REPORTS
Fresh threat intelligence we ingest from public vendor and research feeds — each report linked to its original source. Search, filter by source, and open the reference.
Reports
Newest first. Search, filter by source, open the original.
825 reports · page 4 of 21
arxiv_cs_cr · tlp:amber · 7/15/2026, 4:00:00 AM
PVDetector: Detecting Prompt Injection Attacks on Purpose-Specific LLM Agents through Policy-Violation Concept Analysis arXiv:2607.12624v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed as purpose-specific agents to handle domain-specific tasks such as customer service and code generation. These agents are expected to comply with not only generic safety guardrails but also purpose-specific restrictions tailored to their designated roles. …
Read original ↗https://arxiv.org/abs/2607.12624arxiv_cs_cr · tlp:amber · 7/15/2026, 4:00:00 AM
Watermark Forensics for Generative Models: An Information-Theoretic Perspective arXiv:2607.13003v1 Announce Type: new Abstract: A watermark in a generative model's output is usually asked only whether a text is machine-made. The same mark can do more: attribute it to the user who produced it, extract a hidden payload, or localize the part that survives editing. These form a forensic ladder, and we ask what each rung costs in the sample length $n$. One object organizes the an…
arxiv_cs_cr · tlp:amber · 7/15/2026, 4:00:00 AM
Cross-Cutting Security Analysis of LLM-Generated Code via Metamorphic Testing and Association Rule Mining arXiv:2607.12089v1 Announce Type: new Abstract: Large language models (LLMs) frequently generate code with security vulnerabilities, yet these weaknesses are rarely isolated: they often span multiple concern areas simultaneously, reflecting the cross-cutting nature of security in software. We present a framework that combines security-oriented Metamorphic Relations (MRs)…
Read original ↗https://arxiv.org/abs/2607.12089arxiv_cs_cr · tlp:amber · 7/15/2026, 4:00:00 AM
Antiproof: Synthesizing Vulnerability Detectors and Proofs of Exploitability arXiv:2607.12316v1 Announce Type: new Abstract: Discovering vulnerabilities before attackers exploit them requires high recall and reliable automatic validation, but existing approaches struggle to achieve both without prohibitive cost. We present Antiproof, an end-to-end vulnerability discovery system that combines neuro-symbolic detector synthesis for high-recall discovery with proof-of-exploitabi…
Read original ↗https://arxiv.org/abs/2607.12316arxiv_cs_cr · tlp:amber · 7/15/2026, 4:00:00 AM
Auditable and Transparent Fully Authenticated Disk Encryption via USB Storage Interposition arXiv:2607.12716v1 Announce Type: new Abstract: Full Disk Encryption (FDE) has become increasingly important in the last decades due to the evident confidentiality concerns. In most systems, encryption is provided by an operating system driver, through which the user can transparently access the encrypted disk after supplying the required keys (or the credentials from which those keys…
Read original ↗https://arxiv.org/abs/2607.12716arxiv_cs_cr · tlp:amber · 7/13/2026, 4:00:00 AM
Malaika: Understanding Malware through Tri-Grounded Agentic Reasoning arXiv:2607.09179v1 Announce Type: new Abstract: Recent LLM-based systems have shown promising capabilities for security-focused code analysis. Malware understanding, however, poses a distinct challenge: analysts must reconstruct high-level malicious behaviors under partial observability from sparse, dispersed evidence intertwined with benign functionality. While static analysis can expose security-relevant…
Read original ↗https://arxiv.org/abs/2607.09179arxiv_cs_cr · tlp:amber · 7/13/2026, 4:00:00 AM
Secret Scanner Agent: Extracting Secrets and Access Context from Unstructured Documents arXiv:2607.09011v1 Announce Type: new Abstract: Exposed documents such as emails, chat threads, tickets, and incident notes routinely leak credentials, but during incident response a leaked secret is only half the story. Responders also need to identify the ``door'' the secret opens: the account, tenant, endpoint, database, cloud resource, or other system that the credential could allow a…
Read original ↗https://arxiv.org/abs/2607.09011arxiv_cs_cr · tlp:amber · 7/13/2026, 4:00:00 AM
SLBench: Evaluating How LLM Agents Follow Logical Relations in Skills arXiv:2607.09016v1 Announce Type: new Abstract: Agent skills extend LLM agents with reusable procedures, tools, and domain-specific workflows, but their safety depends on resolving dependencies among interacting instructions. We introduce SkillLogic, a framework for analyzing logical relations in skill files and constructing executable tests from them. Our taxonomy covers eight relation types, including pr…
