Security & Cryptography · Computer Science & AI
Cryptography & Security
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1,372 papers, from 4 September 2026 to 5 November 2026: 1,372 arXiv preprints.
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Newest papers, page 65
How Fragile Is Safety Alignment at Frontier Scale? A Single-Direction Attack on a 320B MoE
Directional ablation removes an aligned language model's ability to refuse by projecting a single "refusal direction" out of the weights that write the residual stream.CS-Guard: Benchmarking LLM Guardrails for Code Generation Security
Large language models (LLMs) have been ex- ploited to generate malware, but the effective- ness of guardrails for code generation secu- rity remains unclear.Subgroup Membership Inference Audits of Differentially Private Synthetic Text
Synthetic data releases are increasingly proposed in the literature as a means of sharing realistic data replicas in lieu of sensitive private datasets.What Makes Adversarial Examples Transfer Across Deepfake Detectors?
Deepfake detectors remain vulnerable to transfer-based black-box attacks, in which adversarial examples are generated on a source surrogate model and transferred to a target model, unknown to the…Beyond Training: A Feasibility Taxonomy for Inference-Time AI Governance
Compute governance today is a governance of training: the thresholds, reporting requirements, and frontier-AI regimes now in force attach to training compute and treat the trained model as the…Active Adaptation, Not Static Defense: Temporal Dynamics of Preventative Steering in Adversarial Fine-Tuning
Large language models remain fragile against malicious fine-tuning, motivating training-time defenses against harmful persona drift.Maverick: Private and Verifiable LLM Inference Made Practical via Matrix-Vector Multiplication Delegation
Open-source large language models (LLMs) are increasingly competitive with closed-source models while offering transparency and the ability to run inference without exposing user inputs to a service…Learning Intrusion Response Strategies for OT Systems
Cyberattacks against Operational Technology (OT) systems, which monitor and control industrial processes, pose an increasing threat to essential societal services.SoK: Privacy Attacks on Machine Learning via Explainable AI
Machine learning explanations reveal model behavior beyond predictions, creating attack surfaces for model confidentiality and data privacy.From Cycle Space to Cycle Manifold: Limits and Achievability of Blind False Data Injection Attacks
A false data injection attack (FDIA) can change the estimated grid state while evading a residual-based bad data detector (BDD).Architecting the Secure AI-SOC: A Neurosymbolic Framework for Pipeline Integrity and Threat Mitigation
The integration of Large Language Models (LLMs) into Security Operations Centers (SOCs) streamlines threat intelligence but introduces critical vulnerabilities, notably indirect prompt injection via…CARTS: Contextual Autoregressive Rank Transcoding Steganography for Full-Capacity Keyed Text Encoding
Autoregressive language models can be used to transform a payload text into a stegotext of identical token length by preserving per-position rank information across contexts - a methodology we…Temporal and Multimodal Deep Learning for Cyberattack Detection in LEO Satellite Systems
The growing reliance on Low-Earth Orbit (LEO) satellite communication systems has increased the need for intelligent methods capable of detecting cyberattacks across complex and dynamic space…Beyond Static Guarantees: Measuring the Static-Pass Dynamic-Fail Gap in Security-Sensitive and LLM-Generated Python Code
Advances in large language models (LLMs) fuel the quest for scalable methods to assess the security of generated and security-sensitive software.Tight Time-Space Lower Bounds for Collision Finding and Element Distinctness under Label Symmetry
How much memory is needed to retain the quantum speedup for collision finding?Detectable Only Where It Is Confounded: What Verified Duplication Counts Say About Membership Evidence in Language Models
When a language model finds a sentence unusually cheap to predict, it is tempting to conclude that the sentence was in its training data.No-Box Vulnerability Analysis: Description-only Detection of Indirect Prompt Injection Vulnerabilities in MCP Servers
Conventional vulnerability analysis relies on either system access or dynamic interaction, all of which may be unavailable to third-party analysts auditing closed-source, remotely hosted, critical…Lower Bounds for Private Graph Optimization Problems using Reconstruction Attacks
This paper studies fundamental graph optimization problems under differential privacy (DP) and shows new, reconstruction-based lower bounds.DriftNet: A Dual-Head Trajectory Transformer for Detecting and Localizing Prompt Injection in LLM Agents
When an indirect prompt injection succeeds against an LLM agent, the compromise is visible in the agent's own behavior: a benign prefix of tool calls, a poisoned observation, and a suffix of actions…ResidualAuth: What Authorization State Must Language Agents Preserve under Revocable Delegation?
Tool-using language agents can delegate and revoke permissions while acting through external services.