Search: “availability”

46 stories in the last 30d

Searchkeyword smart Sortlatest hot importance relevance

DomainAll Cyber AIWindow24h 3d 7d 30d AllIn the wild Important only Show duplicates

CategoryAll Advisory 138 AI industry 99 Vulnerability 98 Exploit / PoC 96 AI safety & security 80 Industry 80 Tools 76 AI research 72 Research 46 Model release 44 Malware 38 Threat actor 35 Data breach 34 AI tools & infra 32

SeverityAll critical 50 high 214 medium 185 low 51 info 527

8,539 Reasons To Rethink How Vulnerabilities Get Patched

Rapid7 counted 8,539 high and critical CVEs in Q2 2026, double last year, with PoC availability up 76%.

Rapid7's Q2 2026 Threat Landscape Report tallied 8,539 high- and critical-severity vulnerability disclosures, twice the number recorded in Q2 2025, with newly disclosed flaws having public proof-of-concept code up 76% year over year. Of newly exploited vulnerabilities, 62% were network-exploitable and required neither authentication nor user interaction. Fake CAPTCHA and ClickFix social engineering accounted for 31.8% of incident response cases, the United States recorded 881 listed ransomware victims, and APT28 exploited SOHO routers for DNS hijacking while Iranian groups targeted US industrial control and OT systems.

Help Net SecurityAug 20, 00:00 UTC · 28d agoResearch

Apple Reference Image: A New Approach for Verified Photography

Apple introduces Reference Image, hardware-backed verifiable photography on iPhone 18 Pro using sensor signing and Private Cloud Compute to counter AI-generated fakes.

Apple announced Reference Image, an opt-in camera mode debuting on the main sensor of iPhone 18 Pro and iPhone 18 Pro Max that produces securely timestamped, verifiable photographs. The design splits into two phases: a secure digital negative created by cryptographically signing pixel data at the sensor immediately after capture (preventing injection or tampering), then developing that negative into a reference image. Private Cloud Compute handles processing without exposing image contents to anyone, including Apple, and fraudulent reference images can be revoked without revealing the photographer's identity. Apple positions the system as stronger than C2PA-based approaches, which sign metadata after capture, are vulnerable to editing-chain compromise, and can tie images to a device or individual.

Hacker News · securitySep 16, 02:07 UTC · 1d agoResearch HN 25↑ · 18 comments

Testing race conditions with memory access tracing and stack-based delay injection

Google Project Zero released MAccConc, Linux kernel tooling that traces memory accesses to explore and test race condition interleavings.

A Google Project Zero researcher published MAccConc (Memory Access Concurrency), tooling for exploring possible interleavings of multithreaded test cases in the Linux kernel, available on GitHub. The tools use KCOV with ASAN outline-mode instrumentation to record per-access memory traces, enabling automatic testing of all A-B-A interleavings plus terminal and GUI explorers for manual analysis. The work targets confirming race condition candidates, building reliable regression tests, and enabling concurrency fuzzing, drawing on ideas from SKI and Ned Williamson's sockfuzzer.

Google Project ZeroSep 8, 07:00 UTC · 8d agoResearch2

Mapping out your unknown: A threat hunter’s guide to GitHub

Datadog Security Labs publishes a threat-hunting guide with audit-log queries to detect GitHub token theft, device code phishing, and source code exfiltration.

Datadog's threat-hunting guide covers GitHub audit log queries for detecting compromised accounts, stolen personal access tokens, and malicious OAuth app authorizations. Attackers typically obtain credentials through phishing, credential stuffing, leaked secrets, or device code phishing, then map private repositories, exfiltrate source code, and pivot into connected cloud and CI/CD environments. The guide maps detections to MITRE techniques like T1078 and T1528 and documents GitHub logging quirks affecting attribution, token metadata, and visibility fields.

Datadog Security LabsSep 16, 00:00 UTC · 1d agoResearch in the wild1

1Password's AI patching benchmark is misleading

Trail of Bits reanalysis says 1Password's 26% AI clean-fix rate is misleading; 86% of eligible patches blocked exploits.