Read original ↗https://arxiv.org/abs/2607.09016arxiv_cs_cr · tlp:amber · 7/13/2026, 4:00:00 AM
SherAgent: Scaling Attack Investigation in the Wild via LLM-Empowered Iterative Query-Filter Backtracking arXiv:2607.09176v1 Announce Type: new Abstract: Provenance-based attack investigation enables viable automation by standardizing data and query logic; however, it is critically hindered in practice by dependency explosions and fragmented causal chains in the wild. Towards designing a robust and automated investigation tool, we collaborated with the SOC of a major Interne…
Read original ↗https://arxiv.org/abs/2607.09176arxiv_cs_cr · tlp:amber · 7/13/2026, 4:00:00 AM
Blockchain-Linked Auditable Decision Management for Telecom/IoT Fraud-Control Requests arXiv:2607.09259v1 Announce Type: new Abstract: Telecom fraud-control studies often stop at detector-level classification, but deployment use requires request-level policy resolution, lifecycle traceability, and auditability. This paper reframes fraud control as blockchain-linked auditable decision management for synthetic telecom/IoT fraud-control requests, and its main result is that the…
Read original ↗https://arxiv.org/abs/2607.09259arxiv_cs_cr · tlp:amber · 7/13/2026, 4:00:00 AM
Leveraging Interpretable Tsetlin Machine for PDF Malware Detection arXiv:2607.09290v1 Announce Type: new Abstract: In the digital era, Portable Document Format (PDF) is one of the most widely used file formats for storing and exchanging digital documents due to its platform independence and rich functionality. However, these same capabilities have also made PDF files an attractive attack vector for cyberattackers, who embed malicious code within seemingly legitimate document…
Read original ↗https://arxiv.org/abs/2607.09290arxiv_cs_cr · tlp:amber · 7/13/2026, 4:00:00 AM
SeedSmith: LLM-Driven Seed Synthesis for Directed Fuzzing arXiv:2607.08949v1 Announce Type: new Abstract: Directed fuzzing steers fuzzers toward user-defined sink functions to identify vulnerabilities, but it frequently fails to trigger crashes even after long campaigns. We identify two challenges that prevent directed fuzzers from exposing crashes: incomplete static analysis of indirect calls, which leaves reachable paths invisible to distance-based guidance, and lack of se…
Read original ↗https://arxiv.org/abs/2607.08949arxiv_cs_cr · tlp:amber · 7/13/2026, 4:00:00 AM
RaMark: Radioactive Watermarking for Generated Tabular Data arXiv:2607.09000v1 Announce Type: new Abstract: Recent advances in generative modeling have made generated tabular data a practical solution for privacy-sensitive data sharing, where watermarking enables ownership verification. However, existing watermarking methods fundamentally fail under retraining attacks, in which an adversary retrains a generative model on a watermarked dataset and regenerates high-utility dat…
Read original ↗https://arxiv.org/abs/2607.09000arxiv_cs_cr · tlp:amber · 7/13/2026, 4:00:00 AM
Proof-of-Continuity: A Temporal Model for Authority Propagation in Distributed Systems and AI Agents arXiv:2607.08906v1 Announce Type: new Abstract: Proof-of-Possession authorization models derive authority from the possession of artifacts such as tokens, credentials, or capabilities. This paper argues that possession is insufficient for discrete execution chains, whether they span multiple services or occur as separated steps within the same machine, because it does not gua…
Read original ↗https://arxiv.org/abs/2607.08906arxiv_cs_cr · tlp:amber · 7/13/2026, 4:00:00 AM
A Seed for Privacy -- semi-automatic privacy-revealing data reminder in databases and data streams arXiv:2607.08801v1 Announce Type: new Abstract: Sharing databases and data streams imposes the danger of revealing private information in the form of complex events which can comprise individual data elements and their combinations. Identifying these privacy-revealing complex events is crucial for preserving privacy while maintaining data utility. However, data producers often …
Read original ↗https://arxiv.org/abs/2607.08801arxiv_cs_cr · tlp:amber · 7/13/2026, 4:00:00 AM
Privacy-Preserving Intent Fulfilment and Assurance for 6G RAN arXiv:2607.08809v1 Announce Type: new Abstract: Intent-based network management is the emerging paradigm for 6G service lifecycle automation, with the 3GPP intent management framework (TS~28.312) defining creation, translation, fulfilment, and assurance stages. Existing fulfilment and assurance approaches require deep packet inspection, per-flow state tracking, or access to vendor-internal node telemetry to verify…
