OmniSafeBench-MM: A Unified Benchmark and Toolbox for Multimodal Jailbreak Attack-Defense Evaluation

Recent advances in multi-modal large language models MLLMs have enabled unified perception-reasoning capabilities, yet these systems remain highly vulnerable to jailbreak attacks that bypass safety alignment and induce harmful behaviors. Existing benchmarks such as JailBreakV-28K, MM-SafetyBench,...

Learning the Wrong Lessons: Syntactic-Domain Spurious Correlations in Language Models

Whitepaper from researchers at MIT, Northeastern University, and Meta. For an LLM to correctly respond to an instruction it must understand both the semantics and the domain i.e., subject area of a given task-instruction pair. However, syntax can also convey implicit information Recent work shows...

Sorting Through Haystacks to Find CTI Needles

Clouded vision CTI systems are confronted with some major issues ranging from the size of the collection networks to their diversity, which ultimately influence the degree of confidence they can put on their signals. Are they fresh enough and sufficiently reliable to avoid any false positives or...

4 breakthrough ideas for compliance and data security

Compliance management will never be easy, but there are ways to make it simpler and more transparent. Every year, organizations confront a growing volume and diversity of data and ever-evolving industry and government regulations. But the answer to more data, more devices, and more regulations...

CISO Spotlight: How diversity of data (and people) defeats today’s cyber threats

This year, we have seen five significant security paradigm shifts in our industry. This includes the acknowledgment that the greater the diversity of our data sets, the better the AI and machine learning outcomes. This diversity gives us an advantage over our cyber adversaries and improves our...