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.

3021 vulnerabilities reference this CWE, most recent first.

GHSA-748W-F5CH-QPR7

Vulnerability from github – Published: 2025-01-21 21:30 – Updated: 2025-01-21 21:30
VLAI
Details

Vulnerability in the Oracle WebLogic Server product of Oracle Fusion Middleware (component: Core). The supported version that is affected is 14.1.1.0.0. Easily exploitable vulnerability allows unauthenticated attacker with network access via HTTP/2 to compromise Oracle WebLogic Server. Successful attacks of this vulnerability can result in unauthorized ability to cause a hang or frequently repeatable crash (complete DOS) of Oracle WebLogic Server. CVSS 3.1 Base Score 7.5 (Availability impacts). CVSS Vector: (CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H).

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2025-21549"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-400",
      "CWE-770"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2025-01-21T21:15:21Z",
    "severity": "HIGH"
  },
  "details": "Vulnerability in the Oracle WebLogic Server product of Oracle Fusion Middleware (component: Core).   The supported version that is affected is 14.1.1.0.0. Easily exploitable vulnerability allows unauthenticated attacker with network access via HTTP/2 to compromise Oracle WebLogic Server.  Successful attacks of this vulnerability can result in unauthorized ability to cause a hang or frequently repeatable crash (complete DOS) of Oracle WebLogic Server. CVSS 3.1 Base Score 7.5 (Availability impacts).  CVSS Vector: (CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H).",
  "id": "GHSA-748w-f5ch-qpr7",
  "modified": "2025-01-21T21:30:56Z",
  "published": "2025-01-21T21:30:56Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2025-21549"
    },
    {
      "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:N/UI:N/S:U/C:N/I:N/A:H",
      "type": "CVSS_V3"
    }
  ]
}

GHSA-74FC-8PM6-2R48

Vulnerability from github – Published: 2022-11-01 19:00 – Updated: 2025-05-06 15:30
VLAI
Details

Xenstore: guests can let run xenstored out of memory T[his CNA information record relates to multiple CVEs; the text explains which aspects/vulnerabilities correspond to which CVE.] Malicious guests can cause xenstored to allocate vast amounts of memory, eventually resulting in a Denial of Service (DoS) of xenstored. There are multiple ways how guests can cause large memory allocations in xenstored: - - by issuing new requests to xenstored without reading the responses, causing the responses to be buffered in memory - - by causing large number of watch events to be generated via setting up multiple xenstore watches and then e.g. deleting many xenstore nodes below the watched path - - by creating as many nodes as allowed with the maximum allowed size and path length in as many transactions as possible - - by accessing many nodes inside a transaction

