Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Infrastructure-as-code (IaC) security scanning can catch common misconfigurations before deployment, but every organization also has internal requirements that a default rule catalog cannot cover. For example, teams may need to enforce required tags, approved instance types, or naming conventions. With custom rules for Datadog IaC Security, security and platform teams can define these requirements as Rego policies and run them alongside Datadog’s default rules during IaC scans.

On 17 September 2026, users on X (formerly Twitter) posted that payment details belonging to other individuals had appeared on the Cineworld app under their personal accounts. On 17 September 2026, users on X (formerly Twitter) posted that payment details belonging to other individuals had appeared on the Cineworld app under their personal accounts.

MSSPs are being asked to secure more clients, across more industries, with more tools than ever before. This post explains why simply adding another threat feed to the stack doesn't solve the problem, and what MSSPs need to operationalise intelligence at scale.

A critical SQL injection vulnerability has been identified in cPanel & WHM’s EmailTrack functionality. The vulnerability was disclosed by cPanel on September 8, 2026, affecting every supported release line. It allows an authenticated cPanel account holder with mail related privileges to ultimately achieve root-level code execution on the underlying host.

SLH-DSA is NIST’s standardised post-quantum digital signature algorithm (hash-based). It generates quantum-resistant signatures, ensuring signatures are not changeable and that they will not be forged, even when later superseded by schemes like RSA and ECDSA, which are susceptible to attacks by quantum computers. Organisations are studying it today because large-scale quantum computers could, in the future, crack the algorithms that currently underpin most digital trust.

AI is set to provide increasing value in IT by enabling more ways to simplify complex IT operations, offering actionable insights, automating routine tasks with context-aware automation, and detecting abnormal events with advanced machine learning algorithms. With agentic AI, systems can understand what is happening in an IT environment, reason about the most probable root causes, determine the right course of action, and implement these changes without requiring additional human intervention.

AI uncertainty is not a strategic reason to wait; it is a strategic imperative to build adaptable organizations that can innovate confidently, govern risk proportionately, and respond effectively as technology and threats evolve. Every few weeks, the AI conversation seems to reset around a new warning. A model demonstrates an unexpected capability. An autonomous agent behaves in a way its designers did not anticipate. A new forecast describes how quickly AI could transform work, security or society.

When organizations experience a cyberattack, executives often focus on recovery timelines, business impact, and regulatory obligations. Yet the outcome of those conversations is often determined long before recovery begins.

Most security tools evaluate risk by looking at the file, but risk is no longer confined to files. A clause pasted into an AI prompt carries no filename. A table summarized into Slack carries no label. A screenshot dropped into a deck carries no metadata, yet none of these trip an alert, because legacy data loss prevention (DLP) was built for a world where the sensitive unit is a discrete object with a name, a location, and a policy attached to it. That world is gone.