Trail of Bits critiques 1Password's FLAWED AI patching benchmark, arguing its 26% clean-fix headline mixes trials where agents were instructed to apply wrong fixes (22% of data) with trials that prohibited compiling or testing (36%). Restricting to reasonable conditions, 2,634 of 3,067 patches (86%) blocked the supplied exploit. Trail of Bits also reports 12.5% of 2,265 developer first fixes failed in its own 2024-2026 assessments, and released post-patch-validation and review-walkthrough agent skills.

Lobsters · securitySep 15, 20:03 UTC · 1d agoResearch1

RobResilience: Implementing and Evaluating a Resilience Framework for Cyber-Physical Embodied Systems

RobResilience implements a runtime resilience framework for robots in Webots/ROS2, evaluating tolerable disruption, degradation, and mitigation feasibility across eight attack scenarios.

The paper implements a formal resilience framework for embodied cyber-physical systems using a PR2 robot and ROS2 in a Webots simulation. At runtime it evaluates three predicates — tolerable disruption (δ), tolerable degradation (γ), and mitigation feasibility (μ) — over a compromised device set derived from IDS confidence scores, triggering mitigation strategies when resilience is lost. Eight attack scenarios systematically covering the full predicate state space confirm runtime behavior matches theoretical definitions. The work addresses 'graceful failure paralysis,' where autonomous systems cannot distinguish safe degraded states from catastrophic hazards during attacks.

arXiv cs.CRSep 15, 15:49 UTC · 1d agoResearch

Retrospective by 'gpg.fail' authors

Authors of the gpg.fail GnuPG vulnerability set published a retrospective with talk recording, slides, and a repo PoC.

Sam James shares that the researchers behind the 'gpg.fail' set of GnuPG vulnerabilities have published a retrospective, including a talk recording and slides. The slides appear to mention an additional vulnerability not yet widely reviewed, and a proof-of-concept is available in their repository. This follows earlier discussion of the gpg.fail findings on oss-security.

oss-securityupdated 03:19 UTC · 3h agofirst Sep 13, 01:12 UTC · 4d agoResearch 9 sources1

When the Whole Company Adopts AI: What It Does to Your SOC

Analysis of 16.9 million SOC alerts finds AI-related alerts at 0.43%, growing 685% since February, with 94.1% noise and 0.02% real attacks.

A review of roughly 16.9 million SOC alerts found about 73,000 (0.43%) were AI-related, a share that grew 685% between February and June 2026. Of AI-related alerts, 94.1% were noise, 5.8% genuine risks, and 0.02% real attacks; 79.8% received benign verdicts, 81.7% were automatically suppressed, and only 5.4% reached a human analyst. The only confirmed attacks were phishing campaigns that weaponized AI brand names as lures, while developer coding agents spawning shells and reading credential stores routinely tripped detections written before AI agents existed.

The Hacker NewsSep 12, 10:24 UTC · 4d agoResearch2

Linux Detection Engineering - Local Privilege Escalation

Elastic details a layered detection framework for Linux local privilege escalation, covering 2026's copy-on-write bug wave and LLM-assisted discovery.

Elastic Security Labs describes how most Linux local privilege escalations share a common host flow — an unprivileged process launched from a writable path becoming root — and proposes layered detections combining general outcome-based rules with per-technique rules in Elastic Defend and Auditd. It tracks 13 recent LPE disclosures, seven of which share a copy-on-write/zero-copy bug class, including Copy Fail, DirtyFrag, Fragnesia, DirtyDecrypt, DirtyClone, pedit COW, and RefluXFS. Qualys attributes RefluXFS to an LLM-assisted research effort with Anthropic using Claude Mythos Preview, and another bug is credited to an LLM-assisted workflow. Detection and endpoint rules are published in Elastic's detection-rules and protections-artifacts repositories.

Elastic Security LabsSep 11, 00:00 UTC · 6d agoResearch1

Researchers Use Claude to Port Pre-Auth RCE Exploit From One PLC Model to Another

Forescout used Anthropic's Claude to port a working pre-auth RCE exploit for CVE-2021-31886 between WAGO PLCs, executing ARM shellcode on live hardware.

