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Forensia intelligence desk · 4,099 source documents · 4,067 stories
Live reporting, advisories and research arranged by editorial readiness. Thin sources stay visible, but they are clearly marked instead of being presented as complete analysis.
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FedADB: Class Anchor-Driven Dual-Branch Federated Learning for Mitigating Forgetting
arXiv:2608.15310v1 Announce Type: new Abstract: Multimodal data collected by heterogeneous devices are used for collaborative training, where federated learning (FL) serves as a key paradigm for effective distributed modeling with data privacy preservation. However, local training suffers from the forgetting of previously learned global knowledge under cross-client data heterogeneity, which leads to significant declines in both performance and convergence speed. Most previous…
Balancing Privacy and Compliance in DeFi: A Zero-Knowledge-Based Auditable Cross-Chain Framework
arXiv:2608.15276v1 Announce Type: new Abstract: With the rise of decentralized finance (DeFi), cross-chain transactions, transfers of assets across different blockchain networks, face a fundamental conflict between user privacy and regulatory compliance. Unlike single-chain systems, cross-chain environments must balance privacy and auditability across heterogeneous architectures. Existing solutions, from transparent ledgers to anonymous cryptocurrencies, fail to reconcile the…
External Sinkhole Attack Detection in Large-Scale WSNs Using Metaheuristic Feature Selection
arXiv:2608.15274v1 Announce Type: new Abstract: Sinkhole attacks in large-scale wireless sensor networks (WSNs) pose a serious threat to network functionality. This paper presents a metaheuristic feature selection for sinkhole attack detection using the bee swarm optimization (BSO) algorithm. In an external sinkhole attack simulation with 2000 nodes deployed over a 3000 $\times$ 3000 m$^2$ field, the proposed method achieves a detection accuracy of 0.997 while reducing the 16…
Inferring 1-Minimal Trigger Configurations for Assessing Linux Kernel CVE Triggerability
arXiv:2608.15225v1 Announce Type: new Abstract: Vendors assessing Linux kernel CVEs need to know whether a bug is triggerable under production-tailored configurations, not merely whether a version is affected, yet upstream reproducers and vulnerability databases rarely provide configuration-level context. We study minimal trigger-configuration inference: given a CVE entry and a target kernel version (optionally a baseline .config), we synthesize a Kconfig-satisfiable option s…
Pre-Model Representation Failures in GNN-Based Smart Contract Vulnerability Detection
arXiv:2608.15184v1 Announce Type: new Abstract: This paper is a failure analysis of the representation layer underlying GNN-based smart contract vulnerability detectors. These systems convert source code into graphs before any learning takes place; if the graph fails to capture the code's semantics, no model improvement can compensate. We investigate GNNSCVulDetector and identify four failures. First, structurally different contracts produce byte-for-byte identical graphs, co…
An Adaptive Gradient Clipping and Noise Injection Mechanism for Differentially Private Federated Learning
arXiv:2608.15153v1 Announce Type: new Abstract: Differentially private federated learning must balance privacy protection against model accuracy and training efficiency. Static gradient clipping applies a fixed threshold throughout training and across model layers, which can cause excessive clipping when the threshold is too small or unnecessarily large noise when it is too large. This paper presents DDP-SA-adaptive, an adaptive gradient clipping and noise adding mechanism fo…
SAEFUZZ: Smart Contract Vulnerability Detection through Statically Guided Evolutionary Fuzzing
arXiv:2608.15151v1 Announce Type: new Abstract: The effectiveness of smart contract fuzzing depends strongly on whether generated transactions reach deep, state-dependent execution paths. Existing fuzzers often generate highly random call sequences, wasting executions on semantically invalid or low-value states and leaving vulnerabilities that require specific invocation orders unexplored. We present a lightweight method for generating fuzz test cases under bytecode-level sta…
Beyond Direct Access: Resource Hijacking in LLM Agents
arXiv:2608.15108v1 Announce Type: new Abstract: Large language model agents are increasingly connected to high-value resources such as computing infrastructure, credentials, usage budgets, identities, private knowledge, communication channels, and organizational workflows. Existing agent security research mainly studies attacks on instructions, data, and tool behaviors, while high-value resources accessible to agents have received much less attention as direct attack targets.…
