CVE-2026-55195
Overview
CVE-2026-55195 is a known-severity vulnerability. It was published on July 8, 2026.
Technical Description
py7zr is a Python-based library and utility to support 7zip archive compression, decompression, encryption and decryption. Prior to 1.1.3, py7zr's Worker.decompress() extracted archive entries without tracking total decompressed size, allowing a crafted .7z file such as a 15.6 KB archive that expands to 100 MB to exhaust disk or memory before extraction completes. This issue is fixed in version 1.1.3.
Remediation
Check the references section for vendor advisories, patches, and mitigation guidance. If immediate patching is not possible, review the CVSS vector to understand the attack surface and apply compensating controls such as network segmentation or access restrictions.
Frequently Asked Questions
What is CVE-2026-55195?
CVE-2026-55195 is a known-severity vulnerability. It was published on July 8, 2026.
How severe is CVE-2026-55195?
CVSS score information is not yet available for this vulnerability. Check back as the CVE record is updated by NVD analysts.
How do I fix or remediate CVE-2026-55195?
Check the references section for vendor advisories, patches, and mitigation guidance. If immediate patching is not possible, review the CVSS vector to understand the attack surface and apply compensating controls such as network segmentation or access restrictions.
How can CyberStrike help with CVE-2026-55195?
CyberStrike's AI-powered security agents can automatically detect CVE-2026-55195 across your infrastructure using autonomous pentesting, DAST scanning, and HackBrowser. The platform continuously monitors for known vulnerabilities and provides actionable remediation guidance prioritized by real-world exploitability.
How CyberStrike Helps
AI agents map your attack surface to find vulnerabilities like this one.
Automated penetration testing that runs continuously, not just quarterly.
AI-driven PR review catches vulnerable dependencies before they ship.
Browser-based exploitation validates findings with real proof-of-concept.