Common Weakness Enumeration
CWE-770
AllowedAllocation of Resources Without Limits or Throttling
Abstraction: Base · Status: Incomplete
The product allocates a reusable resource or group of resources on behalf of an actor without imposing any intended restrictions on the size or number of resources that can be allocated.
1852 vulnerabilities reference this CWE, most recent first.
CVE-2026-113811 (GCVE-0-2026-113811)
Vulnerability from cvelistv5 – Published: 2026-10-21 20:58 – Updated: 2026-10-30 15:49
VLAI
EPSS
VEX
Title
Algorithm::UrataniTakeda versions from 0.1.5 before 0.1.7 for Perl allow memory exhaustion via a never-cleared failure shift cache in search
Summary
Algorithm::UrataniTakeda versions from 0.1.5 before 0.1.7 for Perl allow memory exhaustion via a never-cleared failure shift cache in search.
The failure shift is cached for each pair of trie state and text character in a field of the matcher object, and nothing clears it. A character not seen before at a given state adds an entry that lasts for the life of the matcher.
An attacker who can submit text with many distinct characters to a long-lived matcher can grow its memory with each search.
Severity
7.5 (High)
SSVC
Exploitation: poc
Automatable: yes
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-10-30 15:49 UTC
CWE
- CWE-770 - Allocation of Resources Without Limits or Throttling
Assigner
CPANSec
CNA
References
4 references
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CVE-2026-113795 (GCVE-0-2026-113795)
Vulnerability from cvelistv5 – Published: 2026-10-21 16:01 – Updated: 2026-10-30 15:58
VLAI
EPSS
VEX
Title
pypdf: Possible large memory usage for streams with multiple filters
Summary
pypdf is a free and open-source pure-python PDF library. Prior to 6.20.0, accessing a crafted PDF stream with a large number of filters or multiple filters that pass around large amounts of data can cause large memory consumption. This issue is fixed in version 6.20.0.
Severity
SSVC
Exploitation: none
Automatable: no
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-10-30 15:58 UTC
CWE
Assigner
GitHub_M
CNA
References
4 references
| URL | Tags |
|---|---|
| https://github.com/py-pdf/pypdf/security/advisori… | x_refsource_CONFIRM |
| https://github.com/py-pdf/pypdf/pull/4173 | x_refsource_MISC |
| https://github.com/py-pdf/pypdf/commit/80a84d4be6… | x_refsource_MISC |
| https://github.com/py-pdf/pypdf/releases/tag/6.20.0 | x_refsource_MISC |
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CVE-2026-113791 (GCVE-0-2026-113791)
Vulnerability from cvelistv5 – Published: 2026-10-21 15:37 – Updated: 2026-10-30 15:57
VLAI
EPSS
VEX
Title
pypdf: Possible large memory usage when parsing content streams
Summary
pypdf is a free and open-source pure-python PDF library. Prior to 6.21.0, an attacker can craft a PDF containing a content stream with many small operations, causing parsing to consume large amounts of memory. This issue is fixed in version 6.21.0.
Severity
SSVC
Exploitation: none
Automatable: no
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-10-30 15:57 UTC
CWE
Assigner
GitHub_M
CNA
References
4 references
| URL | Tags |
|---|---|
| https://github.com/py-pdf/pypdf/security/advisori… | x_refsource_CONFIRM |
| https://github.com/py-pdf/pypdf/pull/4218 | x_refsource_MISC |
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CVE-2026-113790 (GCVE-0-2026-113790)
Vulnerability from cvelistv5 – Published: 2026-10-21 15:35 – Updated: 2026-10-28 01:18
VLAI
EPSS
VEX
Title
pypdf: Possible large memory usage when parsing arrays and dictionaries
Summary
pypdf is a free and open-source pure-python PDF library. Prior to 6.21.0, an attacker can craft a PDF containing arrays or dictionaries with many elements, causing parsing to consume large amounts of memory. This issue is fixed in version 6.21.0.
