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1,407 papers
A checklist for evaluating trace detectors is turned into a guide for evaluating trace detectors after finding that attacks or anomalies make up 16% to 86% of the test samples, no evaluation varies that share, and six report no test on data from a second benchmark or source.
Whether a language model was trained on a document matters for copyright, privacy, and benchmark contamination. Yet most membership-inference (MI) evaluations on language models collect members and non-members after the fact, so success may reflect distribution shift and failure is inconclusive. We re-ran OLMo 2 1B's o...
DeepWeave is presented, a probabilistic neuro-symbolic Network Intrusion Detection System (NIDS) that makes logic an integral part of detection, and demonstrates label-efficient, adaptable, and inspectable neuro-symbolic intrusion detection.
LLM agents increasingly triage security alerts by combining the outputs of several detection tools, implicitly treating those tools as trustworthy. Unlike prior work on conflicts between a model's knowledge and its context, we study conflicts among the tools themselves: what happens when this machine-generated evidence...
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Quantum computers are now available through cloud platforms, and recent work has proposed using them to detect network intrusions. It is not yet clear how easily such systems can be attacked. We train a hybrid variational quantum classifier (VQC) on the Friday DDoS subset of CICIDS2017 and test it against two attacks:...
A simple mechanism that uses a random number of dummy points to privatize the batch size and maintain the privacy guarantee even under truncation is addressed, and it is demonstrated empirically that this mechanism achieves better privacy--efficiency tradeoffs than the direct accounting for truncation recently given by...
Over three types of adversarial attacks, the empirical results show a strong relationship between generalization on the source task and transferability, and do not rule out generalization on the source task as a sufficient condition for successful transfer.
Cooperative routing is evaluated by coupling traffic simulation with packet-level simulation of post-quantum-authenticated vehicle-to-infrastructure communication and a tunable extension mixes shared and independent randomness to bound privacy leakage given paired outputs and shared-randomness side information.
LLM agents have been increasingly adopted for security-focused code review, but existing benchmarks mostly derive the reviewed changes from their later fixes instead of the real-world bug-introducing commits. In this paper, we present SecPRBench, the first comprehensive benchmark for evaluating agentic security review...
Autonomous cyber operations increasingly depend on agents that can chain reconnaissance, exploitation, and analysis across many tools while maintaining state over long task horizons. Large Language Models (LLMs) are promising orchestrators for this workflow, but naive agents that pipe model output directly into a shell...
This paper formalizes agentic retrieval-generation loops as finite-horizon partially observable Markov decision processes, explicitly modeling their control policies and state transitions, and develops a comprehensive taxonomy and modular architectural decomposition that categorizes systems by their planning mechanisms...
An idealized reference model---an injection-invariant, utility-preserving oracle---can nevertheless be approximated, as its output distribution in training is interestingly accessible, which motivates a theoretically principled SecPO loss.
Research Manager Mike Walker reflects on a career spanning hacker culture, cybersecurity, and AI, sharing lessons about trust, teamwork, leadership, and why solving difficult problems requires curiosity, judgment, agility—and an understanding of the rules. The post Learn the rules: The hacker mindset appeared first on Microsoft Research.
GPT-Lab
· gpt-lab.eu
Oct 30, 2026
Critical flaws, compromised release channels and agentic AI threats landed within days of each other in mid-October 2026. Why “Black October” may say more about how well we now find weaknesses than about the attacks themselves. The post Black October? The Week AI Changed the Cybersecurity Conversation appeared first on GPT-Lab.
Gemini 4 Carbon is our strongest model with state-of-the-art cybersecurity and long horizon capabilities.
Gemini 3.8 Flash and 3.8 Flash Cyber deliver next-generation intelligence for agentic workflows and cybersecurity.
Google introduces Gemini 3.5 Flash Cyber, a lightweight cybersecurity model to find and patch vulnerabilities.
Students from the MIT Cybersecurity Clinic help local governments and other vulnerable organizations defend against digital threats.
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