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NodeVM observability builtins leak host process and HTTP request data

Moderate severity GitHub Reviewed Published May 18, 2026 in patriksimek/vm2 • Updated May 29, 2026

Package

npm vm2 (npm)

Affected versions

<= 3.11.3

Patched versions

3.11.4

Description

Summary

NodeVM exposes some process-wide observability builtins when they are allowed through require.builtin.

The following builtins are not blocked by the dangerous builtin denylist:

diagnostics_channel
async_hooks
perf_hooks

These modules are process-wide, not sandbox-local. Sandboxed code can use them to observe host application data across the vm2 boundary.

Note: It is a host data exposure issue. The impact depends on whether the host application allows these builtins and uses HTTP, async request context, diagnostics channels, or performance marks in the same process.

Details

Non-denied builtins are exposed to the sandbox through lib/builtin.js:

builtins.set(key, special ? special : vm => vm.readonly(hostRequire(key)));

diagnostics_channel, async_hooks, and perf_hooks are not denied. These modules expose host process state rather than sandbox-local state.

Confirmed examples:

  1. diagnostics_channel lets sandboxed code subscribe to Node.js HTTP diagnostic channels such as http.server.request.start. The sandbox receives host HTTP request objects and can read headers such as Authorization or session tokens.
  2. async_hooks.executionAsyncResource() lets sandboxed code read the current host AsyncResource. If the host stores request/user data on that resource, the sandbox can read it.
  3. perf_hooks.performance.getEntriesByType('mark') lets sandboxed code read host performance timeline entries.

PoC

Run from the vm2 repository root:

node poc/observability-builtins-info-leak.js

observability-builtins-info-leak.js

The PoC uses only the specific builtin being tested in each section.

It confirms:

diagnostics_channel: sandbox reads host HTTP request headers
async_hooks: sandbox reads host AsyncResource data
perf_hooks: sandbox reads host performance mark names

Example impact from the PoC:

authorization: Bearer HOST_HTTP_SECRET_...
x-session-token: HOST_HTTP_SECRET_...

These values are sent to a host HTTP server, but the sandbox reads them through diagnostics_channel.

Screenshot 2026-05-10 at 1 13 20 PM

Impact

An attacker who can run untrusted JavaScript inside NodeVM with affected builtin settings can observe data from the host process.

In a real application, this may expose HTTP request headers, authorization tokens, session tokens, request context values, user identifiers, or other sensitive diagnostics data from the host application or from other users.

Suggested fix

Treat process-wide observability modules as dangerous builtins for untrusted sandboxes.

At minimum, consider blocking:

diagnostics_channel
async_hooks
perf_hooks

These modules are not sandbox-local and can expose host process state across the vm2 boundary.

References

@patriksimek patriksimek published to patriksimek/vm2 May 18, 2026
Published to the GitHub Advisory Database May 29, 2026
Reviewed May 29, 2026
Last updated May 29, 2026

Severity

Moderate

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 Present
Privileges Required None
User interaction None
Vulnerable System Impact Metrics
Confidentiality High
Integrity None
Availability None
Subsequent System Impact Metrics
Confidentiality Low
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:P/PR:N/UI:N/VC:H/VI:N/VA:N/SC:L/SI:N/SA:N/E:U

EPSS score

Weaknesses

Exposure of Resource to Wrong Sphere

The product exposes a resource to the wrong control sphere, providing unintended actors with inappropriate access to the resource. Learn more on MITRE.

CVE ID

CVE-2026-47141

GHSA ID

GHSA-9g8x-92q2-p28f

Source code

Credits

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