Red Team Your AI

Security audits for AI systems: LLM red-teaming, prompt injection, model extraction, supply chain attacks, adversarial robustness testing. Applied to every sector that deploys AI at scale.

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Why AI Security

Models break when they meet reality. An attacker can:

  • Trick them with adversarial inputs
  • Steal their weights via API queries
  • Inject prompts to hijack behavior
  • Poison training data before deployment
  • Exploit supply chain weaknesses

The Audit Workflow

We document five attack surfaces. Test them in order; fix them before production.

🔴 LLM Red-Teaming

Prompt injection, jailbreaks, token smuggling. The attack surface is the input.

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🔴 Model Extraction

Reverse-engineer your model through API queries. Copy weights, steal trade secrets.

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🔴 Data Poisoning

Corrupt training data to plant backdoors and trojans. The model learns to misbehave.

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🔴 Supply Chain

Dependencies, open-source code, pre-trained models. Every link is a weak point.

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🔴 Guardrails & Monitoring

Once deployed, your system needs runtime detection and automated response.

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🔴 Multimodal & Vision

Physical adversarial patches, OCR visual injection, and sensor spoofing attacks.

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Guidance by Topic

Dense technical guides on threat models, testing frameworks (OWASP LLM Top 10, MITRE ATLAS), regulatory context (EU AI Act, ISO 42001), and real-world case studies.

Prompt Injection Attacks Direct and indirect prompt injection, semantic smuggling, output smuggling. /prompt-injection-attacks/ AI System Audit Full-stack audit workflow, from governance to testing and risk reporting. /ai-audit/ Adversarial Attacks & RL Adversarial examples, evasion attacks, model robustness, threat models. /adversarial-attacks-reinforcement-learning/ OWASP LLM Top 10 The canonical taxonomy of LLM application risks and mitigations. /owasp-llm-top-10/ MITRE ATLAS Framework Tactics, techniques, and procedures for AI system attack and defense. /mitre-atlas-framework/ AI Governance & Compliance EU AI Act, ISO 42001, risk management, audit trails, governance frameworks. /ai-governance-eu-ai-act-iso-42001/ RAG & Vector DB Security Securing retrieval-augmented generation, knowledge base injection, data leakage. /rag-vector-db-security/ Cyber-Physical & Robotics Security Autonomous vehicles, drones, industrial robots, embodied AI threat modeling. /cyber-physical-ai-robotics-security/ AI Agent Security Audit Tool-use, action loops, long-horizon planning, agentic threats and defenses. /ai-agent-security-audit/ Strategic Reasoning & Multi-Agent Game theory, Strategy Logic (SL), Stackelberg equilibria, and swarm security. /strategic-reasoning-multi-agent-security/ AI Penetration Testing Structured red team campaigns, CVSS-AI risk grading, and WASA archive. /ai-penetration-testing-audit/ Worst-Case AI Robustness Algorithmic complexity, boundary geometry, and AofA 2007 archive. /analysis-of-algorithms-worst-case-robustness/

AI Security Audit by Sector

The same methods, applied where the stakes and the regulators differ.

Automotive Sensors, OTA updates, in-car assistants. /automotive-ai-security-audit/ Healthcare Clinical models, patient data, medical devices. /healthcare-ai-security-audit/ Banking Credit scoring, fraud detection, chatbots. /banking-ai-security-audit/ Consulting Client confidentiality, RAG, deliverable quality. /consulting-ai-security-audit/