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Common Weakness Enumeration

CWE-770

Allowed

Allocation of Resources Without Limits or Throttling

Abstraction: Base · Status: Incomplete

API response cwe.mitre.org

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.

3611 vulnerabilities reference this CWE, most recent first.

GHSA-2J26-FRM8-CMJ9

Vulnerability from github – Published: 2026-03-23 21:15 – Updated: 2026-05-13 16:16
VLAI
Summary
Rails Active Support has a possible DoS vulnerability in its number helpers
Details

Impact

Active Support number helpers accept strings containing scientific notation (e.g. 1e10000), which when converted to a string could be expanded into extremely large decimal representations. This can cause excessive memory allocation and CPU consumption when the expanded number is formatted, possibly resulting in a DoS vulnerability.

Releases

The fixed releases are available at the normal locations.

Credit

This issue was responsibly reported by Hackerone researcher manun.

Severity
6.6 (Medium)
CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N/E:U
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{
  "affected": [
    {
      "package": {
        "ecosystem": "RubyGems",
        "name": "activesupport"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "8.1.0.beta1"
            },
            {
              "fixed": "8.1.2.1"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "RubyGems",
        "name": "activesupport"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "8.0.0.beta1"
            },
            {
              "fixed": "8.0.4.1"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "RubyGems",
        "name": "activesupport"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "7.2.3.1"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    }
  ],
  "aliases": [
    "CVE-2026-33176"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-400",
      "CWE-770"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2026-03-23T21:15:16Z",
    "nvd_published_at": "2026-03-24T00:16:28Z",
    "severity": "MODERATE"
  },
  "details": "### Impact\nActive Support number helpers accept strings containing scientific notation (e.g. `1e10000`), which when converted to a string could be expanded into extremely large decimal representations. This can cause excessive memory allocation and CPU consumption when the expanded number is formatted, possibly resulting in a DoS vulnerability.\n\n### Releases\nThe fixed releases are available at the normal locations.\n\n### Credit\nThis issue was responsibly reported by Hackerone researcher [manun](https://hackerone.com/manun).",
  "id": "GHSA-2j26-frm8-cmj9",
  "modified": "2026-05-13T16:16:19Z",
  "published": "2026-03-23T21:15:16Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/rails/rails/security/advisories/GHSA-2j26-frm8-cmj9"
    },
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-33176"
    },
    {
      "type": "WEB",
      "url": "https://github.com/rails/rails/commit/19dbab51ca086a657bb86458042bc44314916bcb"
    },
    {
      "type": "WEB",
      "url": "https://github.com/rails/rails/commit/ebd6be18120d1136511eb516338e27af25ac0a1a"
    },
    {
      "type": "WEB",
      "url": "https://github.com/rails/rails/commit/ee2c59e730e5b8faed502cd2c573109df093f856"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/rails/rails"
    },
    {
      "type": "WEB",
      "url": "https://github.com/rails/rails/releases/tag/v7.2.3.1"
    },
    {
      "type": "WEB",
      "url": "https://github.com/rails/rails/releases/tag/v8.0.4.1"
    },
    {
      "type": "WEB",
      "url": "https://github.com/rails/rails/releases/tag/v8.1.2.1"
    },
    {
      "type": "WEB",
      "url": "https://github.com/rubysec/ruby-advisory-db/blob/master/gems/activesupport/CVE-2026-33176.yml"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N/E:U",
      "type": "CVSS_V4"
    }
  ],
  "summary": "Rails Active Support has a possible DoS vulnerability in its number helpers"
}

GHSA-2J7Q-R439-8QQQ

Vulnerability from github – Published: 2026-05-27 15:33 – Updated: 2026-05-27 15:33
VLAI
Details

IBM Db2 11.5.0 through 11.5.9, and 12.1.0 through 12.1.4 is vulnerable to a denial of service when a specially crafted query is run with range partitioned tables.

Severity
5.5 (Medium)
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
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{
  "affected": [],
  "aliases": [
    "CVE-2026-6053"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-770"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2026-05-27T14:17:34Z",
    "severity": "MODERATE"
  },
  "details": "IBM Db2 11.5.0 through 11.5.9, and 12.1.0 through 12.1.4 is vulnerable to a denial of service when a specially crafted query is run with range partitioned tables.",
  "id": "GHSA-2j7q-r439-8qqq",
  "modified": "2026-05-27T15:33:24Z",
  "published": "2026-05-27T15:33:24Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-6053"
    },
    {
      "type": "WEB",
      "url": "https://www.ibm.com/support/pages/node/7273556"
    }
  ],
  "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-2J86-H6VF-9889

Vulnerability from github – Published: 2023-05-09 18:30 – Updated: 2024-04-04 03:56
VLAI
Details

An issue was discovered on GL.iNet devices before 3.216. There is an arbitrary file write in which an empty file can be created anywhere on the filesystem. This is caused by a command injection vulnerability with a filter applied.

Severity
7.5 (High)
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:H/A:N
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{
  "affected": [],
  "aliases": [
    "CVE-2023-31472"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-770"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2023-05-09T18:15:14Z",
    "severity": "HIGH"
  },
  "details": "An issue was discovered on GL.iNet devices before 3.216. There is an arbitrary file write in which an empty file can be created anywhere on the filesystem. This is caused by a command injection vulnerability with a filter applied.",
  "id": "GHSA-2j86-h6vf-9889",
  "modified": "2024-04-04T03:56:54Z",
  "published": "2023-05-09T18:30:38Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2023-31472"
    },
    {
      "type": "WEB",
      "url": "https://github.com/gl-inet/CVE-issues/blob/main/3.215/Arbitrary_File_Creation.md"
    },
    {
      "type": "WEB",
      "url": "https://www.gl-inet.com"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:H/A:N",
      "type": "CVSS_V3"
    }
  ]
}

GHSA-2JC5-XHX8-QJ6H

Vulnerability from github – Published: 2026-06-26 17:22 – Updated: 2026-06-26 17:22
VLAI
Summary
fluent-plugin-opentelemetry Has Denial of Service (DoS) via Large Payloads and Decompression Bombs in `in_opentelemetry`
Details

The fluent-plugin-opentelemetry plugin (specifically the in_opentelemetry HTTP input) lacked strict size limits on incoming requests. It was discovered that the plugin read the entire request body and decompressed payloads into memory without enforcing maximum size thresholds.

