Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Rate limiting plays a major role in application security, especially when it is about defending web applications from malicious bot attacks, credential stuffing, brute force attacks and excessive API calls. Rate limiting security ensures that systems function properly without overwhelming them. It controls the number of requests a client or a specific IP address can send over a specified time period.

Web and mobile application code protection is a must-have security control. Modern solutions such as application layer firewall help your organisation to keep those assets protected from threats like SQL injection, cross-site scripting and bot-driven attacks. This is where a Web Application Firewall (WAF) comes into the picture. A WAF has the capability of filtering, monitoring and blocking HTTP requests to protect the assets from malicious requests without affecting legitimate users.

The management of user access to an organization’s assets, applications, and systems is never static. Users are coming and going, different roles require different access, and for some, privileged access – elevated permissions and access capabilities granted to specific users or groups of users — is needed for mission-critical business functions.

On June 2, 2025, Hewlett Packard Enterprise (HPE) released fixes for multiple vulnerabilities affecting HPE StoreOnce VSA, an enterprise backup storage solution. The most severe of these was CVE-2025-37093, a critical authentication bypass vulnerability discovered by the Zero Day Initiative (ZDI). The flaw resides in the implementation of the machineAccountCheck method and stems from improper handling of an authentication algorithm.

AI is not just reshaping cybersecurity. It is exposing where many organizations remain vulnerable. While attackers are racing ahead with AI-powered tools, too many defenders are still relying on outdated strategies, siloed data, and manual processes. In conversations with security leaders, I hear the same concern repeatedly. The anxiety is not just about AI-enhanced threats. It is about the growing sense that defenders are falling behind.

At BSides312 in Chicago, experts showed that defending systems requires defending people, with trust, inclusion, and communication as key controls. Defense is deeply human.

Modern infrastructure is increasingly run by automated systems, not people. Bots push code. Runners deploy to prod. Agents orchestrate cloud resources. And increasingly, AI models trigger actions directly through prompt-driven automation. Welcome to the era of non-human identities (NHIs): the invisible workforce operating behind modern digital systems.

Similar to Ollama and llama.cpp, LlamaIndex provides an application layer for connecting your data to LLMs and interacting with it through a chat interface. While LlamaIndex is an open source project like other LLM application frameworks, LlamaIndex is also a company, with a recent Series A, a commercial offering, and a more polished aesthetic than their strictly DIY counterparts.

The explosion of generative artificial intelligence tools is sparking a wave of enthusiasm in workplaces, with employees eagerly embracing new applications to boost productivity and innovation. However, this adoption often leads to a new phenomenon known as shadow AI—the use of artificial intelligence tools within an organization without explicit approval or oversight from IT and security teams. Unsanctioned use of AI creates significant (and often invisible) security blind spots.

Research is what turns cybersecurity from a reactive scramble into a proactive discipline. It’s how security teams uncover new threats, pressure-test defenses, and understand the unintended consequences of innovation (especially as AI Agents reshape the attack surface).At Zenity, research isn’t a side effort. It’s how we build, challenge, and ultimately secure what’s next.