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Salvo Affected by Denial of Service via Unbounded Memory Allocation in Form Data Parsing

High severity GitHub Reviewed Published Mar 18, 2026 in salvo-rs/salvo • Updated Mar 25, 2026

Package

cargo salvo (Rust)

Affected versions

< 0.89.3

Patched versions

0.89.3

Description

Summary

Salvo's form data parsing implementations (form_data() method and Extractible macro) do not enforce payload size limits before reading request bodies into memory. This allows attackers to cause Out-of-Memory (OOM) conditions by sending extremely large payloads, leading to service crashes and denial of service.

Details

Vulnerability Description

Three attack vectors exist in Salvo's form handling:

  1. URL-encoded form data (application/x-www-form-urlencoded)

    • Request::form_data() calls BodyExt::collect(body) which reads the entire body into memory without size checking
    • Affects handlers using req.form_data().await directly

  2. Multipart form data (multipart/form-data)

    • Similar unbounded memory allocation during parsing
    • Affects handlers processing multipart uploads

  3. Extractible macro

    • #[derive(Extractible)] with #[salvo(extract(default_source(from = "body")))] internally calls form_data()
    • Vulnerabilities propagate to all extractors using body sources

Root Cause

The FormData::read() implementation prioritizes convenience over safety by reading entire request bodies before validation. Even when Request::payload_with_max_size() is available, it's not automatically applied in the form parsing path.

PoC

  1. run Extract data from request example in readme.md in docker file with limited memory say 100mb.
  2. Send application/x-www-form-urlencoded OR multipart/form-data payload to the endpoint.
  3. The server process OOM-crashes, instead of returning 413 error.

Impact

Immediate Effects

  • Service Unavailability: Servers crash under memory pressure
  • Resource Exhaustion: Single request can consume all available memory
  • Cascading Failures: In containerized environments, OOM can affect other services

Attack Characteristics

  • Low Cost: Attacker needs minimal bandwidth (header only, body can be streamed)
  • No Authentication: Exploitable on public endpoints
  • Difficult to Rate-Limit: Traditional rate limiting may not prevent single large request
  • Amplification: Small network cost → large memory consumption

Real-World Scenarios

  1. Public API endpoints accepting form data
  2. User registration/profile update handlers
  3. File upload endpoints using multipart forms
  4. Any endpoint using #[derive(Extractible)] with body sources

Suggestion: Make Multipart File Upload Handling Explicit Opt-In

Problem Statement

Currently, Salvo's multipart form data parsing automatically handles file uploads without explicit developer intent. This creates several security and usability concerns:

  1. Unintended File Storage: Developers may unknowingly accept file uploads when they only intended to handle text fields
  2. Disk Space Exhaustion: Automatic file buffering to disk can fill storage without proper limits
  3. Resource Cleanup: Temporary files may not be properly cleaned up if handlers don't expect them
  4. Attack Surface: Endpoints inadvertently become file upload targets

References

@chrislearn chrislearn published to salvo-rs/salvo Mar 18, 2026
Published to the GitHub Advisory Database Mar 19, 2026
Reviewed Mar 19, 2026
Published by the National Vulnerability Database Mar 24, 2026
Last updated Mar 25, 2026

Severity

High

CVSS overall score

This score calculates overall vulnerability severity from 0 to 10 and is based on the Common Vulnerability Scoring System (CVSS).
/ 10

CVSS v4 base metrics

Exploitability Metrics
Attack Vector Network
Attack Complexity Low
Attack Requirements None
Privileges Required None
User interaction None
Vulnerable System Impact Metrics
Confidentiality None
Integrity None
Availability High
Subsequent System Impact Metrics
Confidentiality None
Integrity None
Availability None