If the OpenTelemetry ingestion endpoint is exposed to untrusted networks, an attacker can send an excessively large HTTP request or a maliciously crafted, highly compressed payload. When the plugin attempts to read or decompress this payload, it will expand to an excessive size and it will consume significant system resources.

Impact

This vulnerability allows for a Denial of Service (DoS) attack via memory exhaustion. The rapid memory consumption during decompression can easily lead to an Out-of-Memory kill of the Fluentd process by the operating system. This results in the disruption of all log collection and forwarding capabilities on the affected node.

Patches

v0.5.3

Workarounds

If an immediate upgrade is not possible, users are strongly advised to apply the following mitigations:

  1. Restrict Network Access
  2. Ensure that the OpenTelemetry ingestion ports (default 4318) are deployed within a closed, trusted network. Use firewall rules (e.g., iptables, AWS Security Groups) to block access from untrusted networks or instances.
  3. Use a Reverse Proxy
  4. If you must expose HTTP ingestion to external sources, place a robust reverse proxy (such as Nginx) in front of Fluentd. Configure the proxy to handle the gzip decompression and enforce strict limits on both compressed and uncompressed body sizes before passing the traffic to Fluentd.
Severity
5.3 (Medium)
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:L
Show details on source website
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{
  "affected": [
    {
      "database_specific": {
        "last_known_affected_version_range": "\u003c= 0.5.2"
      },
      "package": {
        "ecosystem": "RubyGems",
        "name": "fluent-plugin-opentelemetry"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "0.5.3"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    }
  ],
  "aliases": [
    "CVE-2026-44163"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-770"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2026-06-26T17:22:37Z",
    "nvd_published_at": null,
    "severity": "MODERATE"
  },
  "details": "The `fluent-plugin-opentelemetry` plugin (specifically the `in_opentelemetry` HTTP input) lacked strict size limits on incoming requests.\nIt was discovered that the plugin read the entire request body and decompressed payloads into memory without enforcing maximum size thresholds.\n\nIf the OpenTelemetry ingestion endpoint is exposed to untrusted networks, an attacker can send an excessively large HTTP request or a maliciously crafted, highly compressed payload.\nWhen the plugin attempts to read or decompress this payload, it will expand to an excessive size and it will consume significant system resources.\n\n### Impact\nThis vulnerability allows for a **Denial of Service (DoS)** attack via memory exhaustion. \nThe rapid memory consumption during decompression can easily lead to an Out-of-Memory kill of the Fluentd process by the operating system.\nThis results in the disruption of all log collection and forwarding capabilities on the affected node.\n\n### Patches\nv0.5.3\n\n### Workarounds\nIf an immediate upgrade is not possible, users are strongly advised to apply the following mitigations:\n\n1. Restrict Network Access\n   * Ensure that the OpenTelemetry ingestion ports (default `4318`) are deployed within a closed, trusted network. Use firewall rules (e.g., iptables, AWS Security Groups) to block access from untrusted networks or instances.\n2. Use a Reverse Proxy\n   * If you must expose HTTP ingestion to external sources, place a robust reverse proxy (such as Nginx) in front of Fluentd. Configure the proxy to handle the gzip decompression and enforce strict limits on both compressed and uncompressed body sizes before passing the traffic to Fluentd.",
  "id": "GHSA-2jc5-xhx8-qj6h",
  "modified": "2026-06-26T17:22:37Z",
  "published": "2026-06-26T17:22:37Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/fluent-plugins-nursery/fluent-plugin-opentelemetry/security/advisories/GHSA-2jc5-xhx8-qj6h"
    },
    {
      "type": "WEB",
      "url": "https://github.com/fluent-plugins-nursery/fluent-plugin-opentelemetry/commit/ce6c1f2a7741592c8a79afbe75fded9e8ebfa92d"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/fluent-plugins-nursery/fluent-plugin-opentelemetry"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:L",
      "type": "CVSS_V3"
    }
  ],
  "summary": "fluent-plugin-opentelemetry Has Denial of Service (DoS) via Large Payloads and Decompression Bombs in `in_opentelemetry`"
}

GHSA-2M39-62FM-Q8R3

Vulnerability from github – Published: 2018-08-15 13:22 – Updated: 2023-01-31 01:55
VLAI
Summary
Regular Expression Denial of Service in sshpk
Details

Versions of sshpk before 1.13.2 or 1.14.1 are vulnerable to regular expression denial of service when parsing crafted invalid public keys.

Recommendation

Update to version 1.13.2, 1.14.1 or later.