Forescout Vedere Labs used Claude interactively to port an RCE exploit for CVE-2021-31886, a CVSS 9.8 stack buffer overflow in the Nucleus FTP server's USER command, from a WAGO 750-852 to a WAGO 750-831 PLC, running attacker-supplied ARM shellcode. The final RCE stage cost $535.74 in API usage over 8 hours 32 minutes, and a follow-up attempt to build a C2 implant permanently bricked the device. CERT@VDE lists many Nucleus V1-based WAGO models as vulnerable with no updates available; Siemens plans no Nucleus NET remediation. The work follows a joint NSA/CISA/FBI/DOE/EPA advisory warning of AI-generated exploitation scripts targeting internet-exposed Siemens S7 PLCs.

The Hacker NewsSep 2, 07:47 UTC · 14d agoResearch CVE-2021-318862

Chrome DevTools Technique Enables Authenticated Session Hijacking in Live Windows Browsers

SpecterOps released CDP-Enable-BOF, a Beacon Object File that enables Chrome DevTools Protocol in live Chrome or Edge processes on Windows for session hijacking.

SpecterOps released CDP-Enable-BOF, an x64 Beacon Object File that activates Chrome DevTools Protocol inside running chrome.exe or msedge.exe processes on Windows, exposing cookies, history, saved passwords, and authenticated sessions without administrator rights. It calls Chromium's StartRemoteDebuggingServer on the browser UI thread to stay reliable under CFG, TLS, and CET, and was tested on Chrome 147 and Edge 147. The technique builds on work by DeathFlamingo and Cedric Van Bockhaven; Google had hardened remote debugging in Chrome 136 after attackers used it to steal cookies post-App-Bound Encryption. Defenders can watch Sysmon Event IDs 8 and 10 for injection into browser processes.

The Hacker NewsAug 25, 16:19 UTC · 22d agoResearch2

Locus: A Framework for Exploring and Optimizing Point Addition Hardware for Zero-Knowledge Proofs

Locus framework automates ASIC and FPGA point-addition designs for elliptic curves, achieving 2.71x speedups and 3.11x area reductions for ZKPs.

Locus is a framework that automatically generates ASIC and FPGA implementations of elliptic curve point addition (PADD) for supported equation forms, enabling exploration of over 1,000 design points. On a 12nm technology node, its designs achieve a 2.71x geomean speedup and 3.11x geomean area reduction versus prior ASICs, plus 34.67x geomean speedup over CPU. Integrated into a prior ZKP accelerator at iso-area, it yields a 3.15x geomean speedup on end-to-end proof generation. The framework is open source on GitHub.

arXiv cs.CRSep 16, 15:53 UTC · 14h agoResearch

A GAN-Based Framework for Robust DDoS Attack Detection

WGAN-GP-generated adversarial DDoS traffic augments training data, improving detection resilience against evasion attempts.

Researchers built a DDoS detection framework combining Random Forests, deep neural ensembles, and Transformer-based models trained on CICDDoS2019 with synthetic adversarial flows generated by a Wasserstein GAN with gradient penalty. Hybrid datasets of benign, malicious, and generated traffic taught models more generalizable decision boundaries. Experiments showed improved accuracy and resilience against unseen adversarial traffic, validated on real-world generated flows.

arXiv cs.CRSep 16, 08:04 UTC · 22h agoResearch

The modern attack chain: Rethinking Google Workspace security in the age of AI

Analysis of Vercel and Composio breaches shows stolen OAuth tokens, not phishing email, now open Google Workspace attacks — a path authorized AI agents follow.

The author analyzes the Vercel and Composio breaches as the same OAuth-first attack chain run twice: a stolen OAuth token, obtained via a compromised supplier, becomes the entry point rather than email. These tokens survive password resets, are hard to observe, and let attackers read Gmail and Drive data, take over accounts, and pivot laterally using stored credentials and password-reset magic links. The piece warns that authorized AI agents with overbroad OAuth grants can unintentionally traverse the same path — accessing inboxes, reading sensitive content, and exfiltrating data downstream — without any malicious actor or compromised credential.

Help Net SecuritySep 16, 05:00 UTC · 1d agoResearch in the wild

Building a Linux GPU Driver for the M4 Mac Mini in One Month

Two developers built a fully OpenGL ES 3.0 compliant Linux GPU driver for the M4 Mac Mini in one month via clean-room reverse engineering.