Read original ↗https://arxiv.org/abs/2607.08809arxiv_cs_cr · tlp:amber · 7/13/2026, 4:00:00 AM
Statistically Undetectable Backdoors in Deep Neural Networks arXiv:2607.09532v1 Announce Type: cross Abstract: We show how an adversarial model trainer can plant backdoors in a large class of deep, feedforward neural networks. These backdoors are statistically undetectable in the white-box setting, meaning that the backdoored and honestly trained models are close in total variation distance, even given the full descriptions of the models (e.g., all of the weights). The backd…
Read original ↗https://arxiv.org/abs/2607.09532arxiv_cs_cr · tlp:amber · 7/13/2026, 4:00:00 AM
Ruby: Unmasking Unsafe Rust in Stripped Binaries via Machine Learning arXiv:2211.00111v3 Announce Type: replace Abstract: Rust, as an emerging system programming language, introduces $\texttt{unsafe}$ to allow developers to bypass safety checks during compilation. As a result, memory safety bugs are typically confined to the $\texttt{unsafe}$ regions, which have been the primary focus of Rust bug-finding tools. However, such tools rely on the presence of the $\texttt{unsafe}…
Read original ↗https://arxiv.org/abs/2211.00111arxiv_cs_cr · tlp:amber · 7/13/2026, 4:00:00 AM
Privacy Detective: A Narrative Game that Cultivates Student Developers' Privacy Awareness by Harnessing Legal Documents arXiv:2607.09022v1 Announce Type: cross Abstract: Developers' choices about what data a system collects, how it is used and shared, and what defaults govern user choices directly shape users' privacy experiences. Yet, developers often make problematic privacy-related design decisions without realizing the potential consequences. We introduce Privacy Detecti…
Read original ↗https://arxiv.org/abs/2607.09022arxiv_cs_cr · tlp:amber · 7/13/2026, 4:00:00 AM
Event Burst Trigger: An Availability Backdoor Attack on Event-Based SNN Object Detection arXiv:2607.09115v1 Announce Type: cross Abstract: Event-based vision and spiking neural networks (SNNs) are increasingly adopted for edge intelligence under strict latency and energy constraints. However, the vulnerability of event-based SNN object detection models to availability backdoor attacks remains insufficiently studied. This paper presents Event Burst Trigger (EBT), an availabil…
Read original ↗https://arxiv.org/abs/2607.09115arxiv_cs_cr · tlp:amber · 7/13/2026, 4:00:00 AM
When Routes Run Out: Adversarial Co-Learning and Explainable Robustness in Quantum Repeater Networks arXiv:2607.09378v1 Announce Type: cross Abstract: We study an adversarial bandit problem for entanglement-based quantum-network routing over a modest graph corpus. Alice selects an end-to-end repeater route for an Ekert-91 protocol (E91) representing her move, while Eve selects an attack surface, either edge intercept--resend or repeater memory degradation. Payoffs are drawn …
Read original ↗https://arxiv.org/abs/2607.09378arxiv_cs_cr · tlp:amber · 7/13/2026, 4:00:00 AM
VEXAIoT: Autonomous IoT Vulnerability EXploitation using AI Agents arXiv:2607.09653v1 Announce Type: new Abstract: Internet of Things (IoT) systems are inherently vulnerable due to constrained hardware, outdated firmware, and insecure default configurations, creating a need for scalable and adaptive security testing approaches. While recent adoptions of Large Language Model (LLM) agents have demonstrated promise in penetration testing and Capture-the-Flag (CTF) environments,…
Read original ↗https://arxiv.org/abs/2607.09653arxiv_cs_cr · tlp:amber · 7/13/2026, 4:00:00 AM
Impact of Benign Connectivity Variations on Intrusion Detection for Encrypted OPC UA Traffic in Industrial Private 5G Networks arXiv:2607.09659v1 Announce Type: new Abstract: Machine learning (ML)-based intrusion detection systems (IDSs) are increasingly used to monitor encrypted industrial communication. However, their behavior under realistic private 5G operating conditions remains insufficiently understood. This paper investigates the impact of benign connectivity variati…
Read original ↗https://arxiv.org/abs/2607.09659arxiv_cs_cr · tlp:amber · 7/13/2026, 4:00:00 AM
SFDS: Selective File Disclosure System arXiv:2607.09370v1 Announce Type: new Abstract: Access control to networked resources has been a longstanding challenge. The conventional solution relies on authentication mechanisms, which introduce additional complexities associated with Identity and Access Management (IAM). Such systems require user authentication, identity management, and authorization services, while also introducing security risks arising from vulnerabilities, mis…