Severity
7.5 (High)
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
Show details on source website
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{
  "affected": [
    {
      "package": {
        "ecosystem": "npm",
        "name": "sshpk"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "1.13.2"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    }
  ],
  "aliases": [
    "CVE-2018-3737"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-185",
      "CWE-770"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2020-06-16T20:52:29Z",
    "nvd_published_at": "2018-06-07T02:29:00Z",
    "severity": "HIGH"
  },
  "details": "Versions of `sshpk` before 1.13.2 or 1.14.1 are vulnerable to regular expression denial of service when parsing crafted invalid public keys.\n\n\n## Recommendation\n\nUpdate to version 1.13.2, 1.14.1 or later.",
  "id": "GHSA-2m39-62fm-q8r3",
  "modified": "2023-01-31T01:55:03Z",
  "published": "2018-08-15T13:22:23Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2018-3737"
    },
    {
      "type": "WEB",
      "url": "https://github.com/joyent/node-sshpk/commit/46065d38a5e6d1bccf86d3efb2fb83c14e3f9957"
    },
    {
      "type": "WEB",
      "url": "https://hackerone.com/reports/319593"
    },
    {
      "type": "ADVISORY",
      "url": "https://github.com/advisories/GHSA-2m39-62fm-q8r3"
    },
    {
      "type": "WEB",
      "url": "https://github.com/joyent/node-sshpk/blob/v1.13.1/lib/formats/ssh.js#L17"
    },
    {
      "type": "WEB",
      "url": "https://www.npmjs.com/advisories/606"
    }
  ],
  "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": "Regular Expression Denial of Service in sshpk"
}

GHSA-2M67-WJPJ-XHG9

Vulnerability from github – Published: 2026-04-04 04:17 – Updated: 2026-04-08 22:42
VLAI
Summary
Jackson Core: Document length constraint bypass in blocking, async, and DataInput parsers
Details

Summary

Jackson Core 3.x does not consistently enforce StreamReadConstraints.maxDocumentLength. Oversized JSON documents can be accepted without a StreamConstraintsException in multiple parser entry points, which allows configured size limits to be bypassed and weakens denial-of-service protections.

Details

Three code paths where maxDocumentLength is not fully enforced:

1. Blocking parsers skip validation of the final in-memory buffer

Blocking parsers validate only previously processed buffers, not the final in-memory buffer:

  • ReaderBasedJsonParser.java:255
  • UTF8StreamJsonParser.java:208

Relevant code:

_currInputProcessed += bufSize;
_streamReadConstraints.validateDocumentLength(_currInputProcessed);

This means the check occurs only when a completed buffer is rolled over. If an oversized document is fully contained in the final buffer, parsing can complete without any document-length exception.

2. Async parsers skip validation of the final chunk on end-of-input

Async parsers validate previously processed chunks, but do not validate the final chunk on end-of-input:

  • NonBlockingByteArrayJsonParser.java:49
  • NonBlockingByteBufferJsonParser.java:57
  • NonBlockingUtf8JsonParserBase.java:75

Relevant code:

_currInputProcessed += _origBufferLen;
_streamReadConstraints.validateDocumentLength(_currInputProcessed);

public void endOfInput() {
    _endOfInput = true;
}

endOfInput() marks EOF but does not perform a final validateDocumentLength(...) call, so an oversized last chunk is accepted.

3. DataInput parser path does not enforce maxDocumentLength at all

  • JsonFactory.java:457

Relevant construction path:

int firstByte = ByteSourceJsonBootstrapper.skipUTF8BOM(input);
return new UTF8DataInputJsonParser(readCtxt, ioCtxt,
        readCtxt.getStreamReadFeatures(_streamReadFeatures),
        readCtxt.getFormatReadFeatures(_formatReadFeatures),
        input, can, firstByte);

UTF8DataInputJsonParser does not call StreamReadConstraints.validateDocumentLength(...), so maxDocumentLength is effectively disabled for createParser(..., DataInput) users.

Note: This issue appears distinct from the recently published nesting-depth and number-length constraint advisories because it affects document-length enforcement.

PoC

Async path reproducer

import java.nio.charset.StandardCharsets;
import tools.jackson.core.JsonParser;
import tools.jackson.core.ObjectReadContext;
import tools.jackson.core.StreamReadConstraints;
import tools.jackson.core.async.ByteArrayFeeder;
import tools.jackson.core.json.JsonFactory;

public class Poc {
    public static void main(String[] args) throws Exception {
        JsonFactory factory = JsonFactory.builder()
                .streamReadConstraints(StreamReadConstraints.builder()
                        .maxDocumentLength(10L)
                        .build())
                .build();

        byte[] doc = "{\"a\":1,\"b\":2}".getBytes(StandardCharsets.UTF_8);

        try (JsonParser p = factory.createNonBlockingByteArrayParser(ObjectReadContext.empty())) {
            ByteArrayFeeder feeder = (ByteArrayFeeder) p.nonBlockingInputFeeder();
            feeder.feedInput(doc, 0, doc.length);
            feeder.endOfInput();

            while (p.nextToken() != null) { }
        }

        System.out.println("Parsed successfully");
    }
}
  • Expected result: Parsing should fail because the configured document-length limit is 10, while the input is longer than 10 bytes.
  • Actual result: The document is accepted and parsing completes.

Blocking path reproducer

import java.io.ByteArrayInputStream;
import java.nio.charset.StandardCharsets;
import tools.jackson.core.JsonParser;
import tools.jackson.core.StreamReadConstraints;
import tools.jackson.core.json.JsonFactory;

public class Poc2 {
    public static void main(String[] args) throws Exception {
        JsonFactory factory = JsonFactory.builder()
                .streamReadConstraints(StreamReadConstraints.builder()
                        .maxDocumentLength(10L)
                        .build())
                .build();

        byte[] doc = "{\"a\":1,\"b\":2}".getBytes(StandardCharsets.UTF_8);

        try (JsonParser p = factory.createParser(new ByteArrayInputStream(doc))) {
            while (p.nextToken() != null) { }
        }

        System.out.println("Parsed successfully");
    }
}

Impact

Applications that rely on maxDocumentLength as a safety control for untrusted JSON can accept oversized inputs without error. In network-facing services this weakens an explicit denial-of-service protection and can increase CPU and memory consumption by allowing larger-than-configured request bodies to be processed.

