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Security | Threat Detection | Cyberattacks | DevSecOps | Compliance
The Latest Cybersecurity News & Insights From Around The World
LangGraph and Reflection Agents - This Week in AI
In the ever-evolving terrain of artificial intelligence, OpenAI's LangGraph is making waves by introducing a groundbreaking approach to code generation and analysis. With the prominence of tools like GitHub Co-Pilot and the popularity of projects such as GPT-engineer, the demand for innovative solutions in this domain has never been higher. LangGraph aims to meet this demand by leveraging a flow paradigm inspired by recent advancements like AlphaCodium to enhance the efficiency of code generation.
DevSecOps in an AI world requires disruptive log economics
We’ve been talking about digital transformation for years (or even decades?), but the pace of evolution is now being catapulted forward by AI. This rapid change and innovation creates and relies upon exponential data sets. And while technology is rapidly evolving to manage and maintain these massive data sets, legacy pricing models based on data ingest volume are lagging behind, making it economically unsustainable.
A Complete Step-by-Step Guide to Achieve AI Compliance in Your Organization
AI compliance has become a pivotal concern for organizations in a rapidly evolving technological landscape. It is inconceivable to overlook the growing importance of AI compliance, particularly for entities deeply entrenched in AI operations. It involves an intricate intersection of legal, ethical, and regulatory dimensions, emphasizing the need for a cohesive approach to ensure comprehensive AI compliance.
Microsoft and OpenAI Team Up to Block Threat Actor Access to AI
Analysis of emerging threats in the age of AI provides insight into exactly how cybercriminals are leveraging AI to advance their efforts. When ChatGPT first came out, there were some rudimentary security policies to avoid it being misused for cybercriminal activity. But threat actors quickly found ways around the policies and continued to use it for malicious purposes.
5 security best practices for adopting generative AI code assistants like GitHub Copilot
Not that long ago, AI was generally seen as a futuristic idea that seemed like something out of a sci-fi film. Movies like Her and Ex Machina even warned us that AI could be a Pandora's box that, once opened, could have unexpected outcomes. How things have changed since then, thanks in large part to ChatGPT’s accessibility and adoption!
Mend.io Launches Mend AI
Securing AI is a top cybersecurity priority and concern for governments and businesses alike. Developers have easy access to pre-trained AI models through platforms like Hugging Face and to AI-generated functions and programs through large language models (LLMs) like GitHub Co-Pilot. This access has spurred developers to create innovative software at an enormously fast pace.
Cloudflare Firewall for AI Will Help Secure AI Applications, At Scale and For Free New protections will secure organisations - by default - from attempted attacks, abuse, and tampering as they increasingly rely on AI models
Cloudflare, Inc. announces the development of Firewall for AI, a new layer of protection that will identify abuse and attacks before they reach and tamper with Large Language Models (LLMs), a type of AI application that interprets human language and other types of complex data.
Elastic introduces Elastic AI Assistant
Elastic® introduces Elastic AI Assistant, the open, generative AI sidekick powered by ESRE to democratize cybersecurity and enable users of every skill level. The recently released Elasticsearch Relevance Engine™ (ESRE™) delivers new capabilities for creating highly relevant AI search applications. ESRE builds on more than two years of focused machine learning research and development made possible through Elastic’s leadership role in search use cases.
The Risks of Automated Code Generation and the Necessity of AI-Powered Remediation
Modern software development techniques are creating flaws faster than they can be fixed. While using third-party libraries, microservices, code generators, large language models (LLMs), etc., has remarkably increased productivity and flexibility in development, it has also increased the rate of generating insecure code. An automated and intelligent solution is needed to bridge the widening gap between the introduction and remediation of flaws.