CVE-2026-46741
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Metric Injection in Etsy::StatsD Perl Library

Publication date: 2026-06-04

Last updated on: 2026-06-19

Assigner: CPANSec

Description
Etsy::StatsD versions through 1.002002 for Perl allow metric injections. The metric names and values are not checked for newlines, colons or pipes. Metrics generated from untrusted sources could inject additional statsd metrics. Note that the git repository contains an unreleased version with the gauge and set methods that also do not check for potential metric injections.
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Meta Information
Published
2026-06-04
Last Modified
2026-06-19
Generated
2026-06-25
AI Q&A
2026-06-04
EPSS Evaluated
2026-06-23
NVD
CVE-2026-46741
EUVD
EUVD-2026-34296
Affected Vendors & Products
Showing 1 associated CPE
Vendor Product Version / Range
sanbeg etsy to 1.002002 (inc)
Helpful Resources
Exploitability
CWE
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KEV
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CWE ID Description
CWE-150 The product receives input from an upstream component, but it does not neutralize or incorrectly neutralizes special elements that could be interpreted as escape, meta, or control character sequences when they are sent to a downstream component.
CWE-93 The product uses CRLF (carriage return line feeds) as a special element, e.g. to separate lines or records, but it does not neutralize or incorrectly neutralizes CRLF sequences from inputs.
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Executive Summary

This vulnerability exists in Etsy::StatsD versions through 1.002002 for Perl, where metric names and values are not properly validated for special characters such as newlines, colons, or pipes.

Because of this lack of validation, metrics generated from untrusted sources can inject additional StatsD metrics, potentially manipulating the metrics system.

Additionally, the unreleased version in the git repository includes gauge and set methods that also do not check for potential metric injections.

Impact Analysis

This vulnerability can allow attackers or untrusted sources to inject arbitrary metrics into the StatsD system.

Such metric injections could lead to inaccurate or misleading monitoring data, which may affect system monitoring, alerting, and decision-making processes.

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