CVE-2026-3381: CWE-1395 Dependency on Vulnerable Third-Party Component in PMQS Compress::Raw::Zlib
Compress::Raw::Zlib versions through 2.219 for Perl use potentially insecure versions of zlib. Compress::Raw::Zlib includes a copy of the zlib library. Compress::Raw::Zlib version 2.220 includes zlib 1.3.2, which addresses findings fron the 7ASecurity audit of zlib. The includes fixs for CVE-2026-27171.
AI Analysis
Technical Summary
CVE-2026-3381 identifies a critical security vulnerability in the Perl module Compress::Raw::Zlib, specifically in versions up to 2.219. This module bundles its own copy of the zlib compression library, which in these versions is outdated and contains multiple security flaws. The vulnerability is categorized under CWE-1395, indicating a dependency on a vulnerable third-party component. The affected zlib versions have been found to have serious security issues, including those addressed in CVE-2026-27171, which was uncovered during a 7ASecurity audit. The vulnerability allows an unauthenticated attacker to remotely exploit the compression functionality, potentially leading to full compromise of confidentiality, integrity, and availability of systems using the module. The CVSS v3.1 base score is 9.8, reflecting network attack vector, low attack complexity, no privileges required, and no user interaction needed. The scope is unchanged, but the impact on confidentiality, integrity, and availability is high. The fix is incorporated in Compress::Raw::Zlib version 2.220, which updates the embedded zlib library to version 1.3.2, remediating the identified issues. No public exploits have been reported yet, but the severity and ease of exploitation make this a critical threat for any Perl-based applications relying on this module for compression tasks.
Potential Impact
The vulnerability poses a critical risk to organizations worldwide that utilize Perl applications depending on Compress::Raw::Zlib for compression. Exploitation can lead to remote code execution, data leakage, data corruption, or denial of service, severely impacting confidentiality, integrity, and availability. Since the vulnerability requires no authentication or user interaction, attackers can exploit it remotely over the network, increasing the attack surface significantly. This can affect web servers, backend services, and any software components that perform compression using the vulnerable module. The widespread use of Perl in legacy systems, network appliances, and embedded devices further broadens the potential impact. Organizations may face operational disruptions, data breaches, and compliance violations if the vulnerability is exploited. The lack of known exploits in the wild currently provides a window for proactive mitigation before active attacks emerge.
Mitigation Recommendations
Organizations should immediately identify all systems and applications using Compress::Raw::Zlib versions up to 2.219. The primary mitigation is to upgrade to Compress::Raw::Zlib version 2.220 or later, which includes the updated and secure zlib 1.3.2 library. For environments where immediate upgrade is not feasible, consider isolating affected systems from untrusted networks and restricting network access to limit exposure. Implement network-level intrusion detection and prevention systems tuned to detect anomalous compression-related traffic patterns. Conduct thorough code audits to identify any custom usage of the vulnerable compression functions and apply patches or workarounds where possible. Maintain up-to-date backups and incident response plans to quickly recover from potential exploitation. Monitor security advisories for any emerging exploit code or additional patches related to this vulnerability. Engage with Perl module maintainers and security communities to stay informed about further developments.
Affected Countries
United States, Germany, United Kingdom, France, Japan, Canada, Australia, India, Netherlands, South Korea, China, Brazil
CVE-2026-3381: CWE-1395 Dependency on Vulnerable Third-Party Component in PMQS Compress::Raw::Zlib
Description
Compress::Raw::Zlib versions through 2.219 for Perl use potentially insecure versions of zlib. Compress::Raw::Zlib includes a copy of the zlib library. Compress::Raw::Zlib version 2.220 includes zlib 1.3.2, which addresses findings fron the 7ASecurity audit of zlib. The includes fixs for CVE-2026-27171.
AI-Powered Analysis
Machine-generated threat intelligence
Technical Analysis
CVE-2026-3381 identifies a critical security vulnerability in the Perl module Compress::Raw::Zlib, specifically in versions up to 2.219. This module bundles its own copy of the zlib compression library, which in these versions is outdated and contains multiple security flaws. The vulnerability is categorized under CWE-1395, indicating a dependency on a vulnerable third-party component. The affected zlib versions have been found to have serious security issues, including those addressed in CVE-2026-27171, which was uncovered during a 7ASecurity audit. The vulnerability allows an unauthenticated attacker to remotely exploit the compression functionality, potentially leading to full compromise of confidentiality, integrity, and availability of systems using the module. The CVSS v3.1 base score is 9.8, reflecting network attack vector, low attack complexity, no privileges required, and no user interaction needed. The scope is unchanged, but the impact on confidentiality, integrity, and availability is high. The fix is incorporated in Compress::Raw::Zlib version 2.220, which updates the embedded zlib library to version 1.3.2, remediating the identified issues. No public exploits have been reported yet, but the severity and ease of exploitation make this a critical threat for any Perl-based applications relying on this module for compression tasks.
Potential Impact
The vulnerability poses a critical risk to organizations worldwide that utilize Perl applications depending on Compress::Raw::Zlib for compression. Exploitation can lead to remote code execution, data leakage, data corruption, or denial of service, severely impacting confidentiality, integrity, and availability. Since the vulnerability requires no authentication or user interaction, attackers can exploit it remotely over the network, increasing the attack surface significantly. This can affect web servers, backend services, and any software components that perform compression using the vulnerable module. The widespread use of Perl in legacy systems, network appliances, and embedded devices further broadens the potential impact. Organizations may face operational disruptions, data breaches, and compliance violations if the vulnerability is exploited. The lack of known exploits in the wild currently provides a window for proactive mitigation before active attacks emerge.
Mitigation Recommendations
Organizations should immediately identify all systems and applications using Compress::Raw::Zlib versions up to 2.219. The primary mitigation is to upgrade to Compress::Raw::Zlib version 2.220 or later, which includes the updated and secure zlib 1.3.2 library. For environments where immediate upgrade is not feasible, consider isolating affected systems from untrusted networks and restricting network access to limit exposure. Implement network-level intrusion detection and prevention systems tuned to detect anomalous compression-related traffic patterns. Conduct thorough code audits to identify any custom usage of the vulnerable compression functions and apply patches or workarounds where possible. Maintain up-to-date backups and incident response plans to quickly recover from potential exploitation. Monitor security advisories for any emerging exploit code or additional patches related to this vulnerability. Engage with Perl module maintainers and security communities to stay informed about further developments.
Technical Details
- Data Version
- 5.2
- Assigner Short Name
- CPANSec
- Date Reserved
- 2026-02-28T09:24:49.085Z
- Cvss Version
- null
- State
- PUBLISHED
Threat ID: 69a8e7f5d1a09e29cba26c42
Added to database: 3/5/2026, 2:18:29 AM
Last enriched: 3/12/2026, 7:19:04 PM
Last updated: 4/19/2026, 8:41:17 AM
Views: 335
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