Severity
SSVC
Exploitation: none
Automatable: no
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-10-28 01:18 UTC
CWE
Assigner
GitHub_M
CNA
References
4 references
| URL | Tags |
|---|---|
| https://github.com/py-pdf/pypdf/security/advisori… | x_refsource_CONFIRM |
| https://github.com/py-pdf/pypdf/pull/4218 | x_refsource_MISC |
| https://github.com/py-pdf/pypdf/commit/18bd2981a7… | x_refsource_MISC |
| https://github.com/py-pdf/pypdf/releases/tag/6.21.0 | x_refsource_MISC |
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CVE-2026-113729 (GCVE-0-2026-113729)
Vulnerability from cvelistv5 – Published: 2026-10-20 21:17 – Updated: 2026-10-27 11:07
VLAI
EPSS
VEX
Title
Moov signedxml: Unauthenticated denial of service in exclusive XML canonicalization
Summary
Moov signedxml is a pure Go library for processing signed XML documents. Prior to 1.4.1, ExclusiveCanonicalization in exclusivecanonicalization.go copies the complete accumulated namespace map at every nested element before reference digest or signature checks. Attacker-controlled XML containing deeply nested elements with many unused namespace declarations causes quadratic allocation growth with depth and linear growth with prefixes per level, allowing a comparatively small document to consume multiple gigabytes of memory and terminate the process. The condition is reachable through ValidateReferences without a valid signature, matching certificate, or prior authentication, and it does not bypass signature verification. This issue is fixed in version 1.4.1.
Severity
7.5 (High)
SSVC
Exploitation: none
Automatable: yes
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-10-27 11:07 UTC
CWE
Assigner
GitHub_M
CNA
References
3 references
| URL | Tags |
|---|---|
| https://github.com/moov-io/signedxml/security/adv… | x_refsource_CONFIRM |
| https://github.com/moov-io/signedxml/commit/da2cd… | x_refsource_MISC |
| https://github.com/moov-io/signedxml/releases/tag… | x_refsource_MISC |
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CVE-2026-113711 (GCVE-0-2026-113711)
Vulnerability from cvelistv5 – Published: 2026-10-20 17:49 – Updated: 2026-10-20 19:04
VLAI
EPSS
VEX
Title
ApostropheCMS: Unauthenticated resource exhaustion via pre-auth aposBigUpload processing in @apostrophecms/import-export
Summary
ApostropheCMS is an open-source Node.js content management system. Prior to 4.33.0 of ApostropheCMS and 3.7.0 of the import-export module, import routes invoke bigUploadMiddleware without an early authorize callback, allowing unauthenticated requests to perform upload initialization, chunk storage, temporary processing, and attacker-declared cleanup work before the later user check rejects the import. This issue is fixed in ApostropheCMS 4.33.0 and import-export 3.7.0.
Severity
7.5 (High)
SSVC
Exploitation: poc
Automatable: yes
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-10-20 19:03 UTC
CWE
Assigner
GitHub_M
CNA
References
4 references
| URL | Tags |
|---|---|
| https://github.com/apostrophecms/apostrophe/secur… | x_refsource_CONFIRM |
| https://github.com/apostrophecms/apostrophe/commi… | x_refsource_MISC |
| https://github.com/apostrophecms/apostrophe/commi… | x_refsource_MISC |
| https://github.com/apostrophecms/apostrophe/relea… | x_refsource_MISC |
Impacted products
2 products
| Vendor | Product | Version | |
|---|---|---|---|
| apostrophecms | apostrophe |
Affected:
< 4.33.0
|
|
| @apostrophecms | import-export |
Affected:
< 3.7.0
|
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CVE-2026-113658 (GCVE-0-2026-113658)
Vulnerability from cvelistv5 – Published: 2026-10-20 16:56 – Updated: 2026-10-23 01:55
VLAI
EPSS
VEX
Title
ApostropheCMS: Unauthenticated CSV import requests leave rejected uploads in the system temporary directory
Summary
ApostropheCMS is an open-source Node.js content management system. Prior to 4.33.0, the unauthenticated Rich Text CSV conversion route writes a multipart upload to the system temporary directory before checking its extension and does not remove the staged file when that validation rejects it. Repeated large rejected uploads, using the normal public CSRF cookie, can persistently consume temporary-disk capacity and may disrupt ApostropheCMS and other services that depend on the same partition. This issue is fixed in version 4.33.0.
Severity
7.5 (High)
SSVC
Exploitation: poc
Automatable: yes
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-10-23 01:54 UTC
CWE
Assigner
GitHub_M
CNA
References
4 references
| URL | Tags |
|---|---|
| https://github.com/apostrophecms/apostrophe/secur… | x_refsource_CONFIRM |
| https://github.com/apostrophecms/apostrophe/commi… | x_refsource_MISC |
| https://github.com/apostrophecms/apostrophe/commi… | x_refsource_MISC |
| https://github.com/apostrophecms/apostrophe/relea… | x_refsource_MISC |
Impacted products
1 product
| Vendor | Product | Version | |
|---|---|---|---|
| apostrophecms | apostrophe |
Affected:
< 4.33.0
|
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CVE-2026-113656 (GCVE-0-2026-113656)
Vulnerability from cvelistv5 – Published: 2026-10-20 16:49 – Updated: 2026-10-21 15:53
VLAI
EPSS
VEX
Title
ApostropheCMS: Unauthenticated unbounded multipart upload → disk-exhaustion DoS
Summary
ApostropheCMS is an open-source Node.js content management system. Prior to 1.5.5 of the ApostropheCMS Form add-on, its form submission route stages unbounded multipart uploads before form validation or authentication and lacks upload size, count, and rate limits. Repeated unauthenticated submissions can consume temporary disk storage and disrupt form handling or other host services. This issue is fixed in ApostropheCMS Form 1.5.5.