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2022-42312"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-770"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2022-11-01T13:15:00Z",
    "severity": "MODERATE"
  },
  "details": "Xenstore: guests can let run xenstored out of memory T[his CNA information record relates to multiple CVEs; the text explains which aspects/vulnerabilities correspond to which CVE.] Malicious guests can cause xenstored to allocate vast amounts of memory, eventually resulting in a Denial of Service (DoS) of xenstored. There are multiple ways how guests can cause large memory allocations in xenstored: - - by issuing new requests to xenstored without reading the responses, causing the responses to be buffered in memory - - by causing large number of watch events to be generated via setting up multiple xenstore watches and then e.g. deleting many xenstore nodes below the watched path - - by creating as many nodes as allowed with the maximum allowed size and path length in as many transactions as possible - - by accessing many nodes inside a transaction",
  "id": "GHSA-74fc-8pm6-2r48",
  "modified": "2025-05-06T15:30:38Z",
  "published": "2022-11-01T19:00:31Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2022-42312"
    },
    {
      "type": "WEB",
      "url": "https://lists.fedoraproject.org/archives/list/package-announce%40lists.fedoraproject.org/message/YTMITQBGC23MSDHUCAPCVGLMVXIBXQTQ"
    },
    {
      "type": "WEB",
      "url": "https://lists.fedoraproject.org/archives/list/package-announce%40lists.fedoraproject.org/message/YZVXG7OOOXCX6VIPEMLFDPIPUTFAYWPE"
    },
    {
      "type": "WEB",
      "url": "https://lists.fedoraproject.org/archives/list/package-announce%40lists.fedoraproject.org/message/ZLI2NPNEH7CNJO3VZGQNOI4M4EWLNKPZ"
    },
    {
      "type": "WEB",
      "url": "https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/YTMITQBGC23MSDHUCAPCVGLMVXIBXQTQ"
    },
    {
      "type": "WEB",
      "url": "https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/YZVXG7OOOXCX6VIPEMLFDPIPUTFAYWPE"
    },
    {
      "type": "WEB",
      "url": "https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/ZLI2NPNEH7CNJO3VZGQNOI4M4EWLNKPZ"
    },
    {
      "type": "WEB",
      "url": "https://www.debian.org/security/2022/dsa-5272"
    },
    {
      "type": "WEB",
      "url": "https://xenbits.xenproject.org/xsa/advisory-326.txt"
    },
    {
      "type": "WEB",
      "url": "http://xenbits.xen.org/xsa/advisory-326.html"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:C/C:N/I:N/A:H",
      "type": "CVSS_V3"
    }
  ]
}

GHSA-74H7-XGM8-8M8H

Vulnerability from github – Published: 2025-01-23 12:32 – Updated: 2026-02-23 12:31
VLAI
Details

Denial of service condition in M-Files Server in versions before

25.1.14445.5 allows an unauthenticated user to consume computing resources in certain conditions.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2025-0635"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-770"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2025-01-23T11:15:10Z",
    "severity": "MODERATE"
  },
  "details": "Denial of service condition in M-Files Server in versions before \n\n25.1.14445.5 allows an unauthenticated user to consume computing resources in certain conditions.",
  "id": "GHSA-74h7-xgm8-8m8h",
  "modified": "2026-02-23T12:31:29Z",
  "published": "2025-01-23T12:32:36Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2025-0635"
    },
    {
      "type": "WEB",
      "url": "https://empower.m-files.com/security-advisories/CVE-2025-0635"
    },
    {
      "type": "WEB",
      "url": "https://product.m-files.com/security-advisories/cve-2025-0635"
    }
  ],
  "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:P/PR:N/UI:N/VC:N/VI:N/VA:L/SC:N/SI:N/SA:N/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X",
      "type": "CVSS_V4"
    }
  ]
}

GHSA-74J5-XF3V-CRQ8

Vulnerability from github – Published: 2026-07-15 23:05 – Updated: 2026-07-15 23:05
VLAI
Summary
dd-trace-go: Improper parsing of W3C baggage headers may lead to DoS
Details

Impact

Datadog tracing libraries that implement W3C baggage propagation parse incoming baggage HTTP headers without enforcing item-count or byte-size limits on the extract path. The DD_TRACE_BAGGAGE_MAX_ITEMS (default 64) and DD_TRACE_BAGGAGE_MAX_BYTES (default 8192) limits were applied only to baggage injection, not extraction. A remote, unauthenticated attacker can send a request whose baggage header contains an arbitrarily large number of comma-separated key-value pairs (or a single very large value). The tracer allocates a hash-map entry for each pair on every request, causing unbounded CPU and memory consumption and enabling a remote Denial of Service against any HTTP service that has the baggage propagation style enabled. The baggage propagation style is enabled by default in most affected tracers, so any internet-facing service that has been instrumented with an affected tracer version is exposed unless the propagation style has been explicitly narrowed.

Patches

This is resolved in version 2.8.1 and later of the dd-trace-go library.

