The cybersecurity issues we can't ignore in 2022
The past two years have been a baptism by fire for our cybersecurity systems.
Almost overnight, organizations adopted a remote working model that put cybersecurity blueprints to the test. We had to adapt as an industry, especially in the wake of desperate threat actors causing a 300% spike in reported cybercrimes since the pandemic kicked off.
We’ve learned a few lessons, and I’m comforted that general cybersecurity is taken more seriously, as is code-level software security and quality. President Biden’s Executive Order on securing the software supply chain illuminated critical issues, especially in the wake of the SolarWinds mass breach. The idea that we all need to care more about security and work to reduce vulnerabilities with measurable security awareness is a more significant part of the conversation.
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Forbes: A New Frontier: NSA Proposes “Security By Design” Considerations For AI Enablement
The cybersecurity industry, which has been advocating for “security by design” principles for more than a decade, stands in wide-eyed amazement at the risks posed by artificial intelligence (AI). As organizations rush to embrace AI enablement, a CISO’s most pressing priority is to avoid becoming a roadblock. However, without effective AI usage and governance, observability and traceability, organizations may be blindsided by their AI risk.
Techpartner.news: Secure Code Warrior introduces framework to govern AI use in software development
Secure Code Warrior has introduced the SCW AI Adoption Model, a framework designed to help organisations govern AI use in software development as the industry shifts from the traditional software development lifecycle (SDLC) toward what the company calls the Agentic Development Lifecycle (ADLC).
DevOps.com: Are LLMs Equally Good (or Bad) at Building Secure Software?
With many software engineering teams moving from AI coding assistants into full agentic AI code generation and increasing the amount of code they produce exponentially, ensuring the security of that code must be a top priority. The study produces practical guidance for organizations that are getting on board the AI-assisted or agentic code development train.
Secure AI-driven development before it ships
See developer risk, enforce policy, and prevent vulnerabilities across your software development lifecycle.
