MCP Server Management Options in VS Code
MCP Server Management Options in VS Code Check out the full video.
Security | Threat Detection | Cyberattacks | DevSecOps | Compliance
The Latest Cybersecurity News & Insights From Around The World
Implementing Robust Security Protocols for Agentic AI Autonomy
In this new wave of machine-driven decision-making, the paradigm shift in artificial intelligence towards increasing autonomy is becoming increasingly significant. Autonomous or agentic AI systems, those capable of acting on their own and acclimatising themselves to new environments, are redefining the space by taking actions towards a goal without direct human intervention. Although this is exciting in terms of what it will enable for AI driven processes and creativity, it also introduces a more advanced set of security risks to contend with when dealing with autonomous based AI systems.
Exabeam Nova Automates Investigations | AI-Generated Threat Summaries Explained
Can your SIEM generate a threat summary before the analyst even starts investigating? Meet Exabeam Nova — the industry’s first multi-agent AI platform that delivers proactive, clear, and actionable summaries to speed up investigations and reduce analyst burnout. AI-generated investigation summaries Boost SOC productivity and morale Real Intelligence. Real Security. Real Fast. Subscribe for more product demos and cybersecurity insights!
How Exabeam Builds Dynamic Threat Timelines with AI | Say Goodbye to Alert Fatigue
Over 100 vendors claim to have a SIEM. Most can't deliver. See how Exabeam Threat Center uses AI and behavioral analytics to automatically build dynamic threat timelines to reduce alert fatigue, false positives, and triage time. Prioritize threats by risk score Automate correlation across users, assets, and events Real Intelligence. Real Security. Real Fast. Subscribe for more product demos and cybersecurity insights!
Security-Conscious AI Software Development with Windsurf x Aikido
Modern development teams do far more than simply write code. Now, with the help of AI, software development organizations are orchestrating its creation, maintenance, and delivery at a bigger scale than ever before. Tools like Windsurf and Devin from Cognition help developers across the Software Development Lifecycle (SDLC) by augmenting people with multi-step reasoning agents that can write code.
The challenges of securing AI adoption with Jeremy Snyder
We explored the challenges of securing AI adoption with Jeremy Snyder, Founder and CEO FireTail.ai!
Meeting the AI Mandates with Confidence: Why Federal Teams Trust Snyk
Federal agencies are moving fast to unlock AI's potential—from improving citizen services to driving mission outcomes. But with all that innovation comes a new wave of complexity and risk. Security, trust, and transparency can’t be afterthoughts. They need to be part of the build and AI adoption process from day one. AI-driven development is exponentially increasing both code speed and code insecurity, as AI generates code with up to 40% more vulnerabilities than human developers.
The security principles guiding 1Password's approach to AI
AI is transforming the way we work. There are immense opportunities for automation, intelligent decision-making, and productivity gains. This transformation is a tremendous opportunity, but it also comes with tremendous responsibility, especially when security is involved. For example, AI systems can now act on behalf of users, access sensitive data across tools, and make decisions without oversight, all of which have security implications.
The Role of AI in Cybersecurity
Artificial intelligence (AI) is not a new concept or technology in the world of cybersecurity. It’s been iterated and utilized by security professionals for decades. But as both cybersecurity technology and cyber threats continue to advance, AI is being adopted by organizations at a rapid pace, all of whom seek to harness AI’s power to automate, advance, and empower their security.
Why Prompt Scanning & Filtering Fails to Detect AI Risks [& What to do Instead]
Enterprises deploying AI agents and LLMs often look to prompt scanning as their first line of defense against privacy and security breaches. The idea is simple: analyze the text of the user’s prompt before it reaches the model, detect it for sensitive keywords or patterns, and block the sensitive words that may trigger a security or compliance issue. Enterprises thought this was a safe around, till they walked into unexpected issues.