Severity
7.5 (High)
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
Show details on source website
To clipboard 

{
  "affected": [
    {
      "database_specific": {
        "last_known_affected_version_range": "\u003c= 3.1.0"
      },
      "package": {
        "ecosystem": "Maven",
        "name": "tools.jackson.core:jackson-core"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "3.0.0"
            },
            {
              "fixed": "3.1.1"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    }
  ],
  "aliases": [],
  "database_specific": {
    "cwe_ids": [
      "CWE-770"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2026-04-04T04:17:07Z",
    "nvd_published_at": null,
    "severity": "HIGH"
  },
  "details": "## Summary\n\nJackson Core 3.x does not consistently enforce `StreamReadConstraints.maxDocumentLength`. Oversized JSON documents can be accepted without a `StreamConstraintsException` in multiple parser entry points, which allows configured size limits to be bypassed and weakens denial-of-service protections.\n\n## Details\n\nThree code paths where `maxDocumentLength` is not fully enforced:\n\n### 1. Blocking parsers skip validation of the final in-memory buffer\n\nBlocking parsers validate only previously processed buffers, not the final in-memory buffer:\n\n- `ReaderBasedJsonParser.java:255`\n- `UTF8StreamJsonParser.java:208`\n\nRelevant code:\n\n```java\n_currInputProcessed += bufSize;\n_streamReadConstraints.validateDocumentLength(_currInputProcessed);\n```\n\nThis means the check occurs only when a completed buffer is rolled over. If an oversized document is fully contained in the final buffer, parsing can complete without any document-length exception.\n\n### 2. Async parsers skip validation of the final chunk on end-of-input\n\nAsync parsers validate previously processed chunks, but do not validate the final chunk on end-of-input:\n\n- `NonBlockingByteArrayJsonParser.java:49`\n- `NonBlockingByteBufferJsonParser.java:57`\n- `NonBlockingUtf8JsonParserBase.java:75`\n\nRelevant code:\n\n```java\n_currInputProcessed += _origBufferLen;\n_streamReadConstraints.validateDocumentLength(_currInputProcessed);\n\npublic void endOfInput() {\n    _endOfInput = true;\n}\n```\n\n`endOfInput()` marks EOF but does not perform a final `validateDocumentLength(...)` call, so an oversized last chunk is accepted.\n\n### 3. DataInput parser path does not enforce `maxDocumentLength` at all\n\n- `JsonFactory.java:457`\n\nRelevant construction path:\n\n```java\nint firstByte = ByteSourceJsonBootstrapper.skipUTF8BOM(input);\nreturn new UTF8DataInputJsonParser(readCtxt, ioCtxt,\n        readCtxt.getStreamReadFeatures(_streamReadFeatures),\n        readCtxt.getFormatReadFeatures(_formatReadFeatures),\n        input, can, firstByte);\n```\n\n`UTF8DataInputJsonParser` does not call `StreamReadConstraints.validateDocumentLength(...)`, so `maxDocumentLength` is effectively disabled for `createParser(..., DataInput)` users.\n\n\u003e **Note:** This issue appears distinct from the recently published nesting-depth and number-length constraint advisories because it affects document-length enforcement.\n\n## PoC\n\n### Async path reproducer\n\n```java\nimport java.nio.charset.StandardCharsets;\nimport tools.jackson.core.JsonParser;\nimport tools.jackson.core.ObjectReadContext;\nimport tools.jackson.core.StreamReadConstraints;\nimport tools.jackson.core.async.ByteArrayFeeder;\nimport tools.jackson.core.json.JsonFactory;\n\npublic class Poc {\n    public static void main(String[] args) throws Exception {\n        JsonFactory factory = JsonFactory.builder()\n                .streamReadConstraints(StreamReadConstraints.builder()\n                        .maxDocumentLength(10L)\n                        .build())\n                .build();\n\n        byte[] doc = \"{\\\"a\\\":1,\\\"b\\\":2}\".getBytes(StandardCharsets.UTF_8);\n\n        try (JsonParser p = factory.createNonBlockingByteArrayParser(ObjectReadContext.empty())) {\n            ByteArrayFeeder feeder = (ByteArrayFeeder) p.nonBlockingInputFeeder();\n            feeder.feedInput(doc, 0, doc.length);\n            feeder.endOfInput();\n\n            while (p.nextToken() != null) { }\n        }\n\n        System.out.println(\"Parsed successfully\");\n    }\n}\n```\n\n- **Expected result:** Parsing should fail because the configured document-length limit is 10, while the input is longer than 10 bytes.\n- **Actual result:** The document is accepted and parsing completes.\n\n### Blocking path reproducer\n\n```java\nimport java.io.ByteArrayInputStream;\nimport java.nio.charset.StandardCharsets;\nimport tools.jackson.core.JsonParser;\nimport tools.jackson.core.StreamReadConstraints;\nimport tools.jackson.core.json.JsonFactory;\n\npublic class Poc2 {\n    public static void main(String[] args) throws Exception {\n        JsonFactory factory = JsonFactory.builder()\n                .streamReadConstraints(StreamReadConstraints.builder()\n                        .maxDocumentLength(10L)\n                        .build())\n                .build();\n\n        byte[] doc = \"{\\\"a\\\":1,\\\"b\\\":2}\".getBytes(StandardCharsets.UTF_8);\n\n        try (JsonParser p = factory.createParser(new ByteArrayInputStream(doc))) {\n            while (p.nextToken() != null) { }\n        }\n\n        System.out.println(\"Parsed successfully\");\n    }\n}\n```\n\n## Impact\n\nApplications that rely on `maxDocumentLength` as a safety control for untrusted JSON can accept oversized inputs without error. In network-facing services this weakens an explicit denial-of-service protection and can increase CPU and memory consumption by allowing larger-than-configured request bodies to be processed.",
  "id": "GHSA-2m67-wjpj-xhg9",
  "modified": "2026-04-08T22:42:15Z",
  "published": "2026-04-04T04:17:07Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/FasterXML/jackson-core/security/advisories/GHSA-2m67-wjpj-xhg9"
    },
    {
      "type": "WEB",
      "url": "https://github.com/FasterXML/jackson-core/commit/74c9ee255d1534c179bc7d3de48941bf39a9079c"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/FasterXML/jackson-core"
    }
  ],
  "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": "Jackson Core: Document length constraint bypass in blocking, async, and DataInput parsers"
}

