Language agents are moving from single-user assistants to shared collaborators in workspaces, forums, and group chats. A shared agent observes interleaved messages from multiple users, maintains persistent context, and executes tool actions, creating a boundary problem absent from standard single-user agents: the agent...
Atharv Singh Patlan, Peiyao Sheng, S. Ashwin Hebbar et al.· 0 citations
The performance figures of modern drift-adaptive malware classifiers appear promising, but does this translate to genuine operational reliability? The standard evaluation paradigm primarily focuses on baseline performance metrics, neglecting confidence-error alignment and operational stability. While prior works establ...
Alexander Herzog, Aliai Eusebi, Lorenzo Cavallaro· 0 citations
Multi-relational graph detectors learn from clean data how much to trust each relation, but an adversary pays a different price to manipulate each relation and each action; taking such costs as given, we ask when using a relation is worse than ignoring it. Our first main result proves that degree gating strictly beats...
Audit-based certification bounds the violation rate of an LLM agent by auditing a random fraction $\varepsilon$ of actions and reweighting the audited labels; its validity is meant to rest only on the defender's audit coin. We show that it also rests on a confidentiality property: the coin must not interfere with the a...
Wei Zhu, Meiyun Zuo, Huiping Sun· 0 citations
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Sequential trading agents produce decisions, orders, execution receipts, account states, and reports that need not agree, even when the final portfolio value is correctly computed. We present FIDES-Live, an operational extension of FIDES from generated strategy concordance to the audit of sequential agent traces. The p...
Arther Tian, Alex Ding, Simon Wu et al.· 0 citations
Large Language Models (LLMs) rely on proprietary system prompts to enforce task directives, safety policies, and access controls. These prompts are vulnerable to query-based leakage attacks, where black-box adversaries extract confidential instructions through adaptive, multi-turn interactions. Existing defenses often...
Tushar Nayan, Pratik Poudel, Qian Lou et al.· 0 citations
This work examines whether a targeted LLM training approach can transfer distinct RE skills to open models via inverse basic-block execution: given an x86-64 basic block and a desired output register state, the model predicts the input register values that produce it.
Ritika Poddar, Aidan Fennelly, Deirdre Murphy et al.· 0 citations
Results show that successful task completion can coexist with unauthorized post-hoc disclosure and motivate host-controlled authorization for secondary tool calls and motivate host-controlled authorization for secondary tool calls.
Yue-Peng Hu, Chong-Yu Fan, Sirat Samyoun et al.· Proceedings of the 1st Works...· 8 citations· ⚡2
This work exploits transactions already recorded by both endpoint banks to approximate remote account states locally, enabling multi-layer Graph Neural Network computation without additional account-specific exchange and support a practical rule for banks: use what they already record, and formally protect the little t...
L. Losavio, Dario Fenoglio, M. Gjoreski et al.· 0 citations
Agentic Entity Resolution (ER) systems iteratively plan actions, retrieve evidence, revise hypotheses, and propose graph mutations. An erroneous identity hypothesis may condition later retrieval and produce apparent confirmation. This paper proposes a Digital Identity Optimization (DIO) and Ontology of Digital Identity...
Perimeter triage faces a latency/semantics trade-off: signature engines are fast and format-safe but blind to unseen attacks, while generative models are semantic but slow and unparseable. We present VX-One, a small multi-head network (100K--10M parameters) with calibrated typed outputs: a binary gate, a closed-set cho...
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.
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.
