superred-claim-asb

Agent Security Bench (ASB) security claim for the superred red-teaming framework. It exposes one Task per (agent, benign task, attacker tool), with ASB's attack-success / utility / refusal predicates ported verbatim, plus an adversarial success judge and hierarchical factories by scenario, aggressiveness, and attack type. Pairs with the superred-target-asb target.

Credits / upstream

This module ports Agent Security Bench (ASB) into the superred framework.

  • ASB — https://github.com/agiresearch/ASB (commit 1f561dcc), MIT, Copyright (c) 2024 AGI Research. Paper: Zhang, Huang, Mei, Yao, Wang, Zhan, Wang, Zhang, "Agent Security Bench (ASB)", ICLR 2025.

The ASB benchmark data (agent tasks, attacker tools, normal tools) is vendored verbatim under src/asb_claim/data/ and the upstream MIT license is preserved in data/ASB_LICENSE. ASB's attack-success / utility / refusal predicates and refusal-judge prompt are ported from main_attacker.py; see ASSUMPTIONS.md for deviations. Our SecurityClaim wiring, the adversarial success judge, and the tool-invocation success predicate are original (MIT, see LICENSE).

When reporting results produced with this module, please cite ASB (ICLR 2025).

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Credits

Author: Simon Sure

GitHub Statistics

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License expression

MIT
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Requires

Python <3.14, >=3.11

Provides Extra

dev

Tags

adversarial agent-security-bench ai-safety asb benchmark llm red-teaming security

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