GHSA-2M8G-3CMR-WG3W

Vulnerability from github – Published: 2026-09-01 19:24 – Updated: 2026-09-01 19:24
VLAI
Summary
Django REST framework: Potential bypass of Django `DATA_UPLOAD_MAX_MEMORY_SIZE` when parsing oversized JSON and urlencoded request bodies via DRF `request.data`
Details

Summary

While investigating Django REST Framework's request parsing behavior, I identified that DRF's high-level request.data parsing appears to bypass Django's configured DATA_UPLOAD_MAX_MEMORY_SIZE protection for application/json and application/x-www-form-urlencoded request bodies.

In the tested configurations, Django correctly raises RequestDataTooBig when applications access request.body or Django's native request.POST, but DRF successfully parses the same oversized payloads through request.data.

This behavior appears to occur because DRF passes the underlying HttpRequest object directly to parsers, which consume the request stream through Django's lower-level streaming interface rather than the guarded request.body path.

I am reporting this privately because I am unsure whether this behavior is considered part of DRF's intended security boundary, but it appears to bypass a documented Django request-size protection for common DRF request parsing paths and may have availability implications.

What I Verified

I verified the behavior locally using the following combinations:

  • Django 6.0.7 + DRF 3.17.1 → Affected
  • Django 6.0.7 + DRF current upstream main → Affected

For both versions, the observed behavior was:

Django request.body
→ RequestDataTooBig

Django request.POST (application/x-www-form-urlencoded)
→ RequestDataTooBig

Django request.read()
→ Reads the entire oversized request body

DRF request.data
→ Successfully parses oversized JSON and urlencoded request bodies

I also confirmed that:

  • multipart/form-data remains protected because DRF delegates multipart parsing to Django's multipart parser.
  • The behavior reproduces on both direct WSGI and ASGI servers without a reverse proxy or external request-size middleware.

Technical Details

The relevant execution flow is:

APIView

↓

rest_framework.request.Request

↓

request.data

↓

Request._load_data_and_files()

↓

Request._parse()

↓

Request._load_stream()

↓

self._stream = self._request

↓

JSONParser.parse(...)
or
FormParser.parse(...)

↓

stream.read() / json.load(...)

The important implementation detail is that DRF assigns the original Django HttpRequest object as the parser stream.

Unlike request.body and Django's native form parsing, consuming the stream through HttpRequest.read() does not trigger Django's RequestDataTooBig protection.

As a result, DRF's built-in parsers successfully consume oversized request bodies that Django itself would reject through its higher-level request interfaces.

Reproduction Steps

Environment

Python 3.13

Django 6.0.7

Django REST Framework 3.17.1 (also reproduced on current upstream main)

Configure:

DATA_UPLOAD_MAX_MEMORY_SIZE = 10

Create a simple DRF API view:

from rest_framework.views import APIView
from rest_framework.response import Response

class DemoView(APIView):
    def post(self, request):
        return Response(request.data)

Start the application.

Send an oversized JSON request:

POST /demo
Content-Type: application/json
Content-Length: >10 bytes

Example:

{
  "value": "AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA..."
}

Observed:

HTTP 200

JSON successfully parsed

Now compare against:

request.body

Observed:

RequestDataTooBig

Likewise, compare against:

request.POST

using

application/x-www-form-urlencoded

Observed:

RequestDataTooBig

This demonstrates different enforcement depending on which request API is used.

Root Cause

Django documents HttpRequest.read() as a streaming interface.

DRF exposes request.data as the primary high-level request parsing API.

Currently, DRF forwards the raw Django request stream directly to parsers before any request-size validation equivalent to Django's request.body path occurs.

Consequently:

  • JSONParser
  • FormParser

fully consume oversized request bodies despite Django's configured request-size limit.

Security Impact

This does not appear to introduce:

  • Authentication bypass
  • Authorization bypass
  • Remote code execution
  • Information disclosure
  • Integrity compromise

However, it may reduce the effectiveness of deployments relying on Django's DATA_UPLOAD_MAX_MEMORY_SIZE to limit request-body resource consumption.

Potential consequences include:

  • Additional memory allocation during JSON parsing
  • Additional CPU usage while decoding large JSON payloads
  • Increased resource consumption when handling oversized request bodies
  • Reduced effectiveness of Django's configured request-size protection for DRF endpoints using request.data

The practical impact depends on deployment configuration, including:

  • upstream request-size limits
  • reverse proxy configuration
  • authentication
  • rate limiting
  • endpoint exposure

Memory Observations

During local testing I observed successful parsing of oversized request bodies despite the configured limit.

Representative measurements showed significantly increased memory allocation while parsing large JSON and urlencoded payloads.

I intentionally did not perform destructive concurrency testing or attempt to exhaust system resources.

Scope

Confirmed affected:

  • application/json
  • application/x-www-form-urlencoded

Confirmed not affected:

  • multipart/form-data

Suggested Fix Direction

One possible approach would be for DRF to enforce Django's configured DATA_UPLOAD_MAX_MEMORY_SIZE before handing the raw request stream to parsers that fully materialize request bodies in memory.

This would preserve Django's configured request-size protection for the common request.data API without requiring broader changes to Django's documented streaming interface.

