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Forensia intelligence desk · 4,100 source documents · 4,068 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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24,650 Internet-Exposed BMCs Disclose IPMI Password Hashes Before Login
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[$] A report from Debian's new DFSG team
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Apple Patches 87 Vulnerabilities in iOS, 155 in macOS Tahoe
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JFrog Confirms OpenAI Models Exploited Artifactory Zero-Day Before Hugging Face Breach
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Security updates for Tuesday
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OT Security Startup Frenos Raises $1.52 Million
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Critical OpenWrt DHCPv6 Flaw Could Let Unauthenticated Attackers Run Code as Root
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Nimbus Manticore Deploys NightLedger and Turns Victim Systems Into Covert Relays
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Microsoft Unveils MAI-Cyber-1-Flash, Its First Cybersecurity AI Model
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How we use /goal to find bugs in Patch the Planet
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Act Security Emerges from Stealth to Fight the Patch Problem
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Hacker Conversations: Tal Kollander’s Journey From Black Hat to Hack Blocker
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Hush Security Raises $30 Million for AI Agent Governance
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IR Trends Q2 2026: Phishing and weaponized remote management tools drive attack chains
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Google Adopts New Threat Actor Naming System
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Critical TeamCity Flaw Could Let Attackers Run OS Commands Without Logging In
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Researcher Says AI Helped Develop Linux Traffic-Control Race Into Root Exploit
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Unpatched Fastjson Vulnerability Exploited in Attacks
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Critical Arista VeloCloud Orchestrator Vulnerability Exploited as Zero-Day
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Microsoft Says New Cybersecurity AI Model Helps MDASH Hit 95.95% at Half the Cost
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Origin Energy Data Breach Affects 900,000 Australians
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Attackers Exploit Arista VeloCloud Orchestrator Command Injection Flaw
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SMARM+: Analyzing and Enhancing Shuffled Measurements for Remote Attestation in Real-Time IoT Settings
SMARM+: Analyzing and Enhancing Shuffled Measurements for Remote Attestation in Real-Time IoT Settings arXiv:2607.23698v1 Announce Type: new Abstract: Remote attestation (RA) is a lightweight security primitive for detecting software compromise on IoT devices. Traditional RA schemes require atomic, non-interruptible memory measurements, making them difficult to deploy alongside real-time workloads. SMARM addresses this limitation by measuring memory in a secret, shuffled blo…
DualityCert: Verifier-Gated Language-Model Repair of Broken Duality Claims in Quantum Field Theory
DualityCert: Verifier-Gated Language-Model Repair of Broken Duality Claims in Quantum Field Theory arXiv:2607.23614v1 Announce Type: new Abstract: We present DualityCert, a symbolic verifier for candidate Seiberg-duality claims in four-dimensional N=1 quiver gauge theories. The verifier evaluates 't Hooft anomaly matching, superpotential R-charge consistency, central-charge matching, and a bounded chiral-ring proxy. A claim that passes receives a consistency certificate, whi…
HiTMS: A High-Throughput Multi-Stream Linguistic Steganography Framework
HiTMS: A High-Throughput Multi-Stream Linguistic Steganography Framework arXiv:2607.23597v1 Announce Type: new Abstract: Generative linguistic steganography conceals secret bits within the sampling randomness of large language models. Existing schemes are single-stream, conveying an entire secret through a single response to a single prompt. This convention incurs two limitations: it provides no protocol-level support for batched multi-stream inference, and naive co-batching…
Collusion-Resistant Image-Agnostic Watermarking for Multi-Screen Shooting