Read original ↗https://arxiv.org/abs/2607.09370arxiv_cs_cr · tlp:amber · 7/13/2026, 4:00:00 AM
Federated Learning Architecture: Data Privacy and System Security Approaches arXiv:2607.09391v1 Announce Type: new Abstract: This study explores the integration of homomorphic encryption and differential privacy techniques to enhance data privacy and security in Federated Learning (FL) systems. FL allows data to remain on local devices, eliminating the need for centralized data collection; however, sensitive information may still be leaked during model updates. To address th…
Read original ↗https://arxiv.org/abs/2607.09391arxiv_cs_cr · tlp:amber · 7/13/2026, 4:00:00 AM
Triggering Stealthy Feature Map Backdoors via Physical Fault Injection in Embedded Neural Networks arXiv:2607.09473v1 Announce Type: new Abstract: Fault injection (FI) attacks on embedded neural network (NN) implementations primarily focus on inducing misclassification by corrupting weights or intermediate computations, overlooking their interaction with algorithmic adversarial threats. In this work, we present a cross-level attack that bridges implementation-level physical …
Read original ↗https://arxiv.org/abs/2607.09473arxiv_cs_cr · tlp:amber · 7/13/2026, 4:00:00 AM
Efficient and Universal Watermarking for LLM-Generated Code Detection arXiv:2402.07518v5 Announce Type: replace Abstract: Large language models (LLMs) have significantly enhanced the usability of AI-generated code, providing effective assistance to programmers. This advancement also raises ethical and legal concerns, such as academic dishonesty and the generation of malicious code. For accountability, it is imperative to detect whether a piece of code is AI-generated. Waterm…
Read original ↗https://arxiv.org/abs/2402.07518arxiv_cs_cr · tlp:amber · 7/13/2026, 4:00:00 AM
Entropy Bootstrapping for Wireless Embedded Systems arXiv:2607.08865v1 Announce Type: new Abstract: Weak randomness has broken deployed cryptography through implementation bugs, boot entropy scarcity, and backdoored generators. Inexpensive wireless sensors concentrate the risk because many boot or operate in highly deterministic conditions while relying on basic, rudimentary, or opaque RNGs. On ESP32-class boards, RF-disabled wireless device RNG register (WDEV) output is pse…
Read original ↗https://arxiv.org/abs/2607.08865arxiv_cs_cr · tlp:amber · 7/13/2026, 4:00:00 AM
Portable Acceleration of Learning With Errors KEMs for Post-Quantum Cryptography arXiv:2607.09541v1 Announce Type: new Abstract: The transition to post-quantum cryptography (PQC) is driving demand for implementations that can meet the computational requirements of real-world applications. Among the proposed PQC constructions, Learning With Errors (LWE) based key encapsulation mechanisms (KEMs) are particularly attractive due to their strong security foundations, but they inc…
Read original ↗https://arxiv.org/abs/2607.09541arxiv_cs_cr · tlp:amber · 7/13/2026, 4:00:00 AM
TSAI-MetaFraud: A Benchmark Dataset for Financial Fraud Transaction and Behavioral Risk Detection in Metaverse Ecosystems arXiv:2607.09528v1 Announce Type: cross Abstract: The emergence of metaverse platforms has created virtual economies that introduce new challenges related to fraud, bot activity, and illicit financial behavior. Despite growing interest in trustworthy metaverse analytics, existing datasets typically focus on user behavior, authentication, or financial tran…
Read original ↗https://arxiv.org/abs/2607.09528arxiv_cs_cr · tlp:amber · 7/10/2026, 4:00:00 AM
Controllability-Aware Adversarial Examples Against LLM-Based Network Traffic Classifiers arXiv:2607.07739v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly explored as network intrusion detection classifiers, but their adversarial robustness under realistic attacker constraints remains unclear. We present a controllability-aware black-box transfer framework for LLM-based network traffic classifiers. The framework partitions flow features into direc…
Read original ↗https://arxiv.org/abs/2607.07739arxiv_cs_cr · tlp:amber · 7/10/2026, 4:00:00 AM
Secure QR Codes: Authenticity Verification via EdDSA Signatures and CBOR Certificates arXiv:2607.08383v1 Announce Type: new Abstract: QR codes are a ubiquitous part of daily life, widely trusted by millions. However, their lack of inherent security features has given rise to critical attack vectors, such as spoofing (quishing) on public infrastructure like self-service parking machines. To address this, we present a comprehensive evolution of secure QR code architectures. Fi…