WeSCE: A Benchmark for Measuring Security Drift in LLM-Driven Code Editing
arXiv:2608.15092v1 Announce Type: new Abstract: In this work, we introduce WeSCE, a benchmark for quantifying security drift in code editing under weak-security constraints, where tasks specify only functional objectives without explicit security requirements. WeSCE consists of 400 executable programs derived from real-world code, covering feature addition, feature removal, bug fixing, and refactoring. To quantify security drift, we propose a continuous risk representation th…
Tensor--Action Ko--Lee Cryptography: A Framework and Structural Cryptanalysis of Commuting Subgroup Constructions
arXiv:2608.15030v1 Announce Type: new Abstract: Tensor isomorphism has been studied as an algebraic problem relevant to post-quantum cryptography, while its use in public-key encryption remains open. In this paper, we formulate a Ko--Lee-style framework for public-key encryption from cubic tensor actions and prove its formal correctness. We then show that the framework is generically insecure when the commuting matrix subgroups are given by public finite generating sets. View…
Hierarchical Agentic Incident Response with Digital-Twin-Validated Attack Inference
arXiv:2608.15016v1 Announce Type: new Abstract: Network incident response remains slow and labor-intensive as the defender must infer multi-stage attacks from partial observations and translate recovery decisions into reliable system commands. Decision-theoretic planners provide principled optimization but typically rely on abstract states and predefined actions, while large language model (LLM) agents can reason over operational context but may hallucinate attacks and respon…
SysEvolve: An AI-native, safe, autonomous adversarial attack-defense co-evolutionary system
arXiv:2608.15012v1 Announce Type: new Abstract: The rapid advancement of large language models (LLMs) has created a growing asymmetry in cybersecurity, where attack accelerates toward autonomous execution while defense remains predominantly human-intensive. Despite substantial prior work across cyber ranges, AI-driven attack, and AI-driven defense, this asymmetry persists. We trace it to a deeper root cause, that evolution itself has stalled on both sides at three layers. To…
Workspace Topology as an Attack Vector in Agentic Coding Assistants
arXiv:2608.14876v1 Announce Type: new Abstract: Agentic coding assistants are finding widespread use, not just in new code development but in quickly ingesting and leveraging third-party code. This opens up a risk of malicious code being ingested as these coding tools operate with broad filesystem access inside developer workspaces. In this paper, we extensively study the impact of different dimensions of a novel attack surface we term workspace topology -- defined via direct…
STAR-FL: Secure Federated Learning with Spatial-Temporal Analysis and Robust Aggregation
arXiv:2608.14861v1 Announce Type: new Abstract: Data poisoning attacks pose serious security threats to Federated Learning (FL) systems in Computer Vision. Despite growing research attention, two key challenges remain for existing defense techniques: (1) accurately distinguishing between benign and malicious model updates and (2) effectively mitigating the influence of poisoned model updates during model aggregation. To address these challenges, we propose a novel defense fra…
Bit-Level Triangular Content-Aware Permutation for Fragile Image Watermarking: Zero False Positive Rate, Single-Bit Sensitivity, and Arbitrary Dimension Support
arXiv:2608.14800v1 Announce Type: new Abstract: With the growth of digital document exchange, protecting image integrity against attacks such as Vector Quantization (VQ) and collage has become critical. Existing methods are vulnerable to these attacks and limited to fixed image dimensions. This paper presents a novel, dimension-agnostic, fragile watermarking algorithm that enhances security and tamper localization by replacing conventional hash functions with Triangular Conte…
From Positionwise Confidence to Prefix Scheduling: Verifier Skipping in Speculative Decoding
arXiv:2608.14787v1 Announce Type: new Abstract: Speculative decoding is a leading technique to reduce the cost of autoregressive generation by using a small drafter to propose several tokens, which are then verified in parallel by a larger target model. Speculative diffusion decoding (SDD) further removes sequential drafting by generating every position in a draft block in parallel with a discrete diffusion model. However, SDD still invokes the target on every block, leaving…
