CVE-2026-32720

The CTFer.io Monitoring component is in charge of the collection, process and storage of various signals i.e. logs, metrics and distributed traces. Prior to 0.2.1, due to a mis-written NetworkPolicy, a malicious actor can pivot from a component to any other namespace. This breaks the...

CVE-2026-32720

The CTFer.io Monitoring component is in charge of the collection, process and storage of various signals i.e. logs, metrics and distributed traces. Prior to 0.2.1, due to a mis-written NetworkPolicy, a malicious actor can pivot from a component to any other namespace. This breaks the...

PT-2026-25861

Name of the Vulnerable Software and Affected Versions Fullchain versions prior to 0.1.1 Description Fullchain is a platform for deploying CTF Capture The Flag environments. A misconfigured NetworkPolicy allows a malicious actor to move laterally from a compromised application to any Pod in a...

CVE-2026-32720 Improper Access Control in github.com/ctfer-io/monitoring

The CTFer.io Monitoring component is in charge of the collection, process and storage of various signals i.e. logs, metrics and distributed traces. Prior to 0.2.1, due to a mis-written NetworkPolicy, a malicious actor can pivot from a component to any other namespace. This breaks the...

Simple Steps for Attack Surface Reduction

Story teaser text: Cybersecurity leaders face mounting pressure to stop attacks before they start, and the best defense may come down to the settings you choose on day one. In this piece, Yuriy Tsibere explores how default policies like deny-by-default, MFA enforcement, and application Ringfencin...

Simple Steps for Attack Surface Reduction

Story teaser text: Cybersecurity leaders face mounting pressure to stop attacks before they start, and the best defense may come down to the settings you choose on day one. In this piece, Yuriy Tsibere explores how default policies like deny-by-default, MFA enforcement, and application Ringfencin...

Unveiling the Landscape of LLM Deployment in the Wild: an Empirical Study

Background: Large language models LLMs are increasingly deployed via open-source and commercial frameworks, enabling individuals and organizations to self-host advanced AI capabilities. However, insecure defaults and misconfigurations often expose LLM services to the public Internet, posing...