Category: AI Security
Private Prompt Templates: Stopping Inference-Time Data Leakage
Stop inference-time data leakage in LLMs. Learn how private prompt templates, masking, and governance prevent costly breaches and meet new regulations.
Privacy and Security Risks of Distilled LLMs: A Practical Guide
Distilled LLMs offer efficiency but inherit privacy risks from teacher models and face new extraction vulnerabilities. Learn how to secure deployments with TEEs, LUCID testing, and regulatory compliance strategies.
Why Better Reasoning in LLMs Makes Safety Harder: 2026 Analysis
Discover why increased reasoning capabilities in Large Language Models often lead to new safety vulnerabilities, not better protection. Learn about compositional attacks, context degradation, and mitigation strategies.
Safety by Design in Generative AI: Embedding Protections into Product Architecture
Explore Safety by Design in Generative AI, a framework by Thorn, NIST, and IEEE that embeds protections against harms like CSAM directly into product architecture from development to deployment.
Security Hardening for LLM Serving: Image Scanning and Runtime Policies
Secure your LLM deployments with robust image scanning and runtime policies. Learn how to prevent prompt injection, detect steganographic payloads, and enforce least-privilege access in 2026.
Prompt Injection Attacks: How to Detect and Defend Your LLMs
Learn how to detect and defend against prompt injection attacks, the #1 risk for LLMs. Explore direct vs indirect methods, top tools like NVIDIA PromptShield, and layered defense strategies.
Anonymization vs Pseudonymization in LLM Workflows: A Practical Guide
Explore the critical differences between anonymization and pseudonymization in LLM workflows. Learn how to choose the right method for GDPR compliance, data utility, and security.
Vibe Coding Policies: What to Allow, Limit, and Prohibit
Learn how to build robust Vibe Coding policies. Discover what to allow, limit, and prohibit to secure your AI-assisted development workflow against vulnerabilities and compliance risks.
Safety Use Cases for Large Language Models in Regulated Industries: A Practical Guide
Explore how Large Language Models enhance safety in regulated industries like construction and healthcare. Learn about key use cases, security challenges, and the three pillars of regulatory-grade AI.
LLM Data Residency Compliance: A Global Guide for 2026
Navigate 2026 LLM data residency laws. Learn how GDPR, PIPL, and DPDP impact AI architecture, costs, and compliance strategies for global deployments.
Triaging Vulnerabilities in Vibe-Coded Projects: Severity, Exploitability, and Impact
Discover how to triage vulnerabilities in vibe-coded projects. Learn to assess severity, exploitability, and impact using modern frameworks and benchmarks like SusVibes.
Safe File Uploads in Vibe-Coded Web Apps: Validation and Storage Rules
Learn how to secure file uploads in AI-built apps. Discover validation rules, storage best practices, and prompt engineering tips to prevent path traversal and other critical vulnerabilities in vibe-coded web applications.