SynthGuard-ReleaseBench: Locked-Audit Evidence for Synthetic Tabular Data Releases
arXiv:2608.14753v1 Announce Type: new Abstract: Synthetic tabular data are often judged by realism, privacy, or downstream-task scores. Those scores do not answer whether a proposed release is supported for a named use, population, and threat model. We introduce SynthGuard-ReleaseBench, an audit framework that locks the use, candidate panel, tolerances, and audit schedule before evaluation. It compares real-trained and synthetic-trained workflows on protected data, gives simu…
Not Discrete Enough: On the Inherent Insecurity of dTPMs for Measured Boot
arXiv:2608.14736v1 Announce Type: new Abstract: Measured Boot, a mechanism enabled through Trusted Platform Modules (TPMs), is commonly used for passwordless protection of data-at-rest, aiming to protect data when the device is lost or stolen. Microsoft's standpoint is neutral on which way a TPM should be implemented: Firmware-based TPMs (fTPMs) are viewed as more economical but less secure. Despite the inherent susceptibility to bus sniffing attacks, discrete TPMs (dTPMs) ar…
AccretionLink: On-Device Auditing of Exposure-Control Attacks on Attribute Inference
arXiv:2608.14735v1 Announce Type: new Abstract: Exposure control lets an adversary rank authentic public posts to strengthen private-attribute inference without altering content. AccretionLink defines confidentiality and integrity games for this attack, models bounded selection odds through partial identification, and constructs dependence-aware time-uniform e-processes. On 52 held-out synthetic profiles, odds-four selection reduced aggregate negative log likelihood at every…
Harmony - Rekt
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Multi-Vector (Late Interaction) Embedding Models with Sentence Transformers
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Ukrainian software developer faces 12 years in Swiss ransomware trial
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Critical GitLab GraphQL Flaw Could Let Unauthenticated Attackers Delete Public Projects
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Nearly 750k had financial info, SSNs leaked in South Carolina loan company breach
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Same Cluster, 33 Points More Utilization: What Changed Was the Order
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Snowflake GitHub Actions Flaw Lets Crafted Issues Trigger Command Injection
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Forminator WordPress Flaw Can Enable Unauthenticated RCE via Malicious PHP Uploads
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Cavern C2 Uses DNS and Google Apps Script to Blend Into Legitimate Traffic
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SafePal latest crypto hardware wallet maker affected by breach, with nearly 40,000 impacted
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[$] Development statistics for the 7.2 kernel
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Irregular faces criticism over ‘spin’ in AI hacking postmortem
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[$] Bootstrappable builds: how and why
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Poland probes MyDr healthcare software breach potentially affecting 19 million people
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GNU poke 5.0 released
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680,000 Impacted by French Tax Authority Data Breach
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Mark J. Wielaard receives Distinguished Service Award in Software Freedom
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17th August – Threat Intelligence Report
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Security updates for Monday
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⚡ Weekly Recap: VMware Exploits, Windows 0-Day, MCP Attacks, Browser Hijacks and More
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Ukraine says cyberattack hit Russian e-commerce giant Wildberries amid drone strikes
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clustered evidenceWatchGuard Patches Critical Vulnerabilities
developing · new
Microsoft Rolls Out 22 Fresh Security Patches
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Google Patches 6th Chrome Zero-Day of 2026
developing · new
Cisco Warns of Unpatched Secure Email Flaws, Patches Critical Switch Vulnerabilities
developing · new
Cisco Patches Critical Crosswork, Secure Workload Vulnerabilities
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