Versions Tested

Affected:

  • Django 6.0.7 + DRF 3.17.1
  • Django 6.0.7 + DRF current upstream main

I did not perform a complete historical version bisect.

Disclosure

I have not publicly disclosed this behavior.

I am submitting it privately in accordance with the project's security policy because I am unsure whether maintainers consider this part of DRF's intended security boundary.

Note:

Thank you for taking the time to review this report.

If you determine that this behavior should be addressed, I would be happy to help investigate further, develop a fix, add regression tests, and submit a patch if you'd find that helpful.

I have experience as a Python/Django software engineer, security researcher, and open-source contributor, and I'd be glad to contribute if you think that would be useful.

Severity
5.3 (Medium)
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:L
Show details on source website
To clipboard 

{
  "affected": [
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "djangorestframework"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "3.17.2"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    }
  ],
  "aliases": [
    "CVE-2026-73228"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-400",
      "CWE-770"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2026-09-01T19:24:51Z",
    "nvd_published_at": "2026-08-11T19:18:52Z",
    "severity": "MODERATE"
  },
  "details": "## Summary\n\nWhile investigating Django REST Framework\u0027s request parsing behavior, I identified that DRF\u0027s high-level `request.data` parsing appears to bypass Django\u0027s configured `DATA_UPLOAD_MAX_MEMORY_SIZE` protection for `application/json` and `application/x-www-form-urlencoded` request bodies.\n\nIn the tested configurations, Django correctly raises `RequestDataTooBig` when applications access `request.body` or Django\u0027s native `request.POST`, but DRF successfully parses the same oversized payloads through `request.data`.\n\nThis behavior appears to occur because DRF passes the underlying `HttpRequest` object directly to parsers, which consume the request stream through Django\u0027s lower-level streaming interface rather than the guarded `request.body` path.\n\nI am reporting this privately because I am unsure whether this behavior is considered part of DRF\u0027s intended security boundary, but it appears to bypass a documented Django request-size protection for common DRF request parsing paths and may have availability implications.\n\n\n# What I Verified\n\nI verified the behavior locally using the following combinations:\n\n* Django **6.0.7** + DRF **3.17.1** \u2192 **Affected**\n* Django **6.0.7** + DRF **current upstream main** \u2192 **Affected**\n\nFor both versions, the observed behavior was:\n\n```\nDjango request.body\n\u2192 RequestDataTooBig\n\nDjango request.POST (application/x-www-form-urlencoded)\n\u2192 RequestDataTooBig\n\nDjango request.read()\n\u2192 Reads the entire oversized request body\n\nDRF request.data\n\u2192 Successfully parses oversized JSON and urlencoded request bodies\n```\n\nI also confirmed that:\n\n* `multipart/form-data` remains protected because DRF delegates multipart parsing to Django\u0027s multipart parser.\n* The behavior reproduces on both direct WSGI and ASGI servers without a reverse proxy or external request-size middleware.\n\n\n# Technical Details\n\nThe relevant execution flow is:\n\n```\nAPIView\n\n\u2193\n\nrest_framework.request.Request\n\n\u2193\n\nrequest.data\n\n\u2193\n\nRequest._load_data_and_files()\n\n\u2193\n\nRequest._parse()\n\n\u2193\n\nRequest._load_stream()\n\n\u2193\n\nself._stream = self._request\n\n\u2193\n\nJSONParser.parse(...)\nor\nFormParser.parse(...)\n\n\u2193\n\nstream.read() / json.load(...)\n```\n\nThe important implementation detail is that DRF assigns the original Django `HttpRequest` object as the parser stream.\n\nUnlike `request.body` and Django\u0027s native form parsing, consuming the stream through `HttpRequest.read()` does not trigger Django\u0027s `RequestDataTooBig` protection.\n\nAs a result, DRF\u0027s built-in parsers successfully consume oversized request bodies that Django itself would reject through its higher-level request interfaces.\n\n\n# Reproduction Steps\n\n## Environment\n\nPython 3.13\n\nDjango 6.0.7\n\nDjango REST Framework 3.17.1 (also reproduced on current upstream main)\n\nConfigure:\n\n```python\nDATA_UPLOAD_MAX_MEMORY_SIZE = 10\n```\n\nCreate a simple DRF API view:\n\n```python\nfrom rest_framework.views import APIView\nfrom rest_framework.response import Response\n\nclass DemoView(APIView):\n    def post(self, request):\n        return Response(request.data)\n```\n\nStart the application.\n\nSend an oversized JSON request:\n\n```\nPOST /demo\nContent-Type: application/json\nContent-Length: \u003e10 bytes\n```\n\nExample:\n\n```json\n{\n  \"value\": \"AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA...\"\n}\n```\n\nObserved:\n\n```\nHTTP 200\n\nJSON successfully parsed\n```\n\nNow compare against:\n\n```python\nrequest.body\n```\n\nObserved:\n\n```\nRequestDataTooBig\n```\n\nLikewise, compare against:\n\n```python\nrequest.POST\n```\n\nusing\n\n```\napplication/x-www-form-urlencoded\n```\n\nObserved:\n\n```\nRequestDataTooBig\n```\n\nThis demonstrates different enforcement depending on which request API is used.\n\n\n# Root Cause\n\nDjango documents `HttpRequest.read()` as a streaming interface.\n\nDRF exposes `request.data` as the primary high-level request parsing API.\n\nCurrently, DRF forwards the raw Django request stream directly to parsers before any request-size validation equivalent to Django\u0027s `request.body` path occurs.\n\nConsequently:\n\n* JSONParser\n* FormParser\n\nfully consume oversized request bodies despite Django\u0027s configured request-size limit.\n\n\n# Security Impact\n\nThis does **not** appear to introduce:\n\n* Authentication bypass\n* Authorization bypass\n* Remote code execution\n* Information disclosure\n* Integrity compromise\n\nHowever, it may reduce the effectiveness of deployments relying on Django\u0027s `DATA_UPLOAD_MAX_MEMORY_SIZE` to limit request-body resource consumption.\n\nPotential consequences include:\n\n* Additional memory allocation during JSON parsing\n* Additional CPU usage while decoding large JSON payloads\n* Increased resource consumption when handling oversized request bodies\n* Reduced effectiveness of Django\u0027s configured request-size protection for DRF endpoints using `request.data`\n\nThe practical impact depends on deployment configuration, including:\n\n* upstream request-size limits\n* reverse proxy configuration\n* authentication\n* rate limiting\n* endpoint exposure\n\n\n# Memory Observations\n\nDuring local testing I observed successful parsing of oversized request bodies despite the configured limit.\n\nRepresentative measurements showed significantly increased memory allocation while parsing large JSON and urlencoded payloads.\n\nI intentionally did **not** perform destructive concurrency testing or attempt to exhaust system resources.\n\n\n# Scope\n\nConfirmed affected:\n\n* application/json\n* application/x-www-form-urlencoded\n\nConfirmed not affected:\n\n* multipart/form-data\n\n\n# Suggested Fix Direction\n\nOne possible approach would be for DRF to enforce Django\u0027s configured `DATA_UPLOAD_MAX_MEMORY_SIZE` before handing the raw request stream to parsers that fully materialize request bodies in memory.\n\nThis would preserve Django\u0027s configured request-size protection for the common `request.data` API without requiring broader changes to Django\u0027s documented streaming interface.\n\n\n# Versions Tested\n\nAffected:\n\n* Django 6.0.7 + DRF 3.17.1\n* Django 6.0.7 + DRF current upstream main\n\nI did not perform a complete historical version bisect.\n\n\n# Disclosure\n\nI have not publicly disclosed this behavior.\n\nI am submitting it privately in accordance with the project\u0027s security policy because I am unsure whether maintainers consider this part of DRF\u0027s intended security boundary.\n\n# Note:\n\n**Thank you for taking the time to review this report.**\n\nIf you determine that this behavior should be addressed, I would be happy to help investigate further, develop a fix, add regression tests, and submit a patch if you\u0027d find that helpful.\n\nI have experience as a **Python/Django software engineer, security researcher, and open-source contributor**, and I\u0027d be glad to contribute if you think that would be useful.",
  "id": "GHSA-2m8g-3cmr-wg3w",
  "modified": "2026-09-01T19:24:51Z",
  "published": "2026-09-01T19:24:51Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/encode/django-rest-framework/security/advisories/GHSA-2m8g-3cmr-wg3w"
    },
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-73228"
    },
    {
      "type": "WEB",
      "url": "https://github.com/encode/django-rest-framework/pull/10013"
    },
    {
      "type": "WEB",
      "url": "https://github.com/encode/django-rest-framework/commit/2912dc98042f78e27636551fc22eeaf10f725fdd"
    },
    {
      "type": "WEB",
      "url": "https://github.com/encode/django-rest-framework/commit/82ef7b7e4e0a73ba5c489b465fae7e76d948da4e"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/encode/django-rest-framework"
    },
    {
      "type": "WEB",
      "url": "https://github.com/encode/django-rest-framework/releases/tag/3.17.2"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:L",
      "type": "CVSS_V3"
    }
  ],
  "summary": "Django REST framework: Potential bypass of Django `DATA_UPLOAD_MAX_MEMORY_SIZE` when parsing oversized JSON and urlencoded request bodies via DRF `request.data`"
}

