AI Security
Module 4 Lesson 5: Data Provenance & Integrity
Know your sources. Learn how to implement data lineage and integrity checks to ensure that your training data hasn't been tampered with or replaced.
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AI Security Articles
126 postsAI Security
Module 5 Lesson 1: Model Extraction & Stealing
Your model is your IP. Learn how attackers use 'Query-Answer' pairs to clone your proprietary models for a fraction of the original training cost.
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AI Security
Module 5 Lesson 2: Membership Inference Attacks
Is your data in there? Learn how attackers can determine if a specific record (like a medical file) was used to train a model, violating user privacy.
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AI Security
Module 5 Lesson 3: Training Data Leakage
How LLMs recite their training data. Explore the 'Memorization vs. Learning' trade-off and how to prevent your model from leaking secrets.
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AI Security
Module 5 Lesson 4: Model Inversion Attacks
Reverse-engineering the training set. Learn how attackers work backwards from a model's outputs to reconstruct the sensitive images or text used in training.
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AI Security
Module 5 Lesson 5: AI Intellectual Property Risks
Is your model legally protected? Explore the legal and technical landscape of AI IP, from copyright issues to the dangers of using 'License-Violating' data.
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AI Security
Module 6 Lesson 1: What are Adversarial Examples?
Why models misidentify pandas as gibbons. Explore the phenomenon of adversarial examples and how imperceptible noise can fool neural networks.
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AI Security
Module 6 Lesson 2: Evasion Attacks
Slip past the guards. Learn about evasion attacks where AI models are bypassed in real-time to allow malicious files or actors through security filters.
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AI Security
Module 6 Lesson 3: Gradient vs. Black-Box
How to craft the perfect attack. Understand the difference between having the model's 'Code' (White-Box) and only having its 'Answers' (Black-Box).
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AI Security
Module 6 Lesson 4: Robustness Limitations
Why we can't just 'Patch' AI. Explore the fundamental reasons why deep neural networks are inherently fragile and vulnerable to adversarial noise.
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AI Security
Module 6 Lesson 5: AI Defense Strategies
How to fight back. Explore the most effective ways to defend against adversarial attacks, from adversarial training to input transformation and certified robustness.
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AI Security
Module 7 Lesson 1: What is Prompt Injection?
The #1 AI security threat. Learn the foundations of prompt injection—how attackers hijack an LLM's logic by blending instructions with data.
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AI Security
Module 7 Lesson 2: Direct vs. Indirect Injection
Know your vectors. Learn the difference between a user attacking their own session (Direct) and an attacker poisoning external data (Indirect).
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AI Security
Module 7 Lesson 3: System Prompt Leakage
Your secret instructions, revealed. Learn how attackers trick LLMs into reciting their internal guidelines, codenames, and proprietary logic.
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AI Security
Module 7 Lesson 4: Jailbreak Techniques
Breaking the rules. Explore the history and mechanics of AI jailbreaks, from 'DAN' and 'Do Anything Now' to sophisticated persona adoption and adversarial suffixes.
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AI Security
Module 7 Lesson 5: Prompt Chaining Risks
The chain is only as strong as its weakest prompt. Learn how vulnerabilities propagate through multi-step AI workflows (chains) and how to break the cycle.
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AI Security
Module 8 Lesson 1: Why You Can't Trust AI Output
The 'Implicit Trust' trap. Learn why AI-generated content must be treated as untrusted user input and the dangers of bypassing conventional security checks.
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AI Security
Module 8 Lesson 2: XSS via AI Responses
How AI becomes an XSS vector. Learn how attackers use prompt injection to trick LLM-powered websites into rendering malicious scripts for other users.
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AI Security
Module 8 Lesson 3: SSRF & RCE via Tools
When AI gets a shell. Learn how attackers use tool-calling AIs to perform Server-Side Request Forgery and Remote Code Execution inside your infrastructure.
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AI Security
Module 8 Lesson 4: Sanitizing AI Content
The digital car wash. Learn the technical techniques for cleaning AI output before it touches your users, your database, or your infrastructure.
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AI Security
Module 8 Lesson 5: Human-in-the-Loop AI
The ultimate firewall. Learn how to implement 'Human-in-the-Loop' (HITL) patterns to prevent AI from executing critical actions without explicit human approval.
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AI Security
Module 9 Lesson 1: The Agent Attack Surface
From Chatbot to Agent. Learn how giving AI 'Tools' and 'Plugins' exponentially increases your attack surface and creates new vectors for system compromise.
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AI Security
Module 9 Lesson 2: Tool Injection
How to trick a deputy. Learn the mechanics of tool injection, where attackers manipulate the arguments and payloads of AI-called functions.
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AI Security
Module 9 Lesson 3: Privilege Escalation
From Guest to Root. Learn how attackers use 'Confused Deputy' agents to gain administrative access to systems they should never be able to reach.
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AI Security
Module 9 Lesson 4: Agent-to-Agent Attacks
When robots disagree. Learn how advanced multi-agent systems are vulnerable to 'peer manipulation' and recursive exploitation loops.
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AI Security
Module 9 Lesson 5: Securing AI Plugins
The App Store of AI. Learn the risks of integrating third-party plugins and how to prevent malicious extensions from stealing user data or hijacking sessions.
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