Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Today, we’re excited to launch two practical tools to help teams quickly understand their AI maturity, quantify AI risk, and gather the evidence executives will ask for in 2026: an interactive AI Security Maturity Survey (with a personalized score and mapped recommendations) and a companion AI Security Compliance Checklist. Both are aligned to industry standards and built to be immediately useful in discovery, audits, and planning.

LLM red teaming is a proactive security practice that involves systematically testing large language models (LLMs) with adversarial inputs to find vulnerabilities before deployment. By using manual or automated methods to probe for weaknesses, red teamers can identify issues like harmful content generation, bias, or security exploits, which are then addressed through a continuous “break-fix” loop to improve the model’s safety and reliability.

Automated red teaming uses software to simulate cyberattacks and test security defenses, helping organizations find and fix vulnerabilities more efficiently. It automates tasks like credential harvesting, system enumeration, and privilege escalation to test security posture in a continuous, scalable manner. Beyond traditional systems, automated red teaming can also be used for AI systems, where it tests for risks like data poisoning or prompt injection in generative models.

How Mend.io’s ServiceNow integration helps organizations manage application, network, and operational risks together—at scale. Managing AppSec and network risk as separate programs is no longer realistic for enterprise security teams. Today’s digital environments are interconnected, distributed, and constantly changing. A single misconfiguration, unpatched server, or vulnerable open-source component can become a point of exploitation when combined with weaknesses elsewhere in the stack.

During routine monitoring of NPM registry activity, we identified a suspicious pattern involving user sdjkals who has published 10 packages containing what appear to be WOFF2 font files. Initial analysis reveals these are not legitimate font assets. The packages are scoped under @sdjkals/* with version numbers reaching 1.0.1594 and 1.0.1912, indicating extremely rapid republishing cycles, new versions are being pushed every few minutes.

On December 3, 2025, the React team disclosed CVE-2025-55182, a critical remote code execution vulnerability in React Server Components. The flaw carries a CVSS score of 10.0, the maximum severity rating. What makes this vulnerability particularly dangerous is its simplicity: attackers only need to send a single crafted HTTP request to gain complete control over vulnerable servers. No authentication required. No complex exploit chains. Just one malicious request.

Today, we’re excited to announce the availability of Mend.io’s new integration with Wiz, delivering a powerful Code-to-Cloud security workflow for joint customers. By bringing Mend SAST’s high-accuracy code findings directly into the Wiz platform, organizations can now unify code-level risks with cloud posture, runtime context, identities, and infrastructure—unlocking the complete picture needed to prioritize and remediate risk with confidence.