GHSA-2MCV-Q3Q8-H36J

Vulnerability from github – Published: 2025-01-28 00:32 – Updated: 2026-04-02 21:32
VLAI
Details

The issue was addressed with improved checks. This issue is fixed in macOS Ventura 13.7.3, macOS Sequoia 15.3, macOS Sonoma 14.7.3. Parsing a maliciously crafted file may lead to an unexpected app termination.

Severity
9.8 (Critical)
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H
Show details on source website
To clipboard 

{
  "affected": [],
  "aliases": [
    "CVE-2025-24139"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-770",
      "CWE-787"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2025-01-27T22:15:18Z",
    "severity": "CRITICAL"
  },
  "details": "The issue was addressed with improved checks. This issue is fixed in macOS Ventura 13.7.3, macOS Sequoia 15.3, macOS Sonoma 14.7.3. Parsing a maliciously crafted file may lead to an unexpected app termination.",
  "id": "GHSA-2mcv-q3q8-h36j",
  "modified": "2026-04-02T21:32:09Z",
  "published": "2025-01-28T00:32:14Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2025-24139"
    },
    {
      "type": "WEB",
      "url": "https://support.apple.com/en-us/122068"
    },
    {
      "type": "WEB",
      "url": "https://support.apple.com/en-us/122069"
    },
    {
      "type": "WEB",
      "url": "https://support.apple.com/en-us/122070"
    },
    {
      "type": "WEB",
      "url": "https://support.apple.com/en-us/122375"
    },
    {
      "type": "WEB",
      "url": "http://seclists.org/fulldisclosure/2025/Apr/10"
    },
    {
      "type": "WEB",
      "url": "http://seclists.org/fulldisclosure/2025/Jan/15"
    },
    {
      "type": "WEB",
      "url": "http://seclists.org/fulldisclosure/2025/Jan/16"
    },
    {
      "type": "WEB",
      "url": "http://seclists.org/fulldisclosure/2025/Jan/17"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H",
      "type": "CVSS_V3"
    }
  ]
}

GHSA-2MG2-P7R7-G27F

Vulnerability from github – Published: 2026-07-06 21:06 – Updated: 2026-07-06 21:06
VLAI
Summary
Coder: Zip upload decompression lacks aggregate size limit, enabling denial of service
Details

Summary

POST /api/v2/files converts zip uploads to tar in memory via CreateTarFromZip, which enforced a per-entry size limit but no aggregate limit on total decompressed output, writing to an unbounded in-memory buffer.

