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Update names/numbers
Put in the proper number for the 2025 list
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2_0_voting/voting_round_two/DataModelPoisoning.md

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## LLM03: Data and Model Poisoning
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## LLM04:2025 Data and Model Poisoning
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### Description
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2_0_voting/voting_round_two/ExcessiveAgency.md

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## LLM08: Excessive Agency
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## LLM06:2025 Excessive Agency
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2_0_voting/voting_round_two/ImproperOutputHandling.md

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## LLM02: Insecure Output Handling
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## LLM05:2025 Insecure Output Handling
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Insecure Output Handling refers specifically to insufficient validation, sanitization, and handling of the outputs generated by large language models before they are passed downstream to other components and systems. Since LLM-generated content can be controlled by prompt input, this behavior is similar to providing users indirect access to additional functionality.

2_0_voting/voting_round_two/Misinformation.md

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## Misinformation
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## LLM09:2025 Misinformation
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2_0_voting/voting_round_two/PromptInjection.md

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## LLM01 Prompt Injection
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## LLM01:2025 Prompt Injection
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2_0_voting/voting_round_two/SensitiveInformationDisclosure.md

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## LLM06: Sensitive Information Disclosure
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## LLM02:2025 Sensitive Information Disclosure
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2_0_voting/voting_round_two/UnboundedConsumption.md

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## Unbounded Consumption
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## LLM10:2025 Unbounded Consumption
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2_0_voting/voting_round_two/VectorAndEmbeddingWeaknesses.md

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## Vector and Embedding Weaknesses
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## LLM08:2025 Vector and Embedding Weaknesses
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