Workarounds

If users cannot upgrade immediately: 1. Disable baggage extraction by removing baggage from DD_TRACE_PROPAGATION_STYLE (or DD_TRACE_PROPAGATION_STYLE_EXTRACT if set independently). 2. Cap the maximum HTTP request header size at an upstream proxy or web server (for example, Apache LimitRequestFieldSize, Nginx large_client_header_buffers, Envoy max_request_headers_kb).

Resources

Related upstream advisories: opentelemetry-go GHSA-mh2q-q3fh-2475 opentelemetry-dotnet GHSA-g94r-2vxg-569j

Show details on source website

{
  "affected": [
    {
      "package": {
        "ecosystem": "Go",
        "name": "github.com/DataDog/dd-trace-go"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "last_affected": "1.24.1"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "Go",
        "name": "github.com/DataDog/dd-trace-go/v2"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "2.8.1"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    }
  ],
  "aliases": [
    "CVE-2026-50274"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-770",
      "CWE-400"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2026-07-15T23:05:19Z",
    "nvd_published_at": null,
    "severity": "HIGH"
  },
  "details": "### Impact\nDatadog tracing libraries that implement W3C baggage propagation parse incoming baggage HTTP headers without enforcing item-count or byte-size limits on the extract path. The DD_TRACE_BAGGAGE_MAX_ITEMS (default 64) and DD_TRACE_BAGGAGE_MAX_BYTES (default 8192) limits were applied only to baggage injection, not extraction. A remote, unauthenticated attacker can send a request whose baggage header contains an arbitrarily large number of comma-separated key-value pairs (or a single very large value). The tracer allocates a hash-map entry for each pair on every request, causing unbounded CPU and memory consumption and enabling a remote Denial of Service against any HTTP service that has the baggage propagation style enabled.\nThe baggage propagation style is enabled by default in most affected tracers, so any internet-facing service that has been instrumented with an affected tracer version is exposed unless the propagation style has been explicitly narrowed.\n\n### Patches\nThis is resolved in version 2.8.1 and later of the `dd-trace-go` library.\n\n### Workarounds\nIf users cannot upgrade immediately:\n1. Disable `baggage` extraction by removing `baggage` from `DD_TRACE_PROPAGATION_STYLE` (or `DD_TRACE_PROPAGATION_STYLE_EXTRACT` if set independently).\n2. Cap the maximum HTTP request header size at an upstream proxy or web server (for example, Apache `LimitRequestFieldSize`, Nginx `large_client_header_buffers`, Envoy `max_request_headers_kb`).\n\n\n### Resources\nRelated upstream advisories:\n[opentelemetry-go GHSA-mh2q-q3fh-2475](https://github.com/open-telemetry/opentelemetry-go/security/advisories/GHSA-mh2q-q3fh-2475)\n[opentelemetry-dotnet GHSA-g94r-2vxg-569j](https://github.com/open-telemetry/opentelemetry-dotnet/security/advisories/GHSA-g94r-2vxg-569j)",
  "id": "GHSA-74j5-xf3v-crq8",
  "modified": "2026-07-15T23:05:19Z",
  "published": "2026-07-15T23:05:19Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/DataDog/dd-trace-go/security/advisories/GHSA-74j5-xf3v-crq8"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/DataDog/dd-trace-go"
    }
  ],
  "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": "dd-trace-go: Improper parsing of W3C baggage headers may lead to DoS"
}

GHSA-74JR-8VHJ-2C3F

Vulnerability from github – Published: 2025-12-03 18:30 – Updated: 2026-01-30 21:30
VLAI
Details

