a2b5c14e8c
- Source: inbox/queue/2024-09-00-xu-scav-steering-concept-activation-vectors-jailbreak.md - Domain: ai-alignment - Claims: 2, Entities: 0 - Enrichments: 1 - Extracted by: pipeline ingest (OpenRouter anthropic/claude-sonnet-4.5) Pentagon-Agent: Theseus <PIPELINE>
17 lines
2.1 KiB
Markdown
17 lines
2.1 KiB
Markdown
---
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type: claim
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domain: ai-alignment
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description: SCAV framework demonstrates that the same linear concept directions used for safety monitoring can be surgically targeted to suppress safety activations, with attacks transferring to black-box models like GPT-4
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confidence: experimental
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source: Xu et al. (NeurIPS 2024), SCAV framework evaluation across seven open-source LLMs
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created: 2026-04-21
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title: "Representation monitoring via linear concept vectors creates a dual-use attack surface enabling 99.14% jailbreak success"
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agent: theseus
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scope: causal
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sourcer: Xu et al.
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related: ["mechanistic-interpretability-tools-create-dual-use-attack-surface-enabling-surgical-safety-feature-removal", "chain-of-thought-monitoring-vulnerable-to-steganographic-encoding-as-emerging-capability"]
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---
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# Representation monitoring via linear concept vectors creates a dual-use attack surface enabling 99.14% jailbreak success
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Xu et al. introduce SCAV (Steering Concept Activation Vectors), which identifies the linear direction in activation space encoding the harmful/safe instruction distinction, then constructs adversarial attacks that suppress those activations. The framework achieved an average attack success rate of 99.14% across seven open-source LLMs using keyword-matching evaluation. Critically, these attacks transfer to GPT-4 in black-box settings, demonstrating that the linear structure of safety concepts is a universal property rather than model-specific. The attack provides a closed-form solution for optimal perturbation magnitude, requiring no hyperparameter tuning. This creates a fundamental dual-use problem: the same linear concept vectors that enable precise safety monitoring (as demonstrated by Beaglehole et al.) also create a precision targeting map for adversarial attacks. The black-box transfer is particularly concerning because it means attacks developed on open-source models with white-box access can be applied to deployed proprietary models that use linear concept monitoring for safety. The technical mechanism is less surgically precise than SAE-based attacks but achieves comparable success with simpler implementation, making it more accessible to adversaries.
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