Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

AI desktop assistants and coding tools need credentials to reach external services, and many of them store those credentials as plaintext JSON at predictable paths in the user's home directory. This research covers how credential storage works across 14 popular AI tools, where OS keychain integration is present or missing, and eight attack scenarios that turn that exposure into real risk, from malware-based theft to remote session hijacking to supply-chain compromise via MCP servers.

Built-in browser password managers are convenient. For enterprise secrets, convenience is not a security strategy. There are two kinds of password storage in the world: the kind that helps you log in to your favorite lunch-ordering site faster, and the kind that protects the credentials that can unlock your business. Sadly, many organizations treat both the same way.

Here's a number worth sitting with: the CIS Microsoft Windows 11 Enterprise Benchmark v4.0.0 is 1,364 pages long and covers more than 500 individual configuration settings. That's one operating system. Add your Linux servers, network devices, databases, and cloud workloads, and you're looking at a configuration surface area no team can stay on top of manually. A CIS benchmark tool solves that problem at scale.

A French channel partner recently won two top awards at the Cas d'Or 2026 for a public-sector identity governance project. The recognition covered Cyber Governance & Risk Management and the Public Sector category. Here's a look at what the win signals about identity governance in public organizations and how modern IGA platforms help tackle budget pressure, compliance demands, and complex user populations. Identity governance in the public sector rarely makes headlines.

Identity threat detection and response (ITDR) tools close the visibility gap that EDR and MFA leave open. They surface credential misuse, lateral movement, and Active Directory activity that appears legitimate to endpoint and perimeter defenses. The right fit depends on your identity infrastructure, detection depth, and whether you need real-time blocking or post-event response.

For twenty years, cybersecurity defense rested on a simple idea: make attacking so expensive that adversaries give up and move on. Cheap, capable AI breaks those economics. Recon, exploit development, phishing, and command-and-control infrastructure now run at model speed and cent-per-million-tokens cost. The detect-and-respond doctrine struggles when an attacker’s OODA loop compresses from weeks to seconds. The prevention bar has to rise from blocking known-bad to predicting intent from behavior.

User and entity behavior analytics (UEBA) is a cybersecurity technology that uses machine learning and risk scoring to detect threats by analyzing user and entity behavior patterns. UEBA establishes behavioral baselines for users, devices, and applications, then identifies anomalies that may indicate insider threats, compromised accounts, or advanced attacks that traditional security tools miss.

Non-human identities (NHIs) such as service accounts, API keys, tokens, and workload identities now outnumber human users by 10x or more in most organizations. Unlike human identities that follow HR-driven lifecycles, NHIs are often created ad hoc, granted excessive permissions, and rarely decommissioned. Effective NHI lifecycle management spans five stages: discovery and inventory, secure provisioning, ongoing monitoring, credential risk management (including rotation), and decommissioning.

Controlled unclassified information (CUI) protection requires consistent identification, marking, safeguarding, and access governance across every system that touches federal data. With CMMC Phase 1 underway and the FAR CUI rule in effect, compliance is now a contract prerequisite. Controlled unclassified information (CUI) is sensitive but unclassified information that requires safeguarding or dissemination controls under federal law, regulation, or government-wide policy.

PCI DSS compliance levels categorize merchants and service providers based on annual card transaction volume, determining their validation requirements. Merchants fall into four levels, with Level 1 requiring the most rigorous assessment through a Qualified Security Assessor, while Levels 2 through 4 typically complete self-assessment questionnaires. Service providers follow a separate two-tier system.