Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Industrial control systems (ICS) and SCADA (Supervisory Control and Data Acquisition) environments were never designed to be exposed to the internet. Yet, as manufacturing enterprises embrace digital transformation, they find themselves in a challenging position—balancing operational efficiency with cybersecurity risk.

DeepSeek’s rapid ascent in the AI space has made it impossible to ignore. Its sophisticated models and AI assistant have captured global attention. And, while headlines focus on DeepSeek’s capabilities, STRIKE research exposes critical security flaws, hidden data flows, and unanswered questions about who has access to the data and why.

The explosion of AI has led to the creation of tools that make it more accessible, leading to more adoption and more numerous, less sophisticated users. As with cloud computing, that pattern of growth leads to misconfigurations and, ultimately, leaks. One vector for AI leakage is exposed Ollama APIs that allow access to running AI models. Those exposed APIs create potential information security problems for the models’ owners.

Region: European Union (Global impact for companies handling EU residents' data) Scope: Data privacy, security, and governance The GDPR sets the gold standard for data protection, demanding comprehensive compliance across a spectrum of activities. Organizations must ensure lawful data processing, gain explicit consent, enable data portability, and implement measures like data protection by design and default.

The question of ownership is one of the biggest reasons vulnerabilities persist in organizations far longer than they should. Who owns vulnerabilities? This isn’t just a theoretical debate—it’s a critical operational issue. Modern scanning solutions excel at identifying and prioritizing vulnerabilities, but without clear ownership, those vulnerabilities often linger unaddressed or improperly documented, increasing an organization’s risk exposure.

‍As digital threats grow more sophisticated and cyber regulations expand in scope, business stakeholders are beginning to recognize the need to learn more about cybersecurity and how it impacts organizational performance. With this recognition comes the elevation of chief information security officers (CISOs) into the boardroom, tasked with explaining these cyber intricacies and offering strategies that can help safeguard operational resilience and drive long-term growth.

This article explores the recommended infrastructure for AI workloads, strategies to optimize performance on less expensive servers, and trade-offs in terms of cost and results. We’ll also provide examples of AWS EC2 instance types and pricing to illustrate practical options.

The recent rapid adoption of the AI application “DeepSeek” has gained significant global attention. Becoming the app on both the Apple Store and Google Play Store within its first few days, seeing over 10 million downloads. While this explosive growth of DeepSeek R1 highlights the public’s fascination with AI-driven tools, the security community and policymakers have been less enthusiastic.

With increased reliance on the cloud and data being today’s digital currency, cybercrime has become a pervasive threat that impacts individuals, businesses, and governments alike. Understanding the various types of cybercrime is essential for developing effective strategies to protect against these malicious activities.

This article provides details on how Bitsight TRACE addressed CVE-2024-23897, an arbitrary file read vulnerability that affects Jenkins, a well-known open-source automation server. It includes technical details, common pitfalls, and decisions made since the CVE disclosure until now. The investigation of CVE-2024-23897 is an example of how we can obtain the target instance version but not solely rely on it to classify an instance as vulnerable. First, we go deep to understand the vulnerability.