Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

It’s no surprise that AI is being integrated into identity governance and administration (IGA) platforms. Automation promises productivity boosts, risk detection can be in real-time and cloud environments allow greater scalability. What’s more, the pace of AI means IGA is quickly moving beyond slower, more rigid, rule-based approaches.

Static application security testing (SAST) tools help developers quickly catch potential vulnerabilities as they code. However, these tools rely on inflexible rules that often generate a high number of false positives, reducing trust in their accuracy and slowing adoption. To help developers access context-aware vulnerability detection, we’ve released an open source AI-native SAST solution. This tool scans code changes incrementally and surfaces security issues in real time.

Technology changes every year, and one of the biggest shifts over the last decade has been a deep investment into the use of containers. Containers offer a lot of potential benefits, particularly for information security, but they also present serious risks of their own. Those risks can be mitigated, but you need to understand that the problem exists before you can address it.

Recent supply chain attacks stayed live for hours. Automation tools silently merged their malware in minutes. Read how upgrade bots and AI agents became the insider threat.

“We do not store any credit card data, we outsource it. PCI DSS is not relevant for us.” If you think this way, you are not alone, but it is a misconception. The Payment Card Industry Data Security Standard (PCI DSS), is designed to enhance the security of credit card data. It applies to all organizations that store, process, or transmit cardholder data and sensitive authentication data, or that could affect the security of the environment used for such data.

Preconstruction is no longer a buffer between design and delivery. Across UK construction projects, timelines are compressing, risk is shifting upstream, and teams are being asked to commit earlier with less certainty than ever before. At the same time, project information is increasingly fragmented across cloud platforms, project systems, shared drives, and email. Without structured information management, the speed gains from digital tools often amplify uncertainty rather than reduce it.

You built something great. Your SaaS platform is signing up users. Your app is getting traction — some from Germany, some from France, maybe a handful from Sweden. You’re based in Toronto or Vancouver, operating under PIPEDA, and things feel legally tidy. Then a European enterprise prospect sends over a data protection questionnaire and asks: “Are you GDPR compliant?” Your stomach drops. You’re not sure.

The patch management process is the structured lifecycle through which organizations identify, test, and deploy software and firmware updates to close security vulnerabilities before cyberattacks can exploit them.

Passwords are still necessary, but they are no longer sufficient. Using long, unique, and hard-to-guess passphrases remains best practice. The problem is what happens when one of those passwords falls into the wrong hands: the system doesn’t detect an intrusion—it simply sees a legitimate login. From that point on, the attacker moves through the environment like any other user.

Anthropic’s Mythos announcement is not just another cybersecurity headline. It is a signal. AI is transforming software faster than security teams can adapt. The organizations that win won’t be the ones that simply find more flaws. They’ll be the ones that can prove their software can be trusted. A signal that software risk has entered a new era; one where AI can accelerate both the creation of software and the discovery of its weaknesses faster than human teams can respond.