Niklas and the author reverse engineered Apple's AGX GPU firmware ABI and user-space components in about a month, a process that normally takes years, producing an OpenGL ES 3.0 conformant driver fast enough to run Minecraft at 200fps on an M4 Mac Mini. The work was done transparently using hypervisor traces without examining Apple binaries, following clean-room practices, and included a custom shader compiler, command stream builder, and a full Linux kernel driver for the firmware ABI. The A18 Pro firmware ABI proved significantly more complex than the M1's, with 1.5x as many structs and twice as many pointers. All experiments and provenance evidence were published in public agx-re repositories.

Hacker News · AISep 15, 19:30 UTC · 1d agoResearch HN 40↑ · 5 comments

SEMA-GUARD: Semantic and Graph-Based Vulnerability Detection in Assembly Code

SEMA-GUARD uses semantic analysis and graph neural networks to detect vulnerabilities in assembly code, achieving 85.1% accuracy on a Juliet-derived benchmark.

SEMA-GUARD is a framework that detects vulnerabilities in compiled programs when source code is unavailable, targeting malware, firmware, and embedded systems analysis. It enriches control flow graphs with low-level execution semantics including stack manipulations, memory accesses, and data flow. Evaluated on a Juliet Test Suite set compiled to assembly and split into function-level chunks, it achieves 85.1% accuracy and an F1 score of 0.801, outperforming purely statistical or structural approaches.

arXiv cs.CRSep 15, 14:35 UTC · 1d agoResearch1

From Hypervisor to Container: Cloud Security Vulnerabilities, Defense Mechanisms, and Open Challenges

Survey of 120+ cloud security papers (2008-2025) reviews hypervisor and container isolation attacks, scoring defenses with the ADPO framework and CIA impact scale.

This survey reviews over 120 security publications from 2008 to 2025 on breaches of cloud isolation boundaries via virtual machines and containers. Threats examined include VM escape, VM hopping, CPU cache side-channels, container breakouts, vulnerable container images, and DDoS attacks. The authors introduce ADPO, a 0-3 scoring framework rating defenses on accuracy, deployment ease, performance impact, and operational overhead, plus a 1-5 CIA severity mapping for attack impact.

arXiv cs.CRSep 15, 05:57 UTC · 2d agoResearch

Hackers Turn Windows Shadow Copies Into a Tool for Credential Theft and Ransomware

Attackers abuse Windows VSS shadow copies to delete recovery points before ransomware and to extract NTDS.dit/SAM credentials, demanding context-aware detection.

Threat actors are weaponizing the Volume Shadow Copy Service (VSS) for two purposes: destroying local recovery points via vssadmin.exe, wmic.exe, diskshadow.exe, wbadmin.exe, and bcdedit.exe before encryption, and accessing static copies of locked files such as NTDS.dit and SAM for credential theft. Ransomware families tied to shadow-copy removal include Akira, Black Basta, BlackCat, Conti, LockBit, Qilin, RansomHub, REvil, Ryuk, and WannaCry. Huntress's analysis of the Nightmare-Eclipse tool showed the BlueHammer technique chaining a Windows Defender timing issue with a VSS snapshot to dump the SAM database and decrypt NT hashes. Defenders should correlate VSS operations with parent process, hive access, and subsequent encryption activity, and maintain immutable off-host backups.

GBHackersSep 15, 05:51 UTC · 2d agoResearch in the wild1

The MAL Simulator: Cyber Operations Simulation based on Attack & Defense Graphs

MAL Simulator grounds attack-defense graph simulations in a CRATE-emulated network, training RL attacker and defender agents where attackers outperform search methods.

The MAL Simulator is a cyber operations simulator built on the Meta Attack Language (MAL), enabling decision-driven attack and defense simulations adaptable to new domains without modifying source code. Case studies trained defensive and offensive agents, grounded in data collected from an emulated network implemented in the CRATE cyber range. The trained attacker policy reached designated targets more efficiently than compared search methods, and the trained defender induced lower costs than a naive heuristic under noisy alerts, though defender performance dropped significantly against an RL attacker.

arXiv cs.CRSep 15, 02:59 UTC · 2d agoResearch

A Cyber Range Evaluation of Autonomous Network Incident Response Agents

Cyber range evaluation shows reinforcement learning incident response agents defend emulated networks more efficiently than heuristic policies, depending heavily on adversary behavior.

