CVE-2026-46739: Net::Statsd Metric Injection Vulnerability (Perl)

Technical summary

CVE-2026-46739 describes an improper input validation vulnerability in Net::Statsd's metric transmission logic. The library does not sanitize metric names for reserved statsd protocol characters (newlines, colons, pipes) before transmission, and the update_stats and gauge methods accept non-numeric values without validation. This permits an attacker to break out of the intended metric format and inject new metrics into the statsd server. The attack surface expands when metric names or values originate from untrusted sources—including HTTP query parameters, API responses, or user-controlled input. The vulnerability maps to CWE-150 (Improper Neutralization of Input Leaders in Data Messages) and CWE-93 (Improper Neutralization of CRLF Sequences in HTTP Headers).

Business impact

Successful exploitation can lead to inaccurate monitoring and alerting. Attackers could suppress legitimate alerts by injecting noise, exfiltrate monitoring data structure information, or cause alert fatigue by flooding the monitoring backend. In environments where statsd metrics drive auto-scaling decisions or SLA calculations, injected metrics could trigger unintended infrastructure changes or mask real incidents. The impact is primarily to observability and operational decision-making rather than direct data breach or service availability.

Affected systems

Net::Statsd for Perl versions before 0.13 are vulnerable. Organizations should inventory Perl applications that depend on Net::Statsd, particularly those that accept untrusted input and pass it to statsd metric methods. Affected systems are typically monitoring and observability stacks that rely on statsd protocol integration.

Exploitability

The vulnerability requires network access to an application that uses Net::Statsd and accepts untrusted metric names or values. No authentication is required, and exploitation is straightforward—simply inject a newline or pipe character into a metric name to break protocol boundaries. However, real-world impact depends on the application's data flow; not all uses of Net::Statsd receive untrusted input. The CVSS score of 5.3 (MEDIUM) reflects low confidentiality and availability impact but non-zero integrity risk.

Remediation

Upgrade Net::Statsd to version 0.13 or later, which includes input validation for metric names and numeric type checking for values. Verify the upgrade across all deployed Perl environments and test metric reporting post-patch. As a compensating control, applications should validate and sanitize metric names and values before passing them to Net::Statsd methods, even if the library implements fixes.

Patch guidance

Apply Net::Statsd version 0.13 or newer. Use your Perl package manager (e.g., cpan, cpanm) to upgrade the module. Verify the installed version with 'perl -MNet::Statsd -e 'print $Net::Statsd::VERSION''. Coordinate with application teams to test metric delivery after patching, as validation logic changes may affect edge cases. No special configuration changes are required post-patch.

Detection guidance

Monitor for suspicious metric injections in statsd server logs or collectors. Look for metric names or values containing unusual characters (newlines, pipes, colons in unexpected positions) or metrics that appear anomalous in structure or timing. Network-based detection is difficult without deep packet inspection; log-based detection on the statsd server side is more practical. Correlate unexpected metric surges or malformed metrics with application access logs if possible.

Why prioritize this

Although the CVSS score is MEDIUM (5.3), prioritization should account for deployment context. Upgrade this module in 30 days for most environments, but expedite if your application processes user-supplied metric names or values (e.g., user-generated event names, dynamic tags). The vulnerability does not appear on the CISA KEV list, indicating lower exploitation activity in the wild currently. Low urgency for applications that only generate metrics from trusted, internal sources.

Risk score, explained

CVSS 3.1 score of 5.3 reflects: Attack Vector: Network (attacker can exploit remotely), Attack Complexity: Low (no special conditions needed), Privileges Required: None, User Interaction: None, Scope: Unchanged (impact limited to the statsd service), Confidentiality: None, Integrity: Low (metrics can be altered), Availability: None. The score does not account for application-specific data flows; organizations processing untrusted metric input should elevate risk internally.

Frequently asked questions