Interactive service agent in OpenVPN version 2.5.0 through 2.7_rc2 on Windows allows a local authenticated user to connect to the service and trigger an error causing a local denial of service.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2025-13751"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-770"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2025-12-03T17:15:49Z",
    "severity": "LOW"
  },
  "details": "Interactive service agent in OpenVPN version 2.5.0 through 2.7_rc2 on Windows allows a local authenticated user to connect to the service and trigger an error causing a local denial of service.",
  "id": "GHSA-74jr-8vhj-2c3f",
  "modified": "2026-01-30T21:30:19Z",
  "published": "2025-12-03T18:30:25Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2025-13751"
    },
    {
      "type": "WEB",
      "url": "https://community.openvpn.net/Security%20Announcements/CVE-2025-13751"
    },
    {
      "type": "WEB",
      "url": "https://www.mail-archive.com/openvpn-announce@lists.sourceforge.net/msg00153.html"
    },
    {
      "type": "WEB",
      "url": "https://www.mail-archive.com/openvpn-announce@lists.sourceforge.net/msg00154.html"
    },
    {
      "type": "WEB",
      "url": "https://www.mail-archive.com/openvpn-announce@lists.sourceforge.net/msg00154.htmlhttps:"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H",
      "type": "CVSS_V3"
    },
    {
      "score": "CVSS:4.0/AV:L/AC:L/AT:P/PR:L/UI:P/VC:N/VI:N/VA:H/SC:N/SI:N/SA:H/E:U/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:Clear",
      "type": "CVSS_V4"
    }
  ]
}

GHSA-74XJ-WH4W-VQXC

Vulnerability from github – Published: 2026-07-15 22:53 – Updated: 2026-07-15 22:53
VLAI
Summary
dd-trace-java: Improper parsing of W3C baggage headers may lead to DoS
Details

Impact

Datadog tracing libraries that implement W3C baggage propagation parse incoming baggage HTTP headers without enforcing item-count or byte-size limits on the extract path. The DD_TRACE_BAGGAGE_MAX_ITEMS (default 64) and DD_TRACE_BAGGAGE_MAX_BYTES (default 8192) limits were applied only to baggage injection, not extraction. A remote, unauthenticated attacker can send a request whose baggage header contains an arbitrarily large number of comma-separated key-value pairs (or a single very large value). The tracer allocates a hash-map entry for each pair on every request, causing unbounded CPU and memory consumption and enabling a remote Denial of Service against any HTTP service that has the baggage propagation style enabled. The baggage propagation style is enabled by default in most affected tracers, so any internet-facing service that has been instrumented with an affected tracer version is exposed unless the propagation style has been explicitly narrowed.

Patches

This is resolved in version 1.62.0 and later of the dd-trace-java library.

Workarounds

If users cannot upgrade immediately: 1. Disable baggage extraction by removing baggage from DD_TRACE_PROPAGATION_STYLE (or DD_TRACE_PROPAGATION_STYLE_EXTRACT if set independently). 2. Cap the maximum HTTP request header size at an upstream proxy or web server (for example, Apache LimitRequestFieldSize, Nginx large_client_header_buffers, Envoy max_request_headers_kb).

Resources

Related upstream advisories: opentelemetry-go GHSA-mh2q-q3fh-2475 opentelemetry-dotnet GHSA-g94r-2vxg-569j