The paper evaluates agents for automated network intrusion response in a cyber range designed for human operator training, featuring variable topology, red-team emulation, and simulated users. Alerts are generated by a SIEM platform and mapped to a data modeling language used by the agents, with reinforcement learning policies optimized to minimize combined defense and availability costs using a cyber attack simulator. Reinforcement learning agents defended the system more efficiently than heuristic policies, with performance highly dependent on the adversary policy and simulated user behavior.

arXiv cs.CRSep 15, 02:36 UTC · 2d agoResearch

Evaluating the NIST Bugs Framework Against CWE as a Successor for Automated Vulnerability Classification

NIST Bugs Framework evaluation shows it is more structured and automation-friendly than CWE for automated vulnerability classification, with gaps in attribute guidance.

The paper evaluates NIST SP 800-231's Bugs Framework (BF) against CWE as a target for automated CVE classification using a systematically screened corpus of CVE-to-CWE research. An inter-rater study with 2 subject-matter experts mapping 13 CVEs showed strong agreement on BF's cause and operation axes but only fair agreement on the attribute axis. Automated classification was tested across two LLM deployments under different budgets, and findings support BF as more structured and automation-friendly than CWE, though gaps include under-specified attribute guidance and missing fix commits for closed-source software.

arXiv cs.CRSep 14, 23:18 UTC · 2d agoResearch1

gr-PHYSEC: Real-time Channel-based Key Generation for Physical Layer Secure Wireless Communications

gr-PHYSEC GNU Radio module derives symmetric encryption keys from wireless channel randomness using a neural network, validated on robotic platforms with ADALM-Pluto SDRs.

The paper introduces gr-PHYSEC, a GNU Radio out-of-tree module for real-time physical-layer key generation that derives symmetric keys from the wireless channel's inherent randomness instead of pre-shared secrets. A trained neural network extracts channel features between trusted parties during probe exchanges; features are quantized into binary keys, reconciled via Reed-Solomon encoding, and secured with SHA-512 hashing before direct use for encryption. Real-world experiments at the FAU CAAI connected robotics testbed using ADALM Pluto software-defined radios and NVIDIA Jetson Orin demonstrated low key disagreement rates and NIST-verified randomness. Source code is publicly available on GitHub.

arXiv cs.CRSep 14, 21:37 UTC · 2d agoResearch

New hardware device can RAM into encrypted memory, expose your data

Researchers built a $200 DDR5 interposer that silently drops memory writes to break TDX, SGX, and SEV-SNP confidential VM integrity, requiring physical access.

Researchers from KU Leuven, ETH Zurich, Durham University, and Google demonstrated DDRop, a hardware interposer costing under $200 that corrupts DDR5 bus commands to silently drop writes to encrypted memory, enabling replay attacks on confidential VMs. Because scalable memory encryption lacks freshness checks, protected VMs keep computing on stale attacker-selected data; on an Intel TDX server the attack forces debug mode for plaintext memory reads or forges attestation reports, succeeding in under two minutes without crashing. Intel and AMD both called the attack out of scope for their cloud threat models, with no mitigation planned, and proposed cache line versioning appears still vulnerable. The full interposer design is being released as open-source hardware.

The Register · SecuritySep 14, 18:31 UTC · 2d agoResearch

New DDRop Attack Breaks Intel TDX and AMD SEV-SNP Confidential Computing

DDRop uses a sub-$200 DDR5 interposer to drop memory writes, breaking Intel TDX and AMD SEV-SNP confidentiality guarantees.

Researchers at KU Leuven, ETH Zurich, Durham University, and Google will present DDRop at ACM CCS 2026, a first active interposer attack on DDR5 that silently drops memory writes so processors keep reading stale encrypted data, exploiting the missing freshness guarantee in Intel TDX, Intel Scalable SGX, and AMD SEV-SNP. On Intel TDX's default logical integrity mode it enabled reading victim VM memory, toggling debug mode, and forging remote attestation; AMD SEV-SNP was limited to copying pages between VMs. TDX's stronger cryptographic integrity blocks cross-VM attacks but likely not attestation forgery. The team will release board designs, firmware, and attack code on GitHub; no evidence of real-world use exists and no simple patch is available.

The Hacker Newsupdated Sep 15, 09:57 UTC · 1d agofirst Sep 14, 16:58 UTC · 2d agoResearch 2 sources

Batten the Hatches: Cybersecurity with Military Mariners

Interviews with 20 U.S. Navy and Coast Guard mariners reveal informal, safety-oriented shipboard cyber risk models that may delay attribution and containment.

