Prompt Injection

An in-depth analysis of how autonomous AI agents can exploit internal RAG systems like McKinsey's Lilli, featuring exploit paths, architectural vulnerabilities, and defense strategies.

A comprehensive guide for security professionals transitioning into AI red-teaming, covering prompt injection, RAG vulnerabilities, and control stack testing using modern LLM APIs.

A deep dive into the SPEF (Secure Prompt Engineering Framework), a 4-layer architecture that reduced prompt injection success rates by 86% in production-grade LLM applications.

An audit of over 50 Model Context Protocol (MCP) servers reveals critical security flaws including indirect prompt injection and SSRF in major vendor implementations.

Learn how attackers use indirect prompt injection and tool misuse to compromise LLM agents, and how to implement AgentShield to secure your production workflows.

Explore how malicious code comments can subvert LLM-based coding tools like Claude Code and GitHub Copilot to steal API keys and leak sensitive data, and learn how to implement robust architectural defenses.

A deep dive into atlas-detect, a high-performance Rust crate implementing 97 MITRE ATLAS rules to prevent prompt injections, jailbreaks, and model extraction in LLM applications.

As Anthropic's latest AI capabilities emerge, the industry faces a critical shift in cybersecurity strategy, moving from defensive perimeters to securing the AI-native data flow.

As AI agents move from chatbots to autonomous systems, prompt injection has become a critical security threat. Learn the technical architectural flaws and practical defense strategies for LLM security.

Building production-grade AI requires moving beyond model capability to model governability. Learn how to implement a multi-layered guardrail architecture to mitigate hallucinations, prompt injections, and data leakage.

An in-depth analysis of 50 public system prompts reveals a staggering lack of security, with an average defense score of only 3.7 out of 100. Learn how to protect your LLM applications from prompt injection.

A deep-dive red-teaming experiment testing 10 prompt injection patterns against Claude Code's configuration file. Learn which defense strategies actually stop data leaks and unauthorized access.