Show details on source website

{
  "affected": [
    {
      "package": {
        "ecosystem": "Maven",
        "name": "com.datadoghq:dd-java-agent"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "1.62.0"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    }
  ],
  "aliases": [
    "CVE-2026-50270"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-770",
      "CWE-400"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2026-07-15T22:53:16Z",
    "nvd_published_at": null,
    "severity": "HIGH"
  },
  "details": "### Impact\nDatadog tracing libraries that implement W3C baggage propagation parse incoming baggage HTTP headers without enforcing item-count or byte-size limits on the extract path. The DD_TRACE_BAGGAGE_MAX_ITEMS (default 64) and DD_TRACE_BAGGAGE_MAX_BYTES (default 8192) limits were applied only to baggage injection, not extraction. A remote, unauthenticated attacker can send a request whose baggage header contains an arbitrarily large number of comma-separated key-value pairs (or a single very large value). The tracer allocates a hash-map entry for each pair on every request, causing unbounded CPU and memory consumption and enabling a remote Denial of Service against any HTTP service that has the baggage propagation style enabled. The baggage propagation style is enabled by default in most affected tracers, so any internet-facing service that has been instrumented with an affected tracer version is exposed unless the propagation style has been explicitly narrowed.\n\n\n### Patches\nThis is resolved in version 1.62.0 and later of the `dd-trace-java` library.\n\n### Workarounds\nIf users cannot upgrade immediately:\n1. Disable `baggage` extraction by removing `baggage` from `DD_TRACE_PROPAGATION_STYLE` (or `DD_TRACE_PROPAGATION_STYLE_EXTRACT` if set independently).\n2. Cap the maximum HTTP request header size at an upstream proxy or web server (for example, Apache `LimitRequestFieldSize`, Nginx `large_client_header_buffers`, Envoy `max_request_headers_kb`).\n\n\n### Resources\nRelated upstream advisories:\n[opentelemetry-go GHSA-mh2q-q3fh-2475](https://github.com/open-telemetry/opentelemetry-go/security/advisories/GHSA-mh2q-q3fh-2475)\n[opentelemetry-dotnet GHSA-g94r-2vxg-569j](https://github.com/open-telemetry/opentelemetry-dotnet/security/advisories/GHSA-g94r-2vxg-569j)",
  "id": "GHSA-74xj-wh4w-vqxc",
  "modified": "2026-07-15T22:53:16Z",
  "published": "2026-07-15T22:53:16Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/DataDog/dd-trace-java/security/advisories/GHSA-74xj-wh4w-vqxc"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/DataDog/dd-trace-java"
    }
  ],
  "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": "dd-trace-java: Improper parsing of W3C baggage headers may lead to DoS"
}

GHSA-75M2-JHH5-J5G2

Vulnerability from github – Published: 2025-04-07 18:57 – Updated: 2025-04-08 17:50
VLAI
Summary
Apollo Router Query Planner Vulnerable to Excessive Resource Consumption via Named Fragment Expansion
Details

Impact

Summary

A vulnerability in Apollo Router allowed queries with deeply nested and reused named fragments to be prohibitively expensive to query plan, specifically during named fragment expansion. This could lead to excessive resource consumption and denial of service.

Details

Named fragments were being expanded once per fragment spread during query planning, leading to exponential resource usage when deeply nested and reused fragments were involved.

Fix/Mitigation

A new Query Fragment Expansion Limit metric has been introduced: - This metric computes the number of selections a query would have if its fragment spreads were fully expanded. - The metric is checked against a limit to prevent excessive computation.

Patches

This has been remediated in apollo-router versions 1.61.2 and 2.1.1.

Workarounds

The only known workaround is "Safelisting" or "Safelisting with IDs only" per Safelisting with Persisted Queries - Apollo GraphQL Docs.

References

Query Planning Documentation

Acknowledgements

We appreciate the efforts of the security community in identifying and improving the performance and security of query planning mechanisms.