The study conducts semi-structured interviews with 20 military mariners from U.S. Navy and Coast Guard vessels to understand how service members recognize and respond to cyber risk aboard ships. Unique consequences of compromising military systems identified include weapon takeover and purposeful geopolitical escalation. Cybersecurity is organizationally abstract on ships, so mariners build cyber risk models from informal experience rather than formal instruction. A safety-oriented incident-response model creates resilience but may delay cyber attribution and containment.

arXiv cs.CRSep 11, 13:04 UTC · 5d agoResearch

MicroHasTEE: Bare-Metal Haskell for Type-Level Peripheral Ownership on Armv8-M

MicroHasTEE expresses TrustZone secure and non-secure firmware as one typed Haskell program, catching peripheral-ownership inconsistencies at compile time.

MicroHasTEE is a multiparty Haskell framework that models both TrustZone firmware images as participants in a single typed program, using type-level capability ledgers to track peripheral acquisition, configuration, transfer, and finalization. MicroHs compiles the shared program twice to produce separate bare-metal Secure and Non-secure firmware images. The framework rejects inconsistent resource use, post-configuration attribution changes, wrong-domain callbacks, and calls to unregistered Secure services. A door-lock case study on an STM32U5 Nucleo board produced images of 232.7 KiB and 228.4 KiB of flash with roughly 220 KiB of SRAM per domain.

arXiv cs.CRSep 11, 08:34 UTC · 5d agoResearch1

Function Name Is All You Need to Detect Blockchain Application Attacks

TxLucent detects blockchain dApp attacks from transaction function-name sequences using a transformer, achieving 1.56% false negatives without source code.

Researchers propose TxLucent, which maps transaction call traces to function name sequences and uses a transformer to detect blockchain application attacks without source code or handcrafted rules. Evaluated on 424 real-world incidents with 14,611 attack transactions, it achieves a 1.56% false negative rate and an estimated 0.0017% false positive rate across over 500 million Ethereum transactions. Average analysis time of 24.90 milliseconds supports real-time detection on popular blockchains.

arXiv cs.CRSep 11, 00:43 UTC · 6d agoResearch1

BlueSTAR: Tiered Agentic Architecture for Autonomous Cyber Defense

BlueSTAR is a tiered agentic LLM architecture for autonomous cyber defense, validated on live enterprise IT/OT cyber ranges against seven attack chains.

Researchers present BlueSTAR, a tiered agentic architecture for autonomous cyber defense in enterprise IT/OT networks that transforms high-volume security telemetry into compact indicators of compromise. It pairs deterministic containment for known threats with LLM reasoning for attacks requiring contextual and cross-cycle analysis, and introduces a resilience metric jointly weighing attacker reach, mission-critical impact, and defensive disruption. Evaluation on two live cyber ranges with seven attack chains based on real-world intrusion techniques covered credential theft, repeated compromise, concurrent attackers, and attacks on physical processes.

arXiv cs.CRSep 10, 17:36 UTC · 6d agoResearch

Credential Theft: How Attackers Steal & Use Stolen Credentials

Huntress explains how attackers steal credentials through phishing, AitM, infostealers, and dumping, then use them for lateral movement, BEC, and ransomware.

Huntress published an educational overview of credential theft, citing that roughly 70% of confirmed data breaches begin with stolen credentials. It details acquisition methods including phishing, adversary-in-the-middle attacks that capture MFA session tokens, infostealers (nearly a quarter of threats Huntress observed in 2025), Mimikatz-based credential dumping, credential stuffing, and password spraying. The piece then covers post-theft actions such as lateral movement, privilege escalation, account takeover, business email compromise, and ransomware, and closes with behavioral detection guidance and layered prevention strategies.

HuntressSep 10, 16:00 UTC · 6d agoResearch

CHERI-D Reincarnate: efficient multicore CHERI temporal memory safety through allocation reincarnation (draft version)

CHERI-D Reincarnate adds allocation reincarnation to CHERI, quarantining generation IDs instead of memory to cut temporal memory-safety overheads on multicore systems.