Collusion-Resistant Image-Agnostic Watermarking for Multi-Screen Shooting arXiv:2607.23553v1 Announce Type: new Abstract: Screen-shooting poses a significant threat to confidential information protection. While existing screen-shooting watermarking methods enable copyright verification, the copyrighted images carrying the same copyright watermark across different screens often exhibit highly similar and estimable watermark patterns. These shared patterns can be exploited for…
Mission-Level Runtime Assurance for LLM-Assisted ISR Swarms over a Verification-Aware Fabric
Mission-Level Runtime Assurance for LLM-Assisted ISR Swarms over a Verification-Aware Fabric arXiv:2607.23532v1 Announce Type: new Abstract: Swarms of LLM-assisted autonomous robots are increasingly proposed for cooperative intelligence, surveillance, and reconnaissance (ISR) in contested environments. A growing class of their assurance failures arises not within any single platform but across the swarm: individually-compliant actions compose into a mission-level violation: …
ATLAS: Automated Approximation of Transformers for Efficient Homomorphic Inference in One Hour
ATLAS: Automated Approximation of Transformers for Efficient Homomorphic Inference in One Hour arXiv:2607.23478v1 Announce Type: new Abstract: Fully homomorphic encryption (FHE) provides strong cryptographic guarantees for private inference, but deploying transformer models under FHE remains prohibitively expensive. A key bottleneck is that non-linear operations such as softmax, normalization, and activation must be replaced with polynomial approximations compatible with the…
Isolated but Exposed: Persistence-Based Memory Extraction Attack on LLM Agents
Isolated but Exposed: Persistence-Based Memory Extraction Attack on LLM Agents arXiv:2607.23444v1 Announce Type: new Abstract: LLM-based agents extend large language models with long-term memory (LTM) that persists privacy-sensitive user data across sessions. Production systems mitigate extraction risks through memory isolation, binding each user's LTM to a unique identifier. This defense has blocked known attacks on shared storage, fostering the assumption that isolated LTM…
Renting the Cracking Machine with a Cost-and-Time Analysis of Exhaustive DES-56 Key Search in the Cloud
Renting the Cracking Machine with a Cost-and-Time Analysis of Exhaustive DES-56 Key Search in the Cloud arXiv:2607.23443v1 Announce Type: new Abstract: The Data Encryption Standard (DES), with its 56-bit key, has been considered cryptographically broken since 1998. However, a concrete, reproducible measurement of the cost and time required to perform an exhaustive key search using today's commodity cloud infrastructure has not been widely reported in recent literature. In th…
PATCH-FFT: Unmasking Dormant Hardware Trojans with Patch-Based Frequency-Domain Transformers
PATCH-FFT: Unmasking Dormant Hardware Trojans with Patch-Based Frequency-Domain Transformers arXiv:2607.23421v1 Announce Type: new Abstract: Hardware Trojans embedded by malicious entities in integrated circuits can covertly leak sensitive information through power side channels, often remaining undetected in their dormant state until specific trigger conditions activate their malicious behavior. For information-leaking Trojans, detection in the dormant state is critical, as…
TroPUF: Evaluating Hardware Trojan Insertion in Delay-Based Physical Unclonable Functions
TroPUF: Evaluating Hardware Trojan Insertion in Delay-Based Physical Unclonable Functions arXiv:2607.23418v1 Announce Type: new Abstract: Delay-based Physical Unclonable Functions (PUFs) are commonly used for device authentication and key generation due to the fact that they rely on manufacturing induced delay variations. However, these same variations make PUFs inherently non-deterministic, which can allow malicious logic to blend in with normal circuit behavior. As a resul…
Early Detection of Hardware Trojans Using Neural Controlled Differential Equations and Analysis of Power Traces
Early Detection of Hardware Trojans Using Neural Controlled Differential Equations and Analysis of Power Traces arXiv:2607.23417v1 Announce Type: new Abstract: Evolving Hardware Trojans pose a serious threat to modern digital systems by evading traditional detection through stealthy, adaptive behavior. Even recent methods that leverage advances in machine learning can only detect them after activation, leaving a critical window for potential security breaches. To address thi…