Severity
5.3 (Medium)
SSVC
Exploitation: none
Automatable: yes
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-10-21 14:40 UTC
CWE
- CWE-770 - Allocation of Resources Without Limits or Throttling
Assigner
GitHub_M
CNA
References
4 references
| URL | Tags |
|---|---|
| https://github.com/apostrophecms/apostrophe/secur… | x_refsource_CONFIRM |
| https://github.com/apostrophecms/apostrophe/commi… | x_refsource_MISC |
| https://github.com/apostrophecms/apostrophe/commi… | x_refsource_MISC |
| https://github.com/apostrophecms/apostrophe/relea… | x_refsource_MISC |
Impacted products
2 products
| Vendor | Product | Version | |
|---|---|---|---|
| apostrophecms | apostrophe |
Affected:
< 4.33.0
|
|
| @apostrophecms | form |
Affected:
< 1.5.5
|
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"url": "https://github.com/apostrophecms/apostrophe/security/advisories/GHSA-89mh-mm8c-mv7f"
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"url": "https://github.com/apostrophecms/apostrophe/commit/f84fd41cbf6c22eb8d0008fc9c25df1f7130b350"
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"name": "https://github.com/apostrophecms/apostrophe/releases/tag/@apostrophecms/form@1.5.5",
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"source": {
"advisory": "GHSA-89mh-mm8c-mv7f",
"discovery": "UNKNOWN"
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"title": "ApostropheCMS: Unauthenticated unbounded multipart upload \u2192 disk-exhaustion DoS"
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},
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"assignerShortName": "GitHub_M",
"cveId": "CVE-2026-113656",
"datePublished": "2026-10-20T16:49:36.239Z",
"dateReserved": "2026-10-20T14:27:46.641Z",
"dateUpdated": "2026-10-21T15:53:31.741Z",
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CVE-2026-113431 (GCVE-0-2026-113431)
Vulnerability from cvelistv5 – Published: 2026-11-06 10:28 – Updated: 2026-11-09 15:27
VLAI
EPSS
VEX
Title
Unbounded decoded HTTP/2 header-list size in cowlib cow_http2_machine enables HPACK amplification memory exhaustion
Summary
Allocation of Resources Without Limits or Throttling vulnerability in ninenines cowlib allows an unauthenticated remote peer to exhaust the memory of an HTTP/2 endpoint via HPACK-indexed header fields.
cow_http2_machine:headers_decode/4 in src/cow_http2_machine.erl decodes every HEADERS block with cow_hpack:decode/3. It bounds the compressed block size and the number of fields, but not the size of the decoded header list that RFC 9113 section 6.5.2 places under SETTINGS_MAX_HEADER_LIST_SIZE. A peer stores one header value of up to the dynamic table size (4096 bytes by default) and then references it with one-byte indexed fields, so about 100 bytes on the wire decode to a header list of about 390 KB. A consumer that copies the decoded values, as Cowboy does when cowboy_http2:headers_to_map/2 joins repeated cookie fields into one binary, allocates that amount for every stream. The total across streams and connections is not bounded.
This issue affects cowlib: from 2.7.0 before 2.22.0.
