Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Data privacy is not just a checkbox for compliance requirements. It has become a core business expectation. Customers now want to know how companies collect, store, process, and protect their data. At the same time, global regulations like the GDPR and CCPA have made privacy a critical part of product development. According to a report by the Cisco Consumer Privacy Survey, 99% of companies saw measurable benefits by investing in privacy.

Researchers at Malwarebytes warn that a fake ChatGPT download site is delivering malware. The attackers use sponsored results and SEO manipulation to target users who search for “ChatGPT download.” The phishing page is a convincingly spoofed version of the legitimate ChatGPT website, which delivers malware tailored to Windows or Mac users.

Hong Kong’s Protection of Critical Infrastructures (Computer Systems) Ordinance (Cap. 653) represents a major shift in cybersecurity regulation. The law moves beyond traditional compliance exercises and places a much stronger emphasis on continuous operational resilience. For designated Critical Infrastructure (CI) operators, the challenge is no longer simply deploying security controls.

AI agents can investigate a single vulnerability brilliantly, but that is only about 20% of vulnerability remediation. This post breaks down the other 80%: the data normalization, cross-tool asset identity, SLA enforcement, exception governance, and audit evidence that turn individual agent outputs into a governed, provable remediation program, and why AI and a platform like Seemplicity work better together than apart.

The rapid adoption of generative AI has transformed enterprise productivity, but it’s also quietly introduced a new, sophisticated vulnerability: the AI insider threat. For years, securing the internal perimeter meant watching for data exfiltration via USB sticks or unauthorized emails. Today, the risk looks entirely different.

How Agentic AI Is Outpacing the Compliance Frameworks Built to Contain It.

Picture two realities for the same compliance control reaching production. Reality One: Your AppSec team writes a new rule. An engineer uses Claude Code or Cursor to generate the OPA (Open Policy Agent) Rego policy in minutes. They deploy it. It blocks a legitimate release on a missing context variable, and the on-call engineer routes around the gate to ship the code. The AI gave them fast code — but not code they could trust.