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University of Illinois Urbana-Champaign

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SEC-bench Pro: Can Language Models Solve Long-Horizon Software Security Tasks?

QuestionCan agents reproduce specific disclosed vulnerabilities in large security-critical codebases?

Source summaryThe strongest reported model/scaffold solved 58% overall.

NUWA research note · independent review pending · Contains: question / method / interpretation / limits

CybersecurityCapability

MonitorBench: A Comprehensive Benchmark for Chain-of-Thought Monitorability in Large Language Models

QuestionWhen does a chain of thought reveal factors driving an answer, and how does that visibility change under direct concealment or monitor-aware evasion?

Source summaryDecision factors structurally embedded in planning tend to be easier to monitor than factors that can change an answer without explicit planning (§4.1).

NUWA research note · independent review pending · Contains: question / method / findings / interpretation / limits

SEC-bench: Automated Benchmarking of LLM Agents on Real-World Software Security Tasks

QuestionCan security-agent datasets be built with reproducible vulnerability and patch checks?

Source summaryThe reported best success rates were 18.0% for PoC generation and 34.0% for patching on the complete dataset.

NUWA research note · independent review pending

CybersecurityCapability

InjecAgent: Benchmarking Indirect Prompt Injections in Tool-Integrated Large Language Model Agents

QuestionHow vulnerable are tool-integrated agents to attacker instructions in external content?

Source summaryReAct GPT-4 was vulnerable in 24% of evaluated cases, with a near doubling in the enhanced condition.

NUWA research note · independent review pending

The WMDP Benchmark: Measuring and Reducing Malicious Use With Unlearning

QuestionCan a public proxy benchmark track hazardous knowledge while supporting mitigation research?

Source summaryThe paper evaluates knowledge-reduction methods alongside general-capability retention.

NUWA research note · independent review pending · Contains: question / method / limits

CBRNCapability

HarmBench: A Standardized Evaluation Framework for Automated Red Teaming and Robust Refusal

QuestionCan automated red-team methods and defenses be compared with consistent behavior-level scoring?

Source summaryContextual behaviors had higher attack success than some other functional categories.

NUWA research note · independent review pending · Contains: question / method / limits

Cross-cutting researchBehavior