Security & Cryptography · Computer Science & AI
Cryptography & Security
The newest papers in Cryptography & Security that ReadSearch has read, newest first. Each links to its own page, with its authors, date, where it was published and the original.
1,372 papers, from 4 September 2026 to 5 November 2026: 1,372 arXiv preprints.
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Newest papers, page 27
BrowseSafe++: Benchmarking Prompt Injection Detection Across Web Contexts, Languages, and Browser Views
Browser agents need to make decisions and execute actions on behalf of users while consuming untrusted webpages, creating opportunities for malicious instructions embedded in webpages to redirect…Accuracy and Uncertainty in Machine Deception Detection (Research White Paper)
A deception detector is only as useful as the trust its alarms deserve.From Acoustic Sensing to Physical Actions: A Comprehensive Survey of Security Risks in Edge-Deployed Audio LLM-Based Agents
Audio Large Language Models (Audio LLMs) are embedded in agents for smart homes, vehicles, wearables, and embodied systems, where acoustic inputs can propagate from perception into persistent state…Security in LLM-Assisted Coding: A Systematic Literature Review
Large Language Models accelerate software development but introduce severe security vulnerabilities.Poisoned into Action: Context Attacks on Typed Decision Workflows
Typed decision interfaces restrict models to predefined actions, yet schema-valid choices can still trigger policy-violating state changes.Robust Detection of Directional Adversarial Attacks in Deep Neural Networks for Radiological Imaging
Deep learning is now central to radiology, helping detect changes on X-rays, CTs, and MRIs.To Cache or Not to Cache: Understanding and Mitigating Safety Incompatibility in Cross-Model KV Cache Reuse
Cross-model KV cache sharing reduces prefill computation by allowing a receiver model to reuse prefix KV states generated by a related sender model.SkillMarker: A KGW-Based Watermarking Method for Agent Skill Ownership Verification
Agent skills encode operational procedures and domain expertise as reusable knowledge assets, yet their distribution in plaintext exposes them to unauthorized copying and leakage.LLM-based Code Auditing by Inferring and Evaluating Developer Assumptions
When we see a null pointer check, we know that the developer believes that the pointer may not be initialized.What the Model Cannot See: Covert and Provable Text Invisibility in LLMs
Text wrapped in a trigger can be made behaviorally invisible to a language model: omitted from summaries and quotations, ignored in question answering, and left unflagged by downstream filtering.RetryBench: Separating Retry Permission from Recovery Outcomes in GPT Tool Use
False retry permission (FRP) occurs when an agent retries a timed-out tool call without support from the visible contract.Scalable Weak-to-Strong Verifier Hardening for Agent Environments
Agent environments are essential for large language model (LLM) development.Hardware-Assisted Multi-Stage Ransomware Detection with Adaptive Machine Learning
Ransomware is a fast-escalating privacy threat causing significant financial and data losses worldwide.Revocation Is Not Complete at Receipt: An Executable Outcome Contract for Distributed Agent-Tool Gateways
Distributed agent workflows cache delegated authority at tool gateways.AutoSec-RAN: Specification-Grounded LLM Fine-Tuning for Automated Security Analysis of O-RAN
This paper presents AutoSec-RAN, a specification-grounded large language model (LLM) framework for automated security triage of Open Radio Access Network (O-RAN) testing.ByteMark: A Unified Byte-Level Watermark for Detection Across Language Models
As watermarking of LLM-generated text enters deployment, users increasingly need to check text whose source is unknown.MemForm: Benchmarking Memory Formation Poisoning in LLM Agents
Long-term memory enables LLM agents to learn from past interactions but exposes memory formation to adversarial influence.SecReason: Vulnerability Detection and In-Stream Self-Repair for LLM Code Generation
Large language models (LLMs) may introduce security vulnerabilities into generated code, which can persist into production when verification focuses on functional correctness.What Counts as the Same Task? Executable Contracts for Robustness Evaluation of Tool-Using Agents
Robustness tests for tool-using agents often change the agent's environment, for example by hiding a hostile note in an invoice, and then judge the agent by what it does.Limitations on Autoregressive Token Generation via Sequential Sampling
We study autoregressive token generation through the notion of sequential samplers: A circuit that samples the next symbol only given the previous ones and possibly a small amount of state.