Severity
CWE
- CWE-770 - Allocation of Resources Without Limits or Throttling
Assigner
EEF
CNA
References
4 references
| URL | Tags |
|---|---|
| https://cna.erlef.org/cves/CVE-2026-113431.html | relatedthird-party-advisory |
| https://osv.dev/vulnerability/EEF-CVE-2026-113431 | related |
| https://github.com/ninenines/cowlib/commit/b461b1… | related |
| https://github.com/ninenines/cowlib/commit/a3b15e… | patch |
Impacted products
Date Public
2026-11-06 10:28
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"value": "\u003cp\u003e\u003cstrong\u003e1. The decoder bounds everything but the decoded size.\u003c/strong\u003e \u003ccode\u003ecow_http2_machine:headers_decode/4\u003c/code\u003e passes each complete header block to \u003ccode\u003ecow_hpack:decode/3\u003c/code\u003e. Two limits apply: \u003ccode\u003emax_fragmented_header_block_size\u003c/code\u003e (32768 bytes by default) on the compressed block, and \u003ccode\u003emax_headers\u003c/code\u003e (100 by default, added in cowlib 2.17.0) on the number of fields. \u003ccode\u003emax_header_list_size\u003c/code\u003e appears in the module\u0027s option list with a default of \u003ccode\u003einfinity\u003c/code\u003e, next to a \u003ccode\u003e@todo\u003c/code\u003e comment, and is neither advertised in SETTINGS nor enforced on the decoded list, which is what RFC 9113 section 6.5.2 defines it for.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2. One-byte fields expand to kilobytes.\u003c/strong\u003e The dynamic table holds entries of up to \u003ccode\u003emax_decode_table_size\u003c/code\u003e (4096 bytes by default). The peer sends one literal field with incremental indexing carrying a 4000-byte value, which becomes table entry 62. Every later field is the single byte \u003ccode\u003e0xBE\u003c/code\u003e, an indexed representation of that entry. A 110-byte block that carries four pseudo-headers and 96 such references decodes to a 100-field list whose values total 384,000 bytes. Before 2.17.0 no field count applied, so a 32 KB block referenced the entry about 32,000 times.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3. The allocation is realised by the consumer.\u003c/strong\u003e The list that \u003ccode\u003ecow_hpack\u003c/code\u003e returns is cheap, about 2 KB of heap, because every reference shares the one table binary. Cowboy\u0027s \u003ccode\u003ecowboy_http2:headers_to_map/2\u003c/code\u003e joins repeated fields into a single new binary (\u003ccode\u003e\"; \"\u003c/code\u003e for \u003ccode\u003ecookie\u003c/code\u003e, \u003ccode\u003e\", \"\u003c/code\u003e for other names), so each stream yields a 384,190-byte cookie value that lives in the request process for the life of the stream. Cowboy\u0027s HTTP/1.1 limits \u003ccode\u003emax_header_value_length\u003c/code\u003e and \u003ccode\u003emax_headers\u003c/code\u003e do not apply to HTTP/2. With the default \u003ccode\u003emax_concurrent_streams\u003c/code\u003e of 100 a connection holds about 38 MB, and only the Ranch connection limit bounds the total. Gun hands the decoded list to the owner process without copying the values, so the client side sees a small list per response and no amplification.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4. Measurement.\u003c/strong\u003e On cowboy 2.20.0 with cowlib 2.21.0 on Erlang/OTP 29, one h2c connection on loopback sent 15,943 bytes of HEADERS for 100 streams. Binary memory grew by 38.4 MB and every handler received a 384,190-byte \u003ccode\u003ecookie\u003c/code\u003e header. A control with the same 100 streams and no indexed fields grew by 0.\u003c/p\u003e"
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"value": "**1. The decoder bounds everything but the decoded size.** `cow_http2_machine:headers_decode/4` passes each complete header block to `cow_hpack:decode/3`. Two limits apply: `max_fragmented_header_block_size` (32768 bytes by default) on the compressed block, and `max_headers` (100 by default, added in cowlib 2.17.0) on the number of fields. `max_header_list_size` appears in the module\u0027s option list with a default of `infinity`, next to a `@todo` comment, and is neither advertised in SETTINGS nor enforced on the decoded list, which is what RFC 9113 section 6.5.2 defines it for.\n\n**2. One-byte fields expand to kilobytes.** The dynamic table holds entries of up to `max_decode_table_size` (4096 bytes by default). The peer sends one literal field with incremental indexing carrying a 4000-byte value, which becomes table entry 62. Every later field is the single byte `0xBE`, an indexed representation of that entry. A 110-byte block that carries four pseudo-headers and 96 such references decodes to a 100-field list whose values total 384,000 bytes. Before 2.17.0 no field count applied, so a 32 KB block referenced the entry about 32,000 times.\n\n**3. The allocation is realised by the consumer.** The list that `cow_hpack` returns is cheap, about 2 KB of heap, because every reference shares the one table binary. Cowboy\u0027s `cowboy_http2:headers_to_map/2` joins repeated fields into a single new binary (`\"; \"` for `cookie`, `\", \"` for other names), so each stream yields a 384,190-byte cookie value that lives in the request process for the life of the stream. Cowboy\u0027s HTTP/1.1 limits `max_header_value_length` and `max_headers` do not apply to HTTP/2. With the default `max_concurrent_streams` of 100 a connection holds about 38 MB, and only the Ranch connection limit bounds the total. Gun hands the decoded list to the owner process without copying the values, so the client side sees a small list per response and no amplification.\n\n**4. Measurement.** On cowboy 2.20.0 with cowlib 2.21.0 on Erlang/OTP 29, one h2c connection on loopback sent 15,943 bytes of HEADERS for 100 streams. Binary memory grew by 38.4 MB and every handler received a 384,190-byte `cookie` header. A control with the same 100 streams and no indexed fields grew by 0."