Show details on source website

{
  "affected": [
    {
      "package": {
        "ecosystem": "crates.io",
        "name": "apollo-router"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "1.61.2"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "crates.io",
        "name": "apollo-router"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.0.0-alpha.0"
            },
            {
              "fixed": "2.1.1"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    }
  ],
  "aliases": [
    "CVE-2025-32034"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-770"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2025-04-07T18:57:56Z",
    "nvd_published_at": "2025-04-07T21:15:43Z",
    "severity": "HIGH"
  },
  "details": "# Impact\n\n## Summary\n\nA vulnerability in Apollo Router allowed queries with deeply nested and reused named fragments to be prohibitively expensive to query plan, specifically during named fragment expansion. This could lead to excessive resource consumption and denial of service.\n\n## Details\n\nNamed fragments were being expanded once per fragment spread during query planning, leading to exponential resource usage when deeply nested and reused fragments were involved.\n\n## Fix/Mitigation\n\nA new **Query Fragment Expansion Limit** metric has been introduced:\n  - This metric computes the number of selections a query would have if its fragment spreads were fully expanded.\n  - The metric is checked against a limit to prevent excessive computation.\n\n# Patches\n\nThis has been remediated in `apollo-router` versions 1.61.2 and 2.1.1.\n\n# Workarounds\n\nThe only known workaround is \"Safelisting\" or \"Safelisting with IDs only\" per [Safelisting with Persisted Queries - Apollo GraphQL Docs](https://www.apollographql.com/docs/graphos/routing/security/persisted-queries#router-security-levels).\n\n# References\n\n[Query Planning Documentation](https://www.apollographql.com/docs/graphos/reference/federation/query-plans)\n\n## Acknowledgements\n\nWe appreciate the efforts of the security community in identifying and improving the performance and security of query planning mechanisms.",
  "id": "GHSA-75m2-jhh5-j5g2",
  "modified": "2025-04-08T17:50:03Z",
  "published": "2025-04-07T18:57:56Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/apollographql/router/security/advisories/GHSA-75m2-jhh5-j5g2"
    },
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2025-32034"
    },
    {
      "type": "WEB",
      "url": "https://github.com/apollographql/router/commit/ab6675a63174715ea6ff50881fc957831d4e9564"
    },
    {
      "type": "WEB",
      "url": "https://github.com/apollographql/router/commit/bba032e183b861348a466d3123c7137a1ae18952"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/apollographql/router"
    }
  ],
  "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": "Apollo Router Query Planner Vulnerable to Excessive Resource Consumption via Named Fragment Expansion"
}

GHSA-762Q-JQWQ-G847

Vulnerability from github – Published: 2024-08-12 15:30 – Updated: 2025-11-04 00:31
VLAI
Details

In the Linux kernel, the following vulnerability has been resolved:

mm: huge_memory: use !CONFIG_64BIT to relax huge page alignment on 32 bit machines

Yves-Alexis Perez reported commit 4ef9ad19e176 ("mm: huge_memory: don't force huge page alignment on 32 bit") didn't work for x86_32 [1]. It is because x86_32 uses CONFIG_X86_32 instead of CONFIG_32BIT.

!CONFIG_64BIT should cover all 32 bit machines.

[1] https://lore.kernel.org/linux-mm/CAHbLzkr1LwH3pcTgM+aGQ31ip2bKqiqEQ8=FQB+t2c3dhNKNHA@mail.gmail.com/

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2024-42258"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-770"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2024-08-12T15:15:20Z",
    "severity": "MODERATE"
  },
  "details": "In the Linux kernel, the following vulnerability has been resolved:\n\nmm: huge_memory: use !CONFIG_64BIT to relax huge page alignment on 32 bit machines\n\nYves-Alexis Perez reported commit 4ef9ad19e176 (\"mm: huge_memory: don\u0027t\nforce huge page alignment on 32 bit\") didn\u0027t work for x86_32 [1].  It is\nbecause x86_32 uses CONFIG_X86_32 instead of CONFIG_32BIT.\n\n!CONFIG_64BIT should cover all 32 bit machines.\n\n[1] https://lore.kernel.org/linux-mm/CAHbLzkr1LwH3pcTgM+aGQ31ip2bKqiqEQ8=FQB+t2c3dhNKNHA@mail.gmail.com/",
  "id": "GHSA-762q-jqwq-g847",
  "modified": "2025-11-04T00:31:11Z",
  "published": "2024-08-12T15:30:54Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2024-42258"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/7e1f4efb8d6140b2ec79bf760c43e1fc186e8dfc"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/89f2914dd4b47d2fad3deef0d700f9526d98d11f"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/a5c399fe433a115e9d3693169b5f357f3194af0a"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/d9592025000b3cf26c742f3505da7b83aedc26d5"
    },
    {
      "type": "WEB",
      "url": "https://lists.debian.org/debian-lts-announce/2025/01/msg00001.html"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H",
      "type": "CVSS_V3"
    }
  ]
}

