\n\nis indicative of the problem. To recover the respective RE needs to be restarted manually.\n\nThis issue only affects IPv4 but does not affect IPv6.\nThis issue only affects TCP sessions established in-band (over an interface on an FPC) but not out-of-band (over the management ethernet port on the routing-engine).\n\nThis issue affects Junos OS Evolved:\u00a0\n\n  *  All versions before 21.4R3-S9-EVO,\n  *  22.2 versions before 22.2R3-S4-EVO,\n  *  22.4 version before 22.4R3-S3-EVO,\n  *  23.2 versions before 23.2R2-S1-EVO,\n  *  23.4 versions before 23.4R2-EVO.",
  "id": "GHSA-8pm6-575p-r3mv",
  "modified": "2024-10-11T18:32:49Z",
  "published": "2024-10-11T18:32:49Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2024-47502"
    },
    {
      "type": "WEB",
      "url": "https://supportportal.juniper.net/JSA88132"
    }
  ],
  "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:L/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:Y/R:U/V:X/RE:M/U:X",
      "type": "CVSS_V4"
    }
  ]
}

Mitigation
Requirements

Clearly specify the minimum and maximum expectations for capabilities, and dictate which behaviors are acceptable when resource allocation reaches limits.

Mitigation
Architecture and Design

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
Architecture and Design

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
Implementation

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
Architecture and Design

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
Architecture and Design
  • 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
Architecture and Design

Ensure that protocols have specific limits of scale placed on them.

Mitigation MIT-38.1
Architecture and Design Implementation
  • 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
Operation Architecture and Design

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.