Shesha

AI Security Roadmap: 10 Core Areas 01 | AI Security Fundamentals: What Can Go Wrong? AI Threats → Attack Surface → Risk Assessment → Threat Modeling → Trust Boundaries → Security Controls → AI Policies → Governance → Compliance → Risk Management 02 | LLM Attack & Defense: How Do You Secure LLMs? Prompt Injection → Jailbreaking → Data Leakage → System Prompt Theft → Unsafe Outputs → Input Filtering → Output Validation → Guardrails → Red Teaming → Evaluation 03 | AI Application Security: How Do You Secure AI Apps? Authentication → Authorization → API Security → Input Validation → Output Encoding → Rate Limiting → Secrets Management → Sandboxing → Access Control → Security Testing 04 | RAG Security: How Do You Protect AI Knowledge Systems? Data Poisoning → Document Validation → Access Control → Embedding Security → Vector DB Security → Retrieval Filtering → Context Injection → Source Validation → Data Isolation → Audit Logs 05 | AI Agent Security: How Do You Secure Autonomous Agents? Tool Abuse → Excessive Permissions → Prompt Injection → Memory Poisoning → Identity Control → Tool Allowlisting → Sandboxing → Human Approval → Action Validation → Audit Trails 06 | AI Data Privacy: How Do You Protect Sensitive Data? Data Discovery → PII Detection → Classification → Masking → Encryption → Access Policies → Data Minimization → Retention Controls → Secure Deletion → Privacy Audits 07 | AI Model Security: How Do You Protect Models? Model Theft → Model Extraction → Model Poisoning → Backdoors → Weight Protection → Artifact Signing → Provenance Checks → Access Control → Integrity Validation → Model Monitoring 08 | AI Infrastructure Security: How Do You Secure AI Workloads? Cloud IAM → Network Isolation → GPU Security → Container Security → Kubernetes Hardening → Secrets Protection → Image Scanning → Runtime Security → Patch Management → Compliance 09 | AI Security Testing: How Do You Find Vulnerabilities? Threat Modeling → Attack Simulation → Prompt Injection Testing → Adversarial Testing → Red Teaming → Model Evaluation → Vulnerability Scanning → Risk Scoring → Remediation → Retesting 10 | AI Security Operations: How Do You Detect and Respond? Telemetry → Logging → Anomaly Detection → Abuse Monitoring → Threat Detection → Alerting → Incident Triage → Containment → Forensics → Continuous Improvement

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