Net::Statsd::Lite versions through 0.10.0 for Perl allowed metric injections. The values from the set_add method were not checked for newlines, colons or pipes. Metrics generated from untrusted sources could inject additional statsd metrics. Note that version 0.9.0 fixed a similar issue CVE-2026-46719 for metric names.
Casky was already ahead
This CVE exploits attack patterns that Casky's 0matched skills already investigate — long before this vulnerability was disclosed. Claude's reasoning model maps these techniques to MITRE ATT&CK, so practitioners who ran these skills have already seen the threat behaviour in their findings.
Net::Statsd::Lite versions through 0.10.0 contain a metric injection vulnerability where the set_add method fails to sanitize values for newlines, colons, and pipes—special characters used as delimiters in the StatsD protocol. This allows attackers who control metric values to inject arbitrary StatsD commands, potentially poisoning monitoring data, triggering false alerts, or disrupting observability systems that rely on accurate metrics. Organizations using this Perl library for application instrumentation and metrics collection are at risk, particularly those processing untrusted data or user input through their monitoring pipelines.
While this CVE maps to CWE-93 (Improper Neutralization of Special Elements in Data Query Construction) rather than specific MITRE ATT&CK techniques, Casky's security skills help practitioners detect injection attack patterns through input validation analysis and protocol-level anomaly detection. A practitioner using Casky would identify that the vulnerability stems from missing input sanitization checks—a critical control gap. Though no MITRE techniques currently map to this CVE, detection would focus on Resource Development and Reconnaissance phases where attackers probe for injection points, followed by Defense Evasion when they attempt to manipulate monitoring systems. Security teams should prioritize upgrading to patched versions and implementing input validation layers that strip or escape newlines, colons, and pipes from any user-controlled metric values before they reach the StatsD client.
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