GHSA-762V-RQ7Q-FF97

Vulnerability from github – Published: 2024-10-29 09:30 – Updated: 2024-11-04 21:25
VLAI
Summary
Mattermost Server vulnerable to application crash from attacker-generated large response
Details

Mattermost versions 9.10.x <= 9.10.2, 9.11.x <= 9.11.1 and 9.5.x <= 9.5.9 fail to prevent detailed error messages from being displayed in Playbooks which allows an attacker to generate a large response and cause an amplified GraphQL response which in turn could cause the application to crash by sending a specially crafted request to Playbooks.

Show details on source website

{
  "affected": [
    {
      "package": {
        "ecosystem": "Go",
        "name": "github.com/mattermost/mattermost/server/v8"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "8.0.0-20240926115259-20ed58906adc"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    }
  ],
  "aliases": [
    "CVE-2024-47401"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-770"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2024-10-29T16:13:16Z",
    "nvd_published_at": "2024-10-29T09:15:07Z",
    "severity": "MODERATE"
  },
  "details": "Mattermost versions 9.10.x \u003c= 9.10.2, 9.11.x \u003c= 9.11.1 and 9.5.x \u003c= 9.5.9 fail to\u00a0prevent detailed error messages from being displayed\u00a0in Playbooks which allows an attacker to generate a large response and cause an amplified GraphQL response which in turn could cause the application to crash by sending a specially crafted request to Playbooks.",
  "id": "GHSA-762v-rq7q-ff97",
  "modified": "2024-11-04T21:25:24Z",
  "published": "2024-10-29T09:30:51Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2024-47401"
    },
    {
      "type": "ADVISORY",
      "url": "https://github.com/advisories/GHSA-762v-rq7q-ff97"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/mattermost/mattermost"
    },
    {
      "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:L",
      "type": "CVSS_V3"
    },
    {
      "score": "CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:N/VI:N/VA:L/SC:N/SI:N/SA:N",
      "type": "CVSS_V4"
    }
  ],
  "summary": "Mattermost Server vulnerable to application crash from attacker-generated large response"
}

GHSA-764Q-GPMW-JCCJ

Vulnerability from github – Published: 2024-04-16 00:30 – Updated: 2024-04-16 00:30
VLAI
Details

In lunary-ai/lunary version 1.0.0, an authorization flaw exists that allows unauthorized radar creation. The vulnerability stems from the lack of server-side checks to verify if a user is on a free account during the radar creation process, which is only enforced in the web UI. As a result, attackers can bypass the intended account upgrade requirement by directly sending crafted requests to the server, enabling the creation of an unlimited number of radars without payment.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2024-1666"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-770"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2024-04-16T00:15:10Z",
    "severity": "HIGH"
  },
  "details": "In lunary-ai/lunary version 1.0.0, an authorization flaw exists that allows unauthorized radar creation. The vulnerability stems from the lack of server-side checks to verify if a user is on a free account during the radar creation process, which is only enforced in the web UI. As a result, attackers can bypass the intended account upgrade requirement by directly sending crafted requests to the server, enabling the creation of an unlimited number of radars without payment.",
  "id": "GHSA-764q-gpmw-jccj",
  "modified": "2024-04-16T00:30:33Z",
  "published": "2024-04-16T00:30:33Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2024-1666"
    },
    {
      "type": "WEB",
      "url": "https://github.com/lunary-ai/lunary/commit/c57cd50fa0477fd2a2efe60810c0099eebd66f54"
    },
    {
      "type": "WEB",
      "url": "https://huntr.com/bounties/0f310501-b5b0-4be0-ae38-d6b836f71ff0"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:H/A:N",
      "type": "CVSS_V3"
    }
  ]
}

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.