Common Weakness Enumeration

CWE-400

Discouraged

Uncontrolled Resource Consumption

Abstraction: Class · Status: Draft

The product does not properly control the allocation and maintenance of a limited resource.

5417 vulnerabilities reference this CWE, most recent first.

CVE-2026-33538 (GCVE-0-2026-33538)

Vulnerability from cvelistv5 – Published: 2026-03-24 18:24 – Updated: 2026-03-24 18:37
VLAI
Title
Parse Server: Denial of service via unindexed database query for unconfigured auth providers
Summary
Parse Server is an open source backend that can be deployed to any infrastructure that can run Node.js. Prior to versions 8.6.58 and 9.6.0-alpha.52, an unauthenticated attacker can cause denial of service by sending authentication requests with arbitrary, unconfigured provider names. The server executes a database query for each unconfigured provider before rejecting the request, and since no database index exists for unconfigured providers, each request triggers a full collection scan on the user database. This can be parallelized to saturate database resources. This issue has been patched in versions 8.6.58 and 9.6.0-alpha.52.
SSVC
Exploitation: none Automatable: yes Technical Impact: partial
CISA Coordinator (v2.0.3)
CWE
  • CWE-400 - Uncontrolled Resource Consumption
Assigner
Impacted products
Vendor Product Version
parse-community parse-server Affected: < 8.6.58
Affected: >= 9.0.0, < 9.6.0-alpha.52
Create a notification for this product.
Show details on NVD website

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CVE-2026-33474 (GCVE-0-2026-33474)

Vulnerability from cvelistv5 – Published: 2026-03-24 15:21 – Updated: 2026-03-24 15:52
VLAI
Title
Vikunja Affected by DoS via Image Preview Generation
Summary
Vikunja is an open-source self-hosted task management platform. Starting in version 1.0.0-rc0 and prior to version 2.2.0, unbounded image decoding and resizing during preview generation lets an attacker exhaust CPU and memory with highly compressed but extremely large-dimension images. Version 2.2.0 patches the issue.
SSVC
Exploitation: poc Automatable: no Technical Impact: partial
CISA Coordinator (v2.0.3)
CWE
  • CWE-400 - Uncontrolled Resource Consumption
Assigner
References
Impacted products
Vendor Product Version
go-vikunja vikunja Affected: >= 1.0.0-rc0, < 2.2.0
Create a notification for this product.
Show details on NVD website

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CVE-2026-33464 (GCVE-0-2026-33464)

Vulnerability from cvelistv5 – Published: 2026-05-28 19:35 – Updated: 2026-05-29 14:55
VLAI
Title
Uncontrolled Resource Consumption in Kibana Leading to Denial of Service
Summary
Uncontrolled Resource Consumption (CWE-400) in Kibana can lead to a denial of service via Excessive Allocation (CAPEC-130). An authenticated user holding a low-privileged role can submit a specially crafted, oversized payload to an internal Kibana API, causing the Kibana process to exhaust available resources and become unresponsive to all users until the service recovers or is restarted.
SSVC
Exploitation: none Automatable: no Technical Impact: partial
CISA Coordinator (v2.0.3)
CWE
  • CWE-400 - Uncontrolled Resource Consumption
Assigner
Impacted products
Vendor Product Version
Elastic Kibana Affected: 9.4.0 , ≤ 9.4.0 (semver)
Affected: 9.0.0 , ≤ 9.3.4 (semver)
Affected: 8.0.0 , ≤ 8.19.15 (semver)
Create a notification for this product.
Show details on NVD website

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CVE-2026-33459 (GCVE-0-2026-33459)

Vulnerability from cvelistv5 – Published: 2026-04-08 16:46 – Updated: 2026-04-09 14:24
VLAI
Title
Uncontrolled Resource Consumption in Kibana Leading to Denial of Service
Summary
Uncontrolled Resource Consumption (CWE-400) in Kibana can lead to denial of service via Excessive Allocation (CAPEC-130). An authenticated user with access to the automatic import feature can submit specially crafted requests with excessively large input values. When multiple such requests are sent concurrently, the backend services become unstable, resulting in service disruption and deployment unavailability for all users.
SSVC
Exploitation: none Automatable: no Technical Impact: partial
CISA Coordinator (v2.0.3)
CWE
  • CWE-400 - Uncontrolled Resource Consumption
Assigner
Impacted products
Vendor Product Version
Elastic Kibana Affected: 9.3.0 , ≤ 9.3.2 (semver)
Affected: 8.15.0 , ≤ 8.19.13 (semver)
Affected: 9.0.0 , ≤ 9.2.7 (semver)
Create a notification for this product.
Show details on NVD website