Rendering on Real Silicon: GPU Render-Timing as a Passive, AI-Resistant CAPTCHA Signal
Rendering on Real Silicon: GPU Render-Timing as a Passive, AI-Resistant CAPTCHA Signal arXiv:2607.23389v1 Announce Type: new Abstract: Conventional CAPTCHAs pose puzzles that modern AI systems increasingly solve, while behavioral and cryptographic-attestation defenses carry privacy or enrollment costs. We investigate an orthogonal signal: the physical timing behavior of a client's GPU under a controlled WebGL rendering workload. Unlike WebGL fingerprinting, which hashes pixe…
Exploring the OODA Loop as a Systematic Way of Thinking in Coping with Conflicts
Exploring the OODA Loop as a Systematic Way of Thinking in Coping with Conflicts arXiv:2607.23342v1 Announce Type: new Abstract: When conflicts emerge, we need systematic ways of thinking to deal with them. This paper revisits Boyd's Observe, Orient, Decide, Act (OODA) loop and explores its usefulness as a systematic way of thinking for reasoning about conflicts in dynamic environments characterized by uncertainty, adaptation, and adversarial interference. We explore the OOD…
A Structured Cyber Threat Intelligence Dataset Using STIX 2.1 Entities and MITRE ATT&CK Mappings
A Structured Cyber Threat Intelligence Dataset Using STIX 2.1 Entities and MITRE ATT&CK Mappings arXiv:2607.23312v1 Announce Type: new Abstract: Cyber threat intelligence (CTI) reports are typically written in unstructured formats, which complicates the extraction and analysis of important entities and adversarial behaviors. Although existing CTI research provides extraction tools, knowledge-graph frameworks, and MITRE ATT&CK mapped datasets, curated report-level datasets th…
Hiding in Plain Sight: An Effective Physical Adversarial Patch Attack against Visual-Infrared Fused Face Detection
Hiding in Plain Sight: An Effective Physical Adversarial Patch Attack against Visual-Infrared Fused Face Detection arXiv:2607.23292v1 Announce Type: new Abstract: Deep learning-based visual-infrared fused face detection models are increasingly deployed across a wide range of applications, yet they remain susceptible to adversarial patch attacks. Most prior attacks target either the visual or the infrared image alone in the digital domain, which renders them ineffective again…
From Signals to Behaviors: Evidence-Based Android Malware Detection
From Signals to Behaviors: Evidence-Based Android Malware Detection arXiv:2607.23272v1 Announce Type: new Abstract: Android malware remains a persistent threat, and detecting it accurately is a long-standing open problem. Whether an app is malicious depends on what it actually does and the context in which it does it, not on the surface signals it happens to exhibit. Existing detectors instead reason about proxies for behavior, such as learned features or local code slices, …
SPARC: Automated Root-Cause Analysis of Pre-Silicon Power Side-Channel Leakage in the Processor Design Flow
SPARC: Automated Root-Cause Analysis of Pre-Silicon Power Side-Channel Leakage in the Processor Design Flow arXiv:2607.23218v1 Announce Type: new Abstract: Power-Side-Channel Leakage (PSCL) originates from architectural and micro-architectural artifacts in a processor and poses a severe threat to the confidentiality of cryptographic software. Consequently, pre-silicon PSCL evaluation is indispensable for secure hardware design. Existing frameworks are either limited by poor …
False Prophets: On the Security of World Models in Agentic Systems
False Prophets: On the Security of World Models in Agentic Systems arXiv:2607.23147v1 Announce Type: new Abstract: Large language models now power autonomous agents capable of complex, multi-step tasks in different environments. Accurate and reliable execution of these tasks requires the agent to predict the results of its actions. Recent research proposes to enhance predictive capabilities via specially trained environment simulators-world models. While world models can imp…
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clustered evidenceWatchGuard Patches Critical Vulnerabilities
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Microsoft Rolls Out 22 Fresh Security Patches
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Google Patches 6th Chrome Zero-Day of 2026
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Cisco Warns of Unpatched Secure Email Flaws, Patches Critical Switch Vulnerabilities
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Cisco Patches Critical Crosswork, Secure Workload Vulnerabilities
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