AI systems should fail safely before they ever reach production. Learn how to test AI security in pre-production to uncover real risk early.
Red Teaming
Cyber AI Tip: Red Teaming AI Systems — What Actually Works
Red teaming AI isn’t about tricking models, it’s about breaking systems. Learn how to test AI deployments the way attackers actually will.
AI Supply Chain Resilience — Operational Playbook for Defense
AI supply-chain attacks exploit compromised models, datasets, and plugins. This playbook details how to inventory components, validate provenance, detect backdoors, and respond effectively.
Adversarial Evaluation & AI Red Teaming Pipelines — Operational Playbook for Defense
Adversarial evaluation turns AI risks into automated tests that run in CI/CD and block unsafe releases. This playbook shows how to design threat-led evals, wire them into pipelines, and align with NIST, OWASP, MITRE ATLAS, and SAIF.
Model Extraction & API Abuse — Operational Playbook for Defense
Attackers can clone ML models or extract memorized data through API queries. This playbook details mechanisms, real-world research, and defenses such as output minimization, DP, and active monitoring.
Prompt Injection and LLM Jailbreaking — Operational Playbook for Defense
Prompt injection and jailbreaks exploit LLMs by embedding malicious instructions in user inputs or retrieved content. This playbook outlines real-world cases and practical defenses including sanitization, least-privilege design, and red-team testing.
LLM Red Teaming Tactics: Prompt Injection Reconnaissance & Evasion Techniques
Date: July 23, 2025Author: AI Defense LeagueCategory: Red Teaming | Penetration Testing | LLM Security Overview This post is the first in a new blog series focused on penetration testing and red teaming techniques for Large Language Models (LLMs). Today’s… Read More ›