AI Coding Tool Security — Defending Development Assistants
AI coding tools require specialized security controls beyond general LLM defenses due to their unique combination of cod...
ATLAS-Informed Defense Planning: From Attack Mapping to Mitigation Strategy
Learn how to use MITRE ATLAS proactively to anticipate attack paths, prioritize mitigations, and close security gaps bef...
Automated Red Teaming as a Defensive Flywheel: Building Sustainable Agent Security
Learn why one-time hardening is insufficient for agent security and how automated red teaming creates a sustainable defe...
Automated Red Teaming as a Defensive Practice
Learn how automated red teaming creates a continuous defensive flywheel that systematically discovers vulnerabilities an...
Confabulation as Defense: When Hallucination Protects Secrets
Learn how defensive confabulation can satisfy extraction pressure with plausible fake content while protecting real secr...
Confirmation Gates and Constrained Actions: Limiting Agent Risk Through System Controls
Learn why agent safety depends less on blocking every prompt injection and more on constraining what actions an agent ca...
Data and Model Poisoning — Protecting AI Integrity from Training to Deployment
Data and model poisoning attacks manipulate training data or model weights to introduce vulnerabilities, backdoors, or b...
Defense Strategy Core Principles
Learn the core strategic principles behind robust AI defense, from defense in depth and intent recognition to secure fai...
FIDS: Foreign Instruction Detection Through Separation — Training-Time Defenses for Document Pipelines
Learn why training-time defenses using LoRA adaptation can outperform inference-time mitigations, and how Foreign Instru...
Improper Output Handling: Validating LLM Outputs Before They Reach Your Systems
Learn why treating LLM outputs as untrusted input and applying proper validation, encoding, and sanitization prevents XS...
Intent Security and Behavioral Monitoring for AI Agents
Learn how intent security and behavioral monitoring provide a proactive defense layer for AI agents by observing what th...
Measuring AI Security Risk: Metrics and Methods
Learn how to quantify AI security risks through the NIST AI RMF Measure function — using concrete metrics, tracking indi...
Multi-Language Safety Evaluation: Defending Against Cross-Lingual Jailbreaks
Learn why language-specific safety filters create exploitable blind spots and how to design robust multi-language evalua...
Defending Against Multi-Vector Jailbreak Attacks
Learn how robust defenders withstand compound jailbreak attempts that combine formatting, roleplay, authority claims, an...
When PDF Prompt Injection Hits Production — A Remediation Playbook
Learn the structured response process engineering teams need when PDF prompt injection is reported in production, coveri...
Prompt Drift as a Defensive Signal: Monitoring System Prompt Changes
Learn how to use system prompt version changes as a defensive observability signal to detect unauthorized modifications,...
Securing RAG Pipelines: Defense Against Knowledge Base Attacks
Learn how to defend Retrieval-Augmented Generation (RAG) systems against knowledge base poisoning, retrieval manipulatio...
Resource Exhaustion Detection: Preventing Computational DoS in LLM Applications
Learn how encoder models can predict LLM output length and computational cost before generation, enabling proactive defe...
SAIF Automated Defenses — Scaling Security to Match Threat Velocity
Learn why manual security testing cannot keep pace with AI threats and how automated defenses—adversarial testing, conti...
Harmonizing Platform Controls — Consistent Security Across AI Environments
Learn how to maintain consistent security controls across diverse AI platforms and deployment environments to prevent at...
Sensitive Information Disclosure: Preventing LLMs from Leaking Secrets
Learn why LLMs can inadvertently disclose sensitive information and how layered defenses from training data through outp...
Tool Calling and Agent Security Best Practices
Learn defensive patterns for securing AI agent tool-use capabilities against prompt injection attacks and unauthorized a...
Securing RAG Systems: Defending Against Vector and Embedding Weaknesses
Learn to defend Retrieval-Augmented Generation (RAG) systems against vector and embedding weaknesses that can lead to da...