Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

A new Linux kernel LPE disclosed by Theori/Xint lets any unprivileged local user become root with a 732-byte Python script. Works first try, no race, no per-kernel offsets. CVSS 7.8 (High), effectively critical for shared-kernel and multi-tenant environments.

This post covers a supply chain attack introducing a capability not seen before: using an AI coding assistant’s own GitHub access to commit malicious code to a corporate repository.

Part 1 covered CanisterWorm, the self-spreading npm worm. Part 2 covered the malicious LiteLLM package. Part 3 covered the telnyx WAV steganography attack. Part 4 covered the xinference AI inference attack. This post covers: a compromised @bitwarden/cli package that combines a self-propagating npm worm, a GitHub Actions secrets dumper, and a novel AI assistant poisoning technique.

Part 1 covered CanisterWorm. Part 2 covered the malicious LiteLLM package. Part 3 covered the Telnyx WAV steganography attack. This post covers the latest wave: three malicious versions of xinference on PyPI, carrying the same credential-stealing playbook and a plot twist. On April 22, 2026, Mend.io’s threat detection identified malicious versions of xinference on PyPI: 2.6.0, 2.6.1, and 2.6.2.

Why the next Log4Shell will be won or lost in the first 72 hours—and what a modern zero‑day workflow looks like. Every security team remembers where they were when Log4Shell dropped. A quiet Friday afternoon in December 2021 turned into a weekend of war rooms, emergency patches, and executive updates. Years on, the Log4j fallout still shows up in breach reports—a stubborn reminder that zero‑days don’t end when the news cycle does.

SAST, or Static Application Security Testing, is a method of analyzing source code to find vulnerabilities before the application is deployed. It's a type of white box testing that scans the code without executing it, looking for weaknesses that could be exploited. SAST helps developers identify and fix security issues early in the Software Development Life Cycle (SDLC), potentially reducing costs and improving the overall security posture of the application.

Software Composition Analysis (SCA) tools expose the risks in open source dependencies by identifying vulnerabilities, outdated dependencies, and license issues in your codebase. Top solutions include Mend.io (best for automated remediation and proactive SCA), Sonatype Lifecycle (known for enterprise policy management), Snyk (known for developer experience), and Checkmarx SCA (known for comprehensive coverage).

An AI just found critical vulnerabilities that survived decades of human review. If your security program isn’t built for this moment, it’s already behind. Surprise! An AI just did what your security team couldn’t.

Mend.io’s new Docker Hardened Images integration brings DHI intelligence directly into the AppSec workflow, giving a smarter, faster path to container security. Container scanning has a noise problem. Run a standard scan against any production image, and you’ll surface thousands of CVEs.

AI application security protects AI-powered apps, including those powered by large language models ( LLMs), from unique threats like prompt injection, data poisoning, and model theft. It achieves this by securing the entire lifecycle, including code, data, algorithms, and APIs, using specialized tools and processes that go beyond traditional security measures. It involves securing the AI model’s behavior, training data, and outputs.