}
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"value": "1. The decoder bounds everything but the decoded size. cow_http2_machine:headers_decode/4 passes each complete header block to cow_hpack:decode/3. Two limits apply: max_fragmented_header_block_size (32768 bytes by default) on the compressed block, and max_headers (100 by default, added in cowlib 2.17.0) on the number of fields. max_header_list_size appears in the module\u0027s option list with a default of infinity, next to a @todo comment, and is neither advertised in SETTINGS nor enforced on the decoded list, which is what RFC 9113 section 6.5.2 defines it for.\n\n2. One-byte fields expand to kilobytes. The dynamic table holds entries of up to max_decode_table_size (4096 bytes by default). The peer sends one literal field with incremental indexing carrying a 4000-byte value, which becomes table entry 62. Every later field is the single byte 0xBE, an indexed representation of that entry. A 110-byte block that carries four pseudo-headers and 96 such references decodes to a 100-field list whose values total 384,000 bytes. Before 2.17.0 no field count applied, so a 32 KB block referenced the entry about 32,000 times.\n\n3. The allocation is realised by the consumer. The list that cow_hpack returns is cheap, about 2 KB of heap, because every reference shares the one table binary. Cowboy\u0027s cowboy_http2:headers_to_map/2 joins repeated fields into a single new binary (\"; \" for cookie, \", \" for other names), so each stream yields a 384,190-byte cookie value that lives in the request process for the life of the stream. Cowboy\u0027s HTTP/1.1 limits max_header_value_length and max_headers do not apply to HTTP/2. With the default max_concurrent_streams of 100 a connection holds about 38 MB, and only the Ranch connection limit bounds the total. Gun hands the decoded list to the owner process without copying the values, so the client side sees a small list per response and no amplification.\n\n4. Measurement. On cowboy 2.20.0 with cowlib 2.21.0 on Erlang/OTP 29, one h2c connection on loopback sent 15,943 bytes of HEADERS for 100 streams. Binary memory grew by 38.4 MB and every handler received a 384,190-byte cookie header. A control with the same 100 streams and no indexed fields grew by 0."
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"cveId": "CVE-2026-113431",
"datePublished": "2026-11-06T10:28:15.837Z",
"dateReserved": "2026-10-30T12:30:02.006Z",
"dateUpdated": "2026-11-09T15:27:14.870Z",
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CVE-2026-112899 (GCVE-0-2026-112899)
Vulnerability from cvelistv5 – Published: 2026-11-05 20:35 – Updated: 2026-11-09 18:34
VLAI
EPSS
VEX
Title
Pillow: EPS load(scale) lets Ghostscript render past the decompression bomb limit
Summary
Pillow is a Python imaging library. In versions 2.3.0 through 12.3.0, EPS rendering does not validate the scaled image dimensions before invoking Ghostscript. Applications that process untrusted EPS or PostScript files using an application-selected scale greater than one can incur excessive Ghostscript CPU and temporary disk consumption. In versions with decompression-bomb protection, the scaled output is checked only after Ghostscript has completed rendering, allowing resource consumption beyond the configured pixel limit. The amplification depends on the scale selected by the application, not an attacker-controlled scale value. This issue is fixed in version 13.0.0.
Severity
SSVC
Exploitation: poc
Automatable: no
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-11-09 18:34 UTC
CWE
- CWE-770 - Allocation of Resources Without Limits or Throttling
Assigner
GitHub_M
CNA
References
4 references
| URL | Tags |
|---|---|
| https://github.com/python-pillow/Pillow/security/… | x_refsource_CONFIRM |
| https://github.com/python-pillow/Pillow/pull/10112 | x_refsource_MISC |
| https://github.com/python-pillow/Pillow/commit/3e… | x_refsource_MISC |
| https://github.com/python-pillow/Pillow/releases/… | x_refsource_MISC |
Impacted products
1 product
| Vendor | Product | Version | |
|---|---|---|---|
| python-pillow | Pillow |
Affected:
>= 2.5.0, < 13.0.0
|
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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.