Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Penetration testing is one of the most effective ways to gauge your organization’s cybersecurity readiness. While traditional security tools can block everyday threats, a penetration test (or pen test) demonstrates what might happen if a particularly clever or dedicated threat actor decided to attack your network. A well-executed pen test can reveal unexpected cybersecurity holes in both the technological and human layers at your organization.

Generative artificial intelligence (GenAI) went mainstream in 2022 with the launch of ChatGPT. Now, tech companies are turning their attention toward the next big advancement: agentic AI. Within the next few years, generative AI and agentic AI may coexist in the professional world, synthesizing information and streamlining operations more efficiently than humans can.

Every year, mobile devices become more powerful, more innovative, and more complex. That’s good news for diligent workers who want to stay connected and productive. Unfortunately, it’s also good news for threat actors who want to steal sensitive data. Zero-day vulnerabilities in mobile applications and operating systems (OSs) are becoming more common over time.

Generative artificial intelligence (GenAI) has firmly embedded itself in the workplace. As of 2024, more than two-thirds of organizations in every global region have adopted GenAI. And, as always, cyber criminals are eager to capitalize on a new and potentially powerful piece of technology. Over the past few years, a GenAI tool called FraudGPT has made phishing, hacking, and identity theft as simple as entering an AI prompt. FraudGPT and similar tools are essentially democratizing cyber crime.

Artificial intelligence (AI) has come a long way over the past six decades. From simple chatbots in the 1960s to today’s sophisticated large language models (LLMs), mimicking human behavior has always been one of AI’s most intriguing applications. At present, though, AI cannot plan or make decisions as humans do. If it could, the ethical implications of AI would suddenly become much more complex. That’s where agentic AI comes in.

AI is unlocking new ways to work across industries. Nearly four in five CEOs are implementing or likely to implement generative AI to speed up innovation across their companies, and workers at every level are using GenAI to improve or expand their processes. Unfortunately, they aren’t the only ones embracing the power of AI. WormGPT was one of the best-known early examples of an AI that could create convincing social engineering attacks and build malware.

Over the past few years, artificial intelligence (AI) has transformed millions of organizations worldwide. AI can automate rote tasks, facilitate natural-language interfaces, and pick up subtle patterns in huge data sets. It can also hallucinate wrong answers, reinforce societal biases, and even introduce cybersecurity risks. Before incorporating the technology into their workflows, responsible organizations must weigh the benefits and risks of AI.

The state of cybersecurity has always been in flux, but the arrival of tools like ChatGPT heralded one of the most significant challenges for security teams in years. AI has the potential to unlock incredible potential in data processing and malware detection, but in the wrong hands, Large Language Models (LLMs) and other adversarial AI tools can be used to develop polymorphic malware that can escape detection, gain access to sensitive data, and poison data sets.