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CVE-2026-33382 (GCVE-0-2026-33382)

Vulnerability from cvelistv5 – Published: 2026-07-10 14:58 – Updated: 2026-07-16 03:12
VLAI
Title
Denial of service via unbounded request body size
Summary
Several Grafana API endpoints, some of them unauthenticated, do not limit the size of the request body before processing it. An attacker can send very large payloads that force excessive memory allocation, potentially exhausting memory and causing a denial of service.
SSVC
Exploitation: none Automatable: yes Technical Impact: partial
CISA Coordinator (v2.0.3)
CWE
Assigner
References
Impacted products
Vendor Product Version
Grafana Grafana OSS Affected: 11.6.0 , ≤ 11.6.14 (semver)
Affected: 12.2.0 , ≤ 12.2.8 (semver)
Affected: 12.3.0 , ≤ 12.3.6 (semver)
Affected: 12.4.0 , ≤ 12.4.3 (semver)
Affected: 13.0.0 , ≤ 13.0.1 (semver)
Create a notification for this product.
Date Public
2026-06-09 00:00
Show details on NVD website

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CVE-2026-33287 (GCVE-0-2026-33287)

Vulnerability from cvelistv5 – Published: 2026-03-26 00:33 – Updated: 2026-03-26 15:02
VLAI
Title
LiquidJS has Exponential Memory Amplification through its replace_first Filter $& Pattern
Summary
LiquidJS is a Shopify / GitHub Pages compatible template engine in pure JavaScript. Prior to version 10.25.1, the `replace_first` filter in LiquidJS uses JavaScript's `String.prototype.replace()` which interprets `$&` as a back reference to the matched substring. The filter only charges `memoryLimit` for the input string length, not the amplified output. An attacker can achieve exponential memory amplification (up to 625,000:1) while staying within the `memoryLimit` budget, leading to denial of service. Version 10.25.1 patches the issue.
SSVC
Exploitation: poc Automatable: yes Technical Impact: partial
CISA Coordinator (v2.0.3)
CWE
  • CWE-20 - Improper Input Validation
  • CWE-400 - Uncontrolled Resource Consumption
Assigner
References
Impacted products
Vendor Product Version
harttle liquidjs Affected: < 10.25.1
Create a notification for this product.
Show details on NVD website

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CVE-2026-33285 (GCVE-0-2026-33285)

Vulnerability from cvelistv5 – Published: 2026-03-26 00:34 – Updated: 2026-03-28 02:08
VLAI
Title
LiquidJS: memoryLimit Bypass through Negative Range Values Leads to Process Crash
Summary
LiquidJS is a Shopify / GitHub Pages compatible template engine in pure JavaScript. Prior to version 10.25.1, LiquidJS's `memoryLimit` security mechanism can be completely bypassed by using reverse range expressions (e.g., `(100000000..1)`), allowing an attacker to allocate unlimited memory. Combined with a string flattening operation (e.g., `replace` filter), this causes a V8 Fatal error that crashes the Node.js process, resulting in complete denial of service from a single HTTP request. Version 10.25.1 patches the issue.
SSVC
Exploitation: poc Automatable: yes Technical Impact: partial
CISA Coordinator (v2.0.3)
CWE
  • CWE-20 - Improper Input Validation
  • CWE-400 - Uncontrolled Resource Consumption
Assigner
References
Impacted products
Vendor Product Version
harttle liquidjs Affected: < 10.25.1
Create a notification for this product.
Show details on NVD website

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CVE-2026-33268 (GCVE-0-2026-33268)

Vulnerability from cvelistv5 – Published: 2026-03-25 14:21 – Updated: 2026-03-25 15:53
VLAI
Title
Nanoleaf Lines unauthenticated firmware file store
Summary
Nanoleaf Lines 12.3.2 does not authenticate firmware file uploads. A remote, unauthenticated attacker can upload firmware files on the device and consume storage resources. Fixed in 12.3.6.
SSVC
Exploitation: none Automatable: yes Technical Impact: partial
CISA Coordinator (v2.0.3)
CWE
  • CWE-400 - Uncontrolled Resource Consumption
Assigner
Impacted products
Vendor Product Version
Nanoleaf Lines Affected: 12.3.2 , < 12.3.6 (custom)
Unaffected: 12.3.6
Create a notification for this product.
Date Public
2026-03-25 00:00
Credits
Souvik Kandar
Show details on NVD website

