White Papers

The Ultimate Guide to Prompt Based Attacks

This guide maps the full threat landscape of prompt-based attacks targeting generative and agentic AI — from direct injection and jailbreaking to multi-stage kill chains exploiting retrieval pipelines and agent memory. It covers attacker motivations, attack vectors, and real-world cases to help security teams build comprehensive defenses.

The Economics of AI Defense

AI risks become manageable when technical threats are quantified in financial terms. Using the FAIR-AIR model, real-time, explainable AI guardian agents dramatically reduce incident impact and frequency, cutting AI risk by up to 94% while strengthening regulatory trust.

The Alignment Gate: Intent and Instruction Guardrails for Agentic AI

This paper proposes a measurable alignment framework for agentic AI that maps user intent to system actions using probabilistic scores and a tunable threshold rule, making decisions interpretable and improving safe execution control.

A Two-Stage Approach for Implicit Bias Detection in Generative Language Models

This paper introduces a two-stage method to detect both direct and indirect gender bias in generative language models, revealing that models like GPT-2 and OPT exhibit bias in clinical scenario responses.

The AI Explainability Scorecard

This paper provides a clear framework for measuring how well AI systems explain their decisions, helping teams balance transparency, trust, and performance across real-world use cases.