AIBlindspot

Public Database

Case Studies

Every approved AI failure case, classified against the AI Blindspot Framework. New to AIBlindspot? Start with the overview or the methodology.

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Showing 1120 of 1296 cases

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SECSEC-0014/5NewOtherGlobal

Prompt Injection Attacks Enable Remote Compromise of LLM-Integrated Systems

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Source: MIT AI Risk Repository — The Ethics of Advanced AI Assistants (Gabriel2024)Ingested
SECSEC-0044/5NewGovernmentGlobal

Advanced AI Assistants Enable Harmful Content Generation at Scale

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Source: MIT AI Risk Repository — The Ethics of Advanced AI Assistants (Gabriel2024)Ingested
SECSEC-0014/5NewOtherGlobal

AI Assistants Enable Offensive Cyber Operations as Well as Defence

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Source: MIT AI Risk Repository — The Ethics of Advanced AI Assistants (Gabriel2024)Ingested
GOVGOV-0015/5NewOtherGlobal

Deceptive Alignment: AI Systems Concealing True Objectives During Training

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Source: MIT AI Risk Repository — The Ethics of Advanced AI Assistants (Gabriel2024)Ingested
SECSEC-0014/5NewGovernmentGlobal

AI Tools Lower the Barrier to Software Vulnerability Discovery

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Source: MIT AI Risk Repository — The Ethics of Advanced AI Assistants (Gabriel2024)Ingested
HUMHUM-0034/5NewOtherGlobal

LLM Overconfidence Produces Confident but Factually Wrong Outputs

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Source: MIT AI Risk Repository — Trustworthy LLMs: A Survey and Guideline for Evaluating Large Language Models’ Alignment (Liu2024)Ingested
SECSEC-0014/5NewDefenceGlobal

AI Benchmark Exposes WMD Guidance Risk in Language Models

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Source: MIT AI Risk Repository — Introducing v0.5 of the AI Safety Benchmark from MLCommons (Vidgen2024)Ingested
DATDAT-0014/5NewOtherGlobal

AI Safety Benchmark Exposes Self-Harm Enablement Risk in Generative Models

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Source: MIT AI Risk Repository — Introducing v0.5 of the AI Safety Benchmark from MLCommons (Vidgen2024)Ingested
HUMHUM-0034/5NewLegalGlobal

AI Systems Providing Unauthorised Legal and Specialised Professional Advice

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Source: MIT AI Risk Repository — Introducing v0.5 of the AI Safety Benchmark from MLCommons (Vidgen2024)Ingested
DATDAT-0025/5NewTechnologyGlobal

LLM Training Data Exposed Through Targeted Privacy Attacks

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Source: MIT AI Risk Repository — Trustworthy LLMs: A Survey and Guideline for Evaluating Large Language Models’ Alignment (Liu2024)Ingested
OPSOPS-0014/5NewOtherGlobal

AI Systems Generating Defamatory Content About Individuals

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Source: MIT AI Risk Repository — Introducing v0.5 of the AI Safety Benchmark from MLCommons (Vidgen2024)Ingested
DATDAT-0014/5NewOtherGlobal

AI Benchmark Exposes Hate Speech Generation Risk in Language Models

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Source: MIT AI Risk Repository — Introducing v0.5 of the AI Safety Benchmark from MLCommons (Vidgen2024)Ingested
SECSEC-0044/5NewOtherGlobal

AI Systems Spreading Factual Misinformation About Electoral Processes

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Source: MIT AI Risk Repository — Introducing v0.5 of the AI Safety Benchmark from MLCommons (Vidgen2024)Ingested
DATDAT-0034/5NewOtherGlobal

LLM Political Bias Risks Manipulation of Socio-Political Processes

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Source: MIT AI Risk Repository — Trustworthy LLMs: A Survey and Guideline for Evaluating Large Language Models’ Alignment (Liu2024)Ingested
GOVGOV-0015/5NewOtherUSA

AI Systems Concealing True Objectives Until Oversight Is Removed

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Source: MIT AI Risk Repository — An Overview of Catastrophic AI Risks (Hendrycks2023)Ingested
DATDAT-0014/5NewOtherGlobal

AI Safety Benchmark Flags Models Enabling Violent Crime Responses

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Source: MIT AI Risk Repository — Introducing v0.5 of the AI Safety Benchmark from MLCommons (Vidgen2024)Ingested
DATDAT-0014/5NewOtherGlobal

AI Safety Benchmark Exposes Models Enabling Non-Violent Criminal Activity

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Source: MIT AI Risk Repository — Introducing v0.5 of the AI Safety Benchmark from MLCommons (Vidgen2024)Ingested
ENVENV-0043/5NewRetailGlobal

AI Competitive Pressure Drives Short-Term Deployment Over Long-Term Safety

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Source: MIT AI Risk Repository — An Overview of Catastrophic AI Risks (Hendrycks2023)Ingested
DATDAT-0014/5NewOtherGlobal

AI Benchmark Flags Models Generating Explicit Sexual Content

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Source: MIT AI Risk Repository — Introducing v0.5 of the AI Safety Benchmark from MLCommons (Vidgen2024)Ingested
ENVENV-0044/5NewDefenceGlobal

Autonomous Lethal Weapons and the Military AI Arms Race

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Source: MIT AI Risk Repository — An Overview of Catastrophic AI Risks (Hendrycks2023)Ingested
SECSEC-0014/5NewOtherGlobal

Imperceptible Input Manipulation Fools High-Accuracy Deep Learning Models

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Source: MIT AI Risk Repository — Towards risk-aware artificial intelligence and machine learning systems: An overview (Zhang2022)Ingested
GOVGOV-0064/5NewFinanceGlobal

Black-Box LLM Reasoning Failures in High-Stakes Financial Decisions

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Source: MIT AI Risk Repository — Trustworthy LLMs: A Survey and Guideline for Evaluating Large Language Models’ Alignment (Liu2024)Ingested
SECSEC-0015/5NewDefenceGlobal

Advanced AI Enabling Catastrophic Malicious Use in Defence and Security Contexts

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Source: MIT AI Risk Repository — An Overview of Catastrophic AI Risks (Hendrycks2023)Ingested
OPSOPS-0014/5NewOtherGlobal

Model Misspecification Causes Biased Predictions and Flawed Operational Decisions

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Source: MIT AI Risk Repository — Towards risk-aware artificial intelligence and machine learning systems: An overview (Zhang2022)Ingested

Beyond accidental failureNational Security

We also track 20 hostile uses of AI.

National Security dashboard →

The public database covers AI that fails by accident. AIBlindspot National Security — exclusive to the Defence tier — tracks AI used as a weapon, mapped by capability:

State-Sponsored AI Operations
6
AI-Enabled Disinformation
5
Adversarial Attacks on AI
0
Autonomous Weapon Incidents
1
AI-Assisted Cyber Attacks
5
Dual-Use AI Misuse
3