Public Database
Case Studies
Every approved AI failure case, classified against the AI Blindspot Framework. Filter by category, lifecycle stage, industry, geography, or date.
Multi-Agent AI Systems Combining Capabilities to Defeat Security Safeguards
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AI-Enabled Swarm Attacks Overwhelm Single-Agent Security Assumptions
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Multi-Agent AI Systems Introduce Novel Security Vulnerabilities
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Collective AI Systems Develop Emergent Goal-Directed Behaviour
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Corrupted Training Loop from Undesirable Model Outputs
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AI Agents as Attack Surface for Principal Compromise
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Cascading Security Failures in Multi-Agent AI Systems
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Model Extraction Attack Exposes Proprietary AI Architecture and Parameters
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Open-Source AI Models Repurposed for Unintended or Harmful Applications
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Jailbreaking Dismantles AI Safety Controls to Enable Unrestricted Harmful Output
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Generative AI Model Exposes Sensitive Personal Data Used in Training
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Opaque Training Data Provenance Undermines Model Explainability
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PII and Sensitive Data Leakage Through AI Training Datasets
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Prompt Injection Attack Manipulates Generative AI Output
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Prompt Priming Causes Generative Models to Leak Personal Training Data
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Adversarial Input Manipulation Causes AI Model to Produce Incorrect Outputs
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Prompt Leakage Exposes Confidential AI System Instructions
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Jailbreak Attacks Bypass AI Safety Controls in Transport Systems
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Sensitive Personal Data Exposed Through AI Model Prompts
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Generative AI Weaponised to Produce Hateful and Obscene Content
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Generative AI Deployed to Spread Targeted Disinformation
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AI Model Deployed Outside Its Intended Purpose
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Confidential Data Leaked via Model Prompt Submission
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AI Model Delivers Insufficient Accuracy for Its Intended Task
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