CVSS v4 base metrics

Exploitability Metrics
Attack Vector: This metric reflects the context by which vulnerability exploitation is possible. This metric value (and consequently the resulting severity) will be larger the more remote (logically, and physically) an attacker can be in order to exploit the vulnerable system. The assumption is that the number of potential attackers for a vulnerability that could be exploited from across a network is larger than the number of potential attackers that could exploit a vulnerability requiring physical access to a device, and therefore warrants a greater severity.
Attack Complexity: This metric captures measurable actions that must be taken by the attacker to actively evade or circumvent existing built-in security-enhancing conditions in order to obtain a working exploit. These are conditions whose primary purpose is to increase security and/or increase exploit engineering complexity. A vulnerability exploitable without a target-specific variable has a lower complexity than a vulnerability that would require non-trivial customization. This metric is meant to capture security mechanisms utilized by the vulnerable system.
Attack Requirements: This metric captures the prerequisite deployment and execution conditions or variables of the vulnerable system that enable the attack. These differ from security-enhancing techniques/technologies (ref Attack Complexity) as the primary purpose of these conditions is not to explicitly mitigate attacks, but rather, emerge naturally as a consequence of the deployment and execution of the vulnerable system.
Privileges Required: This metric describes the level of privileges an attacker must possess prior to successfully exploiting the vulnerability. The method by which the attacker obtains privileged credentials prior to the attack (e.g., free trial accounts), is outside the scope of this metric. Generally, self-service provisioned accounts do not constitute a privilege requirement if the attacker can grant themselves privileges as part of the attack.
User interaction: This metric captures the requirement for a human user, other than the attacker, to participate in the successful compromise of the vulnerable system. This metric determines whether the vulnerability can be exploited solely at the will of the attacker, or whether a separate user (or user-initiated process) must participate in some manner.
Vulnerable System Impact Metrics
Confidentiality: This metric measures the impact to the confidentiality of the information managed by the VULNERABLE SYSTEM due to a successfully exploited vulnerability. Confidentiality refers to limiting information access and disclosure to only authorized users, as well as preventing access by, or disclosure to, unauthorized ones.
Integrity: This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information. Integrity of the VULNERABLE SYSTEM is impacted when an attacker makes unauthorized modification of system data. Integrity is also impacted when a system user can repudiate critical actions taken in the context of the system (e.g. due to insufficient logging).
Availability: This metric measures the impact to the availability of the VULNERABLE SYSTEM resulting from a successfully exploited vulnerability. While the Confidentiality and Integrity impact metrics apply to the loss of confidentiality or integrity of data (e.g., information, files) used by the system, this metric refers to the loss of availability of the impacted system itself, such as a networked service (e.g., web, database, email). Since availability refers to the accessibility of information resources, attacks that consume network bandwidth, processor cycles, or disk space all impact the availability of a system.
Subsequent System Impact Metrics
Confidentiality: This metric measures the impact to the confidentiality of the information managed by the SUBSEQUENT SYSTEM due to a successfully exploited vulnerability. Confidentiality refers to limiting information access and disclosure to only authorized users, as well as preventing access by, or disclosure to, unauthorized ones.
Integrity: This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information. Integrity of the SUBSEQUENT SYSTEM is impacted when an attacker makes unauthorized modification of system data. Integrity is also impacted when a system user can repudiate critical actions taken in the context of the system (e.g. due to insufficient logging).
Availability: This metric measures the impact to the availability of the SUBSEQUENT SYSTEM resulting from a successfully exploited vulnerability. While the Confidentiality and Integrity impact metrics apply to the loss of confidentiality or integrity of data (e.g., information, files) used by the system, this metric refers to the loss of availability of the impacted system itself, such as a networked service (e.g., web, database, email). Since availability refers to the accessibility of information resources, attacks that consume network bandwidth, processor cycles, or disk space all impact the availability of a system.
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

EPSS score

Exploit Prediction Scoring System (EPSS)

This score estimates the probability of this vulnerability being exploited within the next 30 days. Data provided by FIRST.
(6th percentile)

Weaknesses

Allocation of Resources Without Limits or Throttling

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. Learn more on MITRE.

CVE ID

CVE-2026-33241

GHSA ID

GHSA-pp9r-xg4c-8j4x

Source code

Credits

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