chore: import upstream snapshot with attribution
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---
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sidebar_label: HarmBench
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description: Red team LLM safety using HarmBench's 400 harmful behavior tests, with filters for specific semantic and functional categories
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---
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# HarmBench Plugin
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The HarmBench plugin uses the [HarmBench dataset](https://github.com/centerforaisafety/HarmBench/tree/main/data/behavior_datasets) published by the [Center for AI Safety](https://www.safe.ai/) to test LLM responses to harmful prompts. The dataset evaluates models across 400 key harmful behaviors including:
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- Chemical and biological threats (e.g., dangerous substances, weapons)
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- Illegal activities (e.g., theft, fraud, trafficking)
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- Misinformation and conspiracy theories
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- Harassment and hate speech
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- General harmful requests
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- Cybercrime (e.g., malware, system exploitation)
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- Copyright violations
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Unlike many of our other plugins, the HarmBench plugin uses a statically generated dataset vs dynamically generating cases such as those for [Harmful behavior detection](harmful.md) (which was partially based on HarmBench's classifications for harmful behavior), [excessive agency](excessive-agency.md), [hallucination](hallucination.md) and others. It is still however a great tool but not something that can be used in lieu of a constantly evolving, dynamically generated set of test cases.
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## Configuration
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To include the HarmBench plugin in your LLM red teaming setup:
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```yaml
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redteam:
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plugins:
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- harmbench
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```
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You can control the number of test cases using the `numTests` parameter:
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```yaml
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redteam:
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plugins:
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- id: harmbench
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numTests: 25 # The default is 5, but you can define the limit here.
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```
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### Filtering by Category
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You can run a subset of HarmBench by filtering the dataset's semantic categories:
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```yaml
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redteam:
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plugins:
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- id: harmbench
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numTests: 20
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config:
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categories:
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- cybercrime_intrusion
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- misinformation_disinformation
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```
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The available semantic categories are:
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- `chemical_biological`
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- `copyright`
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- `cybercrime_intrusion`
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- `harassment_bullying`
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- `harmful`
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- `illegal`
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- `misinformation_disinformation`
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Common aliases such as `cybercrime`, `misinformation`, and `chemical and biological` are also accepted and normalized to the canonical values above.
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### Filtering by Functional Category
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HarmBench also distinguishes between `standard`, `contextual`, and `copyright` behaviors. You can filter by those functional slices as well:
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```yaml
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redteam:
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plugins:
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- id: harmbench
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numTests: 20
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config:
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categories:
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- misinformation
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functionalCategories:
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- contextual
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```
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When you set both semantic and functional filters, Promptfoo generates tests from the matching intersection.
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The available functional categories are:
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- `standard`
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- `contextual`
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- `copyright`
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## References
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- [HarmBench Paper](https://arxiv.org/abs/2402.04249)
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- [HarmBench Dataset](https://github.com/centerforaisafety/HarmBench/tree/main/data/behavior_datasets)
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- [Center for AI Safety](https://www.safe.ai/)
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## Related Concepts
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- [Types of LLM vulnerabilities](/docs/red-team/llm-vulnerability-types/) - Full vulnerability and plugin directory with category mapping
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- [Evaluating LLM safety with HarmBench](/docs/guides/evaling-with-harmbench)
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- [Harmful Content Plugin](harmful.md)
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- [BeaverTails Plugin](beavertails.md)
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- [CyberSecEval Plugin](cyberseceval.md)
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- [Pliny Plugin](pliny.md)
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