PRESS RELEASE: Qwiet AI Expands Integrations, Language Support, and AutoFix Capabilities | Read Here
Key Takeaways AI has transformed both software development and the threat landscape. Code is being generated faster than ever, often without the context or security awareness needed to keep it safe. This demands a new approach to how we think about application security. Traditional AppSec tools fall short in modern, AI-assisted workflows. Legacy scanners struggle […]
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Key Takeaways AI has transformed both software development and the threat landscape. Code is being generated faster than ever, often without the context or security awareness needed to keep it safe. This demands a new approach to how we think about application security. Traditional AppSec tools fall short in modern, AI-assisted workflows. Legacy scanners struggle […]
Key Takeaways Log4j is still present in many applications due to transitive dependencies and outdated libraries, making it a current, not just historical, threat. Traditional security tools often bury real threats like Log4j under layers of unrelated alerts, making it hard for developers to know what matters. Qwiet helps developers prioritize and fix real vulnerabilities […]
Key Takeaways Agentic AI brings context and reasoning to security, helping tools detect vulnerabilities and whether they’re exploitable based on code behavior. Contextual reachability filters out noise by mapping real data and control flow, giving developers clear and actionable findings. Qwiet AI’s CPG and agentic model support precision and automation, aligning AppSec with the realities […]
Claude’s announcement about vulnerability detection capabilities got me thinking. As someone who uses Claude Code daily and has built deterministic analysis tools, I’ve seen both the incredible potential and the real limitations of LLMs in security work. Let me be clear upfront: Claude Code has become indispensable in my workflow. The productivity gains are real. […]
Sorry, we missed you at our Black Hat 2025 Playbook webinar with Cyera and Qwiet AI! We shared a quick, informative breakdown of what we’re most excited about for next week, and while you couldn’t make it, we still want you in the loop. If you haven’t registered for our events yet, no worries, we’ve included the […]
Key Takeaways Shift-left alone isn’t enough. With AI-generated code and fast CI/CD, static scans during development can’t detect runtime risk or traceable exploits. Shift-everywhere integrates context-aware security. By using tools like Code Property Graphs, ownership mapping, and exploit reachability analysis, teams can embed actionable security logic throughout the SDLC. Developers need fewer alerts and more insight. […]
Key Takeaways Understanding the security risks introduced by machine learning systems beyond the model layer is crucial. These risks include outdated dependencies, weak secrets management, and architectural mismatches in legacy codebases. Secret sprawl is a growing concern, especially with AI agents embedded in CI/CD workflows. This trend makes runtime exposure, hardcoded credentials, and misconfigurations increasingly […]
Key Findings The SAIL (Secure AI Lifecycle) Framework outlines AI-specific risks across the lifecycle, but lacks implementation details. Qwiet AI fills this gap with direct, technical controls focused on code and configuration-level vulnerabilities. Qwiet AI aligns with SAIL Phases 2 and 3 by identifying hidden AI assets, detecting hardcoded secrets, auditing third-party AI components, and […]
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, […]
