The Qwiet Blog

Key Takeaways Claiming that AI alone is not sufficient proof is one thing; real value comes from demonstrating how AI actually functions, not merely stating that it exists. AI-washing erodes trust. Vague claims or superficial integrations damage credibility across the AppSec space. Agentic, transparent systems win. Teams should look for tools that integrate AI deeply, […]

Key Takeaways Shift left overburdened developers without giving them the right tools or support. The intention was solid, but the execution often left devs overwhelmed and security goals unmet. Shifting to the middle means shared responsibility, not shifted burden. With security integrated contextually into dev workflows, both speed and protection improve. Developer-security collaboration thrives when […]

Key Takeaways AI Native means built, not bolted. It’s the difference between a platform that embeds AI into its architecture and one that adds it later as a feature. Only the former can deliver meaningful context, automation, and integration across the SDLC. Developers need signal, not noise. AI-native tools like Qwiet prioritize relevance, context, and […]

Key Takeaways Even the Most Mature DevSecOps Teams Can Miss Basic Flaws: GitLab’s account takeover vulnerability illustrates how even well-resourced, security-minded organizations can overlook foundational authentication checks. There’s a Pattern of Similar Incidents Across the Industry: Microsoft, Okta, and CircleCI have all experienced recent breaches tied to identity or access logic. These are systemic, not […]

Our journey in application security has always been about empowering developers, making them the key players in shipping secure code without drowning in noise. Back in 2021, at ShiftLeft, we introduced the concept of “Attacker Reachability,” a way to focus only on those open-source vulnerabilities that could be exploited in a given application. The results […]

Key Takeaways AI-generated code is not inherently more or less secure than human-written code. The risks depend on how the code is reviewed, tested, and validated, not who or what wrote it. Security scanners treat both AI and human code the same way. They analyze syntax, structure, dependencies, and behaviors without considering the source of […]

Key Takeaways False negatives pose a significant hidden risk by allowing real vulnerabilities to slip through security scans undetected, leaving systems exposed without raising alerts. Technical limitations, changing environments, and tool trade-offs are the main reasons false negatives persist, even after decades of AppSec progress. Reducing false negatives requires a comprehensive and layered strategy that […]

Key Takeaways Agentic AI is purpose-built for specific tasks, not general interaction. It doesn’t respond to prompts like a chatbot—it operates automatically based on system-level inputs. By limiting the scope of agentic AI, we enhance its precision and reliability. This approach removes variability and user-driven input, making the model easier to train, test, and trust […]

Key Takeaways While IDE tools are beneficial for providing immediate feedback, their scope is limited. They excel at catching fundamental issues early in development, such as missing input validation, insecure function usage, or weak defaults. However, they cannot see system-wide interactions, merged branches, or production configurations. This limitation underscores the need for a more comprehensive […]