Note: Exploitation requires authenticated file-upload access and the impact is limited to availability (denial of service).

Impact

An authenticated user could upload a zip within the 100 MiB upload limit but containing many highly compressible entries whose decompressed size exhausted memory, crashing coderd before any RBAC check. Repeated requests could keep the service unavailable. This is a denial of service; it does not allow data disclosure or code execution.

Patches

The fix adds a metadata preflight check that sums projected entry sizes and a streaming writer that enforces the aggregate limit during decompression.

The fix was backported to all supported release lines:

Release line Patched version
2.34 v2.34.2
2.33 v2.33.8
2.32 v2.32.7
2.29 (ESR) v2.29.17

Workarounds

Restrict file-upload permissions to trusted users or place a reverse proxy with request-body size limits in front of coderd.

Resources

  • Fix: #25877

Credits

Coder would like to thank Anthropic's Security Team (ANT-2026-22438) for independently disclosing this issue!

Severity
6.5 (Medium)
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
Show details on source website
To clipboard 

{
  "affected": [
    {
      "package": {
        "ecosystem": "Go",
        "name": "github.com/coder/coder/v2"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.34.0"
            },
            {
              "fixed": "2.34.2"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "Go",
        "name": "github.com/coder/coder/v2"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.33.0"
            },
            {
              "fixed": "2.33.8"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "Go",
        "name": "github.com/coder/coder/v2"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.30.0"
            },
            {
              "fixed": "2.32.7"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "Go",
        "name": "github.com/coder/coder/v2"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.17.0"
            },
            {
              "fixed": "2.29.17"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    }
  ],
  "aliases": [
    "CVE-2026-55078"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-409",
      "CWE-770"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2026-07-06T21:06:45Z",
    "nvd_published_at": null,
    "severity": "MODERATE"
  },
  "details": "### Summary\n\n`POST /api/v2/files` converts zip uploads to tar in memory via `CreateTarFromZip`, which enforced a per-entry size limit but no aggregate limit on total decompressed output, writing to an unbounded in-memory buffer.\n\n\u003e **Note:** Exploitation requires authenticated file-upload access and the impact is limited to availability (denial of service).\n\n### Impact\n\nAn authenticated user could upload a zip within the 100 MiB upload limit but containing many highly compressible entries whose decompressed size exhausted memory, crashing `coderd` before any RBAC check. Repeated requests could keep the service unavailable. This is a denial of service; it does not allow data disclosure or code execution.\n\n### Patches\n\nThe fix adds a metadata preflight check that sums projected entry sizes and a streaming writer that enforces the aggregate limit during decompression.\n\nThe fix was backported to all supported release lines:\n\n| Release line | Patched version |\n|---|---|\n| 2.34 | [v2.34.2](https://github.com/coder/coder/releases/tag/v2.34.2) |\n| 2.33 | [v2.33.8](https://github.com/coder/coder/releases/tag/v2.33.8) |\n| 2.32 | [v2.32.7](https://github.com/coder/coder/releases/tag/v2.32.7) |\n| 2.29 (ESR) | [v2.29.17](https://github.com/coder/coder/releases/tag/v2.29.17) |\n\n### Workarounds\n\nRestrict file-upload permissions to trusted users or place a reverse proxy with request-body size limits in front of `coderd`.\n\n### Resources\n\n- Fix: #25877\n\n### Credits\n\nCoder would like to thank Anthropic\u0027s Security Team (ANT-2026-22438) for independently disclosing this issue!",
  "id": "GHSA-2mg2-p7r7-g27f",
  "modified": "2026-07-06T21:06:45Z",
  "published": "2026-07-06T21:06:45Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/coder/coder/security/advisories/GHSA-2mg2-p7r7-g27f"
    },
    {
      "type": "WEB",
      "url": "https://github.com/coder/coder/pull/25877"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/coder/coder"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H",
      "type": "CVSS_V3"
    }
  ],
  "summary": "Coder: Zip upload decompression lacks aggregate size limit, enabling denial of service"
}

GHSA-2MG9-FCHF-M4W9

Vulnerability from github – Published: 2026-01-15 18:31 – Updated: 2026-01-15 18:31
VLAI
Details

Cyberfox Web Browser 52.9.1 contains a denial of service vulnerability that allows attackers to crash the application by overflowing the search bar with excessive data. Attackers can generate a 9,000,000 byte payload and paste it into the search bar to trigger an application crash.

Severity
7.5 (High)
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
6.7 (Medium)
CVSS:4.0/AV:L/AC:L/AT:N/PR:N/UI:A/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N
Show details on source website
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{
  "affected": [],
  "aliases": [
    "CVE-2021-47784"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-770"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2026-01-15T16:16:10Z",
    "severity": "MODERATE"
  },
  "details": "Cyberfox Web Browser 52.9.1 contains a denial of service vulnerability that allows attackers to crash the application by overflowing the search bar with excessive data. Attackers can generate a 9,000,000 byte payload and paste it into the search bar to trigger an application crash.",
  "id": "GHSA-2mg9-fchf-m4w9",
  "modified": "2026-01-15T18:31:32Z",
  "published": "2026-01-15T18:31:32Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2021-47784"
    },
    {
      "type": "WEB",
      "url": "https://web.archive.org/web/20180906035057/https://cyberfox.8pecxstudios.com"
    },
    {
      "type": "WEB",
      "url": "https://www.exploit-db.com/exploits/50336"
    }
  ],
  "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:H/SC:N/SI:N/SA:N/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X",
      "type": "CVSS_V4"
    }
  ]
}
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.

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