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cybersecurity

1,407 papers

TRACE: Trajectory-Based Safety Patch Learning for LLM Post-Training Realignment

This paper proposes TRACE, which simulates harmful SFT trajectories to produce progressively corrupted model states, and optimizes a safety patch simultaneously across these states, and improves the safety rate by up to 77 percentage points over the best baselines, while maintaining comparable utility to the undefended...

Changyue Li, Jiaming He, Youliang Yuan et al. · 0 citations
#artificial intelligence Preprint Jun 2026

AutoDojo: A Generative Benchmark for Evaluating Prompt Injection Defenses in LLM Agents

AutoDojo is introduced, a generative benchmark built on AgentDojo and AgentDyn that generates IPI adaptively for a given agent and defense, and it is demonstrated that standard static benchmarks often significantly overestimate defense efficacy.

Xinhang Ma, Taoran Li, Chao-Wei Xiao et al. · 5 citations

Large Language Models Hack Rewards, and Society

To study this phenomenon, SocioHack is introduced, a sandbox of 72 societal environments, and it is found that within these environments, reward hacking naturally emerges and leads to regulatory loophole discovery.

Wei Liu, Xinyi Mou, Hanqi Yan et al. · 3 citations
#artificial intelligence Preprint May 2026

MemPoison: Bypassing Selective Memory Mechanisms to Plant Backdoors in LLM Agents

MemPoison is proposed, a novel memory poisoning attack that bypasses selective memory mechanisms in LLM agents, where an attacker can inject triggerable backdoors into the agent's long-term memory through dialogue interactions, thereby misleading its subsequent responses.

Hongtao Wang, Sean Yang, Yu Chen et al. · 5 citations

The End of Trust: How Agentic AI Breaks Security Assumptions

The Infinite Impostor is introduced, an attack model in which an autonomous agent interposes itself between two parties who already trust each other, hijacking an existing relationship rather than building a new one from scratch, and the governance tensions that arise when platforms become the regulatory substrate of d...

Osama Zafar, Alexander Nemecek, Erman Ayday · 0 citations
#artificial intelligence Preprint Open access Sep 2026

Who Owns This Agent? Tracing AI Agents Back to Their Owners

AI agents increasingly act autonomously in the world, yet harmful behavior cannot be reliably traced to the account that deployed the agent. This creates an accountability gap across both benign and malicious settings: misconfigured or hijacked agents may cause unintended harm, while malicious operators may deploy agen...

Ruben Chocron, Doron Jonathan Ben Chayim, Eyal Lenga et al. · 0 citations

Watermarking Should Be Treated as a Monitoring Primitive

It is shown that even zero-bit watermarking supports internal attribution under per-entity multi-key deployments without explicitly encoding identity, and external identification in selected text and image configurations is demonstrated.

Toluwani Aremu, Nils Lukas, Jie Zhang · 1 citation
#artificial intelligence Preprint Open access Sep 2026

Every Bit, Everywhere, All at Once: A Binomial Multibit LLM Watermark

With LLM watermarking already being deployed commercially, practical applications increasingly require multibit watermarks that encode more complex payloads, such as user IDs or timestamps, into the generated text. In this work, we propose a fundamentally new approach for multibit watermarking: introducing binomial enc...

Thibaud Gloaguen, Robin Staab, Mark Vero et al. · 0 citations
#artificial intelligence Review May 2026

FraudBench: A Multimodal Benchmark for Detecting AI-Generated Fraudulent Refund Evidence

FraudBench is a multimodal benchmark for detecting AI-generated fraudulent refund evidence and shows that current MLLMs often recognize real-damaged evidence but fail on many fake-damaged subsets, with fake-damage detection rates far below the 50\% baseline on most generator subsets.

Xinyu Yan, Bo-Yang Chen, Jia-Ming Zhang et al. · 1 citation
#artificial intelligence Review May 2026

MOSAIC-Bench: Measuring Compositional Vulnerability Induction in Coding Agents

MOSAIC-Bench (Malicious Objectives Sequenced As Innocuous Compliance), a benchmark of 199 three-stage attack chains paired with deterministic exploit oracles on deployed software substrates that treats both exploit ground truth and downstream reviewer protocol as first-class evaluation axes, is introduced.

J. Steinberg, Oren Gal · 4 citations

From tech blogs

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Microsoft Research Blog Nov 3, 2026

Learn the rules: The hacker mindset

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 Oct 30, 2026

Black October? The Week AI Changed the Cybersecurity Conversation

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.

Google DeepMind Blog Jul 17, 2026

Introducing Gemini 3.5 Flash Cyber

Google introduces Gemini 3.5 Flash Cyber, a lightweight cybersecurity model to find and patch vulnerabilities.

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