Read original ↗https://arxiv.org/abs/2607.08383arxiv_cs_cr · tlp:amber · 7/10/2026, 4:00:00 AM
Forensic Schema for Psychological Manipulation in Cyber Fraud: LLM-Driven Victim Reports Analysis arXiv:2607.07751v1 Announce Type: new Abstract: Existing cybercrime classification schemas capture contact metadata and financial transactions but omit the psychological manipulation techniques perpetrators employ. We present a forensic schema (four categories, 35 questions) adding 11 manipulation indicators and cryptocurrency evidence fields to established forensic foundations.…
Read original ↗https://arxiv.org/abs/2607.07751arxiv_cs_cr · tlp:amber · 7/10/2026, 4:00:00 AM
Token-Flow Firewall: Semantic Runtime Auditing for Persistent AI Agents arXiv:2607.08395v1 Announce Type: new Abstract: Persistent AI agents extend large language models (LLMs) beyond single-turn interaction into long-lived software systems. Unlike traditional chat assistants, unsafe content in these agents can propagate through persistent state, reusable skills, and tool-mediated interactions, creating a substantially larger semantic attack surface. We observe that most sec…
Read original ↗https://arxiv.org/abs/2607.08395arxiv_cs_cr · tlp:amber · 7/10/2026, 4:00:00 AM
Reverse Engineering Compliance: A Dual-Graph Verification Framework for Auditing Legacy IT Security Concepts arXiv:2607.08292v1 Announce Type: new Abstract: The NIS-2 Directive increases the need for continuous, auditable compliance evidence and motivates a shift from document-based compliance toward machine-readable compliance artifacts. The Open Security Controls Assessment Language (OSCAL) is a standard for this purpose, which the German Federal Office for Information Sec…
Read original ↗https://arxiv.org/abs/2607.08292arxiv_cs_cr · tlp:amber · 7/10/2026, 4:00:00 AM
Mechanistic Interpretability of LLM Jailbreaks via Internal Attribution Graphs arXiv:2607.07903v1 Announce Type: new Abstract: Large language models (LLMs) exhibit remarkable capabilities but remain highly vulnerable to adversarial prompts and jailbreak attacks. Existing approaches primarily analyze these failures through input-output behaviors or attribution methods, offering limited insight into how adversarial perturbations alter the model's internal reasoning. Consequent…
Read original ↗https://arxiv.org/abs/2607.07903arxiv_cs_cr · tlp:amber · 7/10/2026, 4:00:00 AM
Mini-Programs, Mega-Problems: Unveiling OAuth-based Authentication Misuses in Mini-Programs via Dynamic Analysis arXiv:2607.08232v1 Announce Type: new Abstract: Mini-programs have become a dominant paradigm for lightweight application deployment within super apps such as WeChat. To support seamless integration, super apps provide OAuth mechanisms for user login. However, improper integration of OAuth-based Authentication (OBA) flows by third-party developers can lead to crit…
Read original ↗https://arxiv.org/abs/2607.08232arxiv_cs_cr · tlp:amber · 7/10/2026, 4:00:00 AM
Multi-Agent Firewall Architecture for Privacy Protection of Sensitive Data in Interactions with Language Models arXiv:2607.08282v1 Announce Type: new Abstract: While Large Language Models (LLMs) have become essential productivity tools, their integration into workflows without adequate safeguards creates significant risks. This paper proposes an open-source, privacy-focused, user-facing firewall designed to secure both web-based and programmatic LLM interactions. The archite…
Read original ↗https://arxiv.org/abs/2607.08282arxiv_cs_cr · tlp:amber · 7/10/2026, 4:00:00 AM
TRACE: A Two-Channel Robust Attribution Watermark via Complementary Embeddings for LLM-Agent Trajectories arXiv:2607.08400v1 Announce Type: new Abstract: LLM agents reach users through resellers, who may rebrand a developer's agent or substitute a cheaper model. When provenance is disputed, attribution rests on the trajectory log (the record of tool calls, observations, and executed actions, not the model's reasoning), which the reseller stores and processes to meter usage. …
Read original ↗https://arxiv.org/abs/2607.08400arxiv_cs_cr · tlp:amber · 7/10/2026, 4:00:00 AM
From Legacy Documentation to OSCAL: An MCP-Based Agent Pipeline for Threat-Informed Continuous Compliance in Critical Infrastructure arXiv:2607.08288v1 Announce Type: new Abstract: In critical infrastructure, operational technology environments often cannot be actively scanned, and yet active system feedback is needed for risk assessment and compliance. This paper presents a non-invasive, MCP-grounded multi-agent pipeline that converts natural-language system descriptions in…
Read original ↗https://arxiv.org/abs/2607.08288