The proposal extends CHERI-D temporal memory safety by quarantining exhausted generation IDs rather than memory slots, allowing freed memory immediate reuse through allocation reincarnation. It adds coherent ID caching and multicore support connecting physical coherence events to the virtually addressed ObjID buffer. The design was implemented as a hardware-software co-design across CHERI-Toooba FPGA softcore, QEMU, LLVM/Clang, and CheriBSD. Across evaluated workloads it substantially reduces memory-sweep frequency and quarantine overhead with low performance and hardware cost.

arXiv cs.CRSep 10, 14:19 UTC · 6d agoResearch

Few-Shot Learning for Network Intrusion Detection: Methods, Datasets, and Performance

A PRISMA-style review of 21 few-shot learning studies for network intrusion detection finds meta-learning and CNNs dominant and evaluation inconsistently reported.

The systematic review screened 1,358 records from ACM Digital Library, IEEE Xplore, and Scopus covering 2022-2026 and retained 21 studies on few-shot learning for network intrusion detection. Meta-learning (8 studies) and convolutional neural networks (10) are the most common approaches, while CIC-IDS2017 and CSE-CIC-IDS2018 are the most frequently used datasets. Most evaluations use five or fewer samples per class, and missing parameters and source code limit reproducibility and direct comparison.

arXiv cs.CRSep 10, 09:07 UTC · 6d agoResearch1

You've Got a BUD in Me: Authenticated Reads from Per-Block Write Logs

Researchers propose BUD, per-block write-log digests enabling blockchain validators to serve historical membership and exclusion proofs far cheaper than state-wide tries.

The paper introduces Block Update Digests (BUD), which authenticate each block's write log with predecessor pointers, plus a SuperBUD and exponential hierarchy to turn long unchanged intervals into short proofs. Soundness against adversarial provers and up to f Byzantine validators is proven under archive, attestation, and committee evidence assumptions. Benchmarks show a 50x state-size increase raises the base-BUD path only 1.24x versus 3.1x for in-memory and 69.5x for disk-backed Merkle Patricia tries, with read payloads below 800 bytes and p99 warm verification at 146 microseconds.

arXiv cs.CRSep 10, 08:46 UTC · 6d agoResearch

Domain-Incremental Learning for Multi-Channel Replay Speech Detection

First continual learning benchmark for multi-channel replay speech detection shows task-specific beamforming cuts catastrophic forgetting across 24 acoustic environments.

Researchers frame replay-attack detection for voice-controlled systems as domain-incremental learning over acoustic environments, evaluating a beamformer-based detector across all 24 environment orderings of the ReMASC corpus with five seeds. Naive sequential fine-tuning raises error rates on previously learned environments by 18.8 points, while elastic weight consolidation halves forgetting but loses plasticity and gradient projection memory is statistically indistinguishable from naive fine-tuning. A task-specific beamformer keeping one spatial front-end per environment significantly improves final and incremental accuracy, and the last environment in a sequence dominates final performance.

arXiv cs.CRSep 10, 08:03 UTC · 6d agoResearch1

An Empirical Analysis of ReDoS Vulnerabilities and ReDoS Detection Tools

Study of NVD data finds ReDoS vulnerabilities growing more prevalent and more likely to be exploited, while five detection tools disagree substantially.

The study compares five publicly available ReDoS detection tools and one regex correction tool across three datasets. An empirical analysis of all ReDoS vulnerabilities reported to the NVD finds they are becoming more prevalent and are much more likely to be exploited than non-ReDoS weaknesses. The detection tools exhibited substantial disagreement on whether a given regex is vulnerable.

arXiv cs.CRSep 9, 15:09 UTC · 7d agoResearch

AD Rights Management Service (Part 1): Architecture, Deprecation, and Reconnaissance

Huntress maps AD RMS architecture and recon paths, setting up an offline key-extraction attack against its unrotatable 255-year root key.

Huntress's multi-part research examines Active Directory Rights Management Services, Microsoft's enterprise DRM role that still ships in Windows Server 2025 despite migration guidance favoring Azure Information Protection. Part 1 covers the trust model and how an ordinary domain account can locate RMS clusters and read rights-policy templates. Part 2 will detail four independent paths for extracting the Server Licensor Certificate (SLC) private key via service-group membership and the configuration database, enabling fully offline decryption of protected documents. The SLC certificate is valid from 2002 to 2258 and has no key-rotation mechanism, so a stolen key decrypts protected content indefinitely.