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CVE-2026-33235 (GCVE-0-2026-33235)

Vulnerability from cvelistv5 – Published: 2026-06-24 20:52 – Updated: 2026-06-25 15:42
VLAI
Title
AutoGPT: Denial of Service (DoS) via Resource Exhaustion in text templating features
Summary
AutoGPT is a workflow automation platform for creating, deploying, and managing continuous artificial intelligence agents. In versions prior to 0.6.52, the Fill Text Template block is vulnerable to a Denial of Service (DoS) attack. While the backend implements a SandboxedEnvironment to prevent unauthorized attribute access (e.g., blocking __class__), it fails to limit the computational complexity or execution time of the expressions. An attacker can input computationally expensive Python/Jinja2 expressions that consume the server's CPU and memory, leading to a complete system hang or crash. In multi-tenant or self-hosted environments, this results in a complete service outage and "noisy neighbor" effects that require manual administrative intervention to recover. This issue has been fixed in version 0.6.52.
SSVC
Exploitation: poc Automatable: no Technical Impact: partial
CISA Coordinator (v2.0.3)
CWE
  • CWE-400 - Uncontrolled Resource Consumption
Assigner
References
Impacted products
Vendor Product Version
Significant-Gravitas AutoGPT Affected: >= 0.1.0, < 0.6.52
Create a notification for this product.
Show details on NVD website

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CVE-2026-33232 (GCVE-0-2026-33232)

Vulnerability from cvelistv5 – Published: 2026-05-19 00:35 – Updated: 2026-05-19 13:03
VLAI
Title
AutoGPT: Unauthenticated DoS via Disk Space Exhaustion
Summary
AutoGPT is a workflow automation platform for creating, deploying, and managing continuous artificial intelligence agents. Versions 0.4.2 through 0.6.51 are vulnerable to an unauthenticated Denial of Service (DoS) through the server due to uncontrolled disk space consumption. The download_agent_file endpoint creates persistent temporary files for every request but fails to delete them after they are served. An unauthenticated attacker can repeatedly call this endpoint to exhaust the server's disk space, causing the database or other system services to fail due to "No space left on device" errors, rendering the entire AutoGPT Platform backend unavailable to all users. This issue has been patched in version 0.6.52.
SSVC
Exploitation: poc Automatable: yes Technical Impact: partial
CISA Coordinator (v2.0.3)
CWE
  • CWE-459 - Incomplete Cleanup
  • CWE-400 - Uncontrolled Resource Consumption
  • CWE-770 - Allocation of Resources Without Limits or Throttling
Assigner
References
Impacted products
Vendor Product Version
Significant-Gravitas AutoGPT Affected: >= 0.4.2, < 0.6.52
Create a notification for this product.
Show details on NVD website

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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. 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
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 is simply difficult to effectively institute -- and even when properly done, it does not provide a full solution. It simply makes the attack require more resources on the part of the attacker.
  • recognizes the attack and denies that user further access for a given amount of time, or
  • 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
Implementation

Ensure that all failures in resource allocation place the system into a safe posture.

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-227: Sustained Client Engagement

An adversary attempts to deny legitimate users access to a resource by continually engaging a specific resource in an attempt to keep the resource tied up as long as possible. The adversary's primary goal is not to crash or flood the target, which would alert defenders; rather it is to repeatedly perform actions or abuse algorithmic flaws such that a given resource is tied up and not available to a legitimate user. By carefully crafting a requests that keep the resource engaged through what is seemingly benign requests, legitimate users are limited or completely denied access to the resource.

CAPEC-492: Regular Expression Exponential Blowup

An adversary may execute an attack on a program that uses a poor Regular Expression(Regex) implementation by choosing input that results in an extreme situation for the Regex. A typical extreme situation operates at exponential time compared to the input size. This is due to most implementations using a Nondeterministic Finite Automaton(NFA) state machine to be built by the Regex algorithm since NFA allows backtracking and thus more complex regular expressions.