CVE-2025-54872
Overview
CVE-2025-54872 is a known-severity vulnerability. It was published on August 6, 2025.
Technical Description
onion-site-template is a complete, scalable tor hidden service self-hosting sample. Versions which include commit 3196bd89 contain a baked-in tor image if the secrets were copied from an existing onion domain. A website could be compromised if a user shared the baked-in image, or if someone were able to acquire access to the user's device outside of a containerized environment. This is fixed by commit bc9ba0fd.
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-2025-54872?
CVE-2025-54872 is a known-severity vulnerability. It was published on August 6, 2025.
How severe is CVE-2025-54872?
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-2025-54872?
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-2025-54872?
CyberStrike's AI-powered security agents can automatically detect CVE-2025-54872 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.