HuntressSep 8, 04:00 UTC · 9d agoResearch1

DRIFT: Removing Diffusion Watermarks by Deflecting the Generative Trajectory

Introduces DRIFT, a black-box attack removing diffusion watermarks by deflecting generative trajectories, achieving 98-100% success across nine watermarking schemes.

Researchers propose DRIFT, a black-box watermark removal attack combining partial forward diffusion with stochastic reverse resampling to break trajectory-dependent verification. The paper derives information-theoretic and Wasserstein source-dependence bounds and shows the first verifier-rejected rung is least distorted among rejected rungs. Across nine watermarks spanning three paradigms, DRIFT achieves 98-100% attack success with the best image quality among compared attacks, without secret keys, verifier internals, or per-image gradient optimization.

arXiv cs.CRSep 8, 03:54 UTC · 9d agoResearch

Your Cloud Security Checklist Doesn't Work the Way You Think It Does

Intruder's 2026 Cloud Security Index found misconfiguration risk profiles differ sharply across AWS, Azure, and Google Cloud across 3,000 organizations.

Intruder analyzed misconfiguration data from 3,000 organizations across AWS, Azure, and Google Cloud for its 2026 Cloud Security Index. Weak IAM controls and missing logging affected 80-98% of accounts regardless of provider, while exposed services ranged from 76% on AWS to just 8% on Google Cloud. Top issues included S3 buckets without HTTPS enforcement (87% of AWS accounts), Entra ID users without MFA (55% of Azure accounts), and missing OS Login MFA (77% of Google Cloud accounts). Weak IAM prevalence rose with organization size, from 87% at SMEs to 98% at large enterprises, and midmarket organizations took the longest to remediate at 35 days on average.

The Hacker NewsSep 7, 11:45 UTC · 9d agoResearch

Has anybody seen my keys? A key-hierarchy strategy for rack-level security

Oxide's RFD 0301 proposes a rack-level key hierarchy using Shamir secret sharing and a trust quorum to protect data-at-rest keys.

Oxide's request for discussion (RFD 0301) lays out a key-hierarchy strategy for rack-level security, deriving keys from a rack secret protected by Shamir secret sharing across a trust quorum of sleds, with keys exchanged over authenticated sprockets sessions. The document maps which keys protect control-plane data, metrics, Crucible extents, and authentication tokens, and defines open questions on key lifecycle, locality, and compromise handling. Future work includes sealing shares with the root of trust so an attacker would need to steal K whole sleds to reconstruct the rack secret.

Hacker News · securitySep 7, 02:14 UTC · 10d agoResearch HN 52↑ · 3 comments

Security Vulnerability in a Voting System

A four-year-old vulnerability letting anyone recover ballot casting order was demonstrated with AI coding agents against Georgia's May 2026 primary data.

A previously disclosed vulnerability in ballot scanners used across 21 US states, including Georgia, allows recovery of the order in which ballots were cast. Nearly four years after the original disclosure, a researcher pointed AI coding agents at the vulnerability paper and used only public data — county early-voting lists and cast-vote record (CVR) files — to analyze voter behavior in Georgia's May 2026 primary. The demonstration required no access to voting machines, networks, source code, or non-public records.

Schneier on SecuritySep 4, 11:09 UTC · 12d agoResearch in the wild

Cost-Aware Hierarchical Multi-Agent Ransomware Detection and Family Attribution

Researchers propose a hierarchical multi-agent system that cuts ransomware analysis cost by 44% while reaching 96.57% detection accuracy.

An arXiv paper (2609.04820) presents a Cost-Aware Hierarchical Multi-Agent System (HMAS) for adaptive ransomware detection and family attribution. Specialized agents run static analysis first, with dynamic and memory modalities invoked only when confidence is insufficient or specialists disagree; a Meta Orchestrator balances accuracy against computational cost via a cost model, and a locally deployed LLM verifies difficult cases. The system achieved 96.57% accuracy, 0.96 F1-score, and 0.99 ROC-AUC for binary detection, and 0.90 macro-F1 for multiclass family attribution. Average analysis cost dropped 43.97% versus exhaustive analysis, with 56.05% of cases resolved using static evidence alone.

arXiv cs.CRSep 4, 07:17 UTC · 12d agoResearch