CVE-2026-100653

vLLM is an inference and serving engine for large language models. In versions from 0.22.1 through 0.28.0, the operator-supplied model revision pin --revision / --code-revision is not propagated to several Hugging Face artifact loads for the FunAudioChat and Tarsier2 architectures: the...

EUVD-2026-87747

vLLM is an inference and serving engine for large language models. In versions from 0.22.1 through 0.28.0, the operator-supplied model revision pin --revision / --code-revision is not propagated to several Hugging Face artifact loads for the FunAudioChat and Tarsier2 architectures: the...

CVE-2026-100653

vLLM is an inference and serving engine for large language models. In versions from 0.22.1 through 0.28.0, the operator-supplied model revision pin --revision / --code-revision is not propagated to several Hugging Face artifact loads for the FunAudioChat and Tarsier2 architectures: the...

CVE-2026-100653 vLLM 0.22.1 before 0.28.0 Incomplete Artifact Pin Propagation

vLLM is an inference and serving engine for large language models. In versions from 0.22.1 through 0.28.0, the operator-supplied model revision pin --revision / --code-revision is not propagated to several Hugging Face artifact loads for the FunAudioChat and Tarsier2 architectures: the...

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

Anomaly-based network intrusion detection systems NIDS are an important first line of defense. However, training NIDS for new attack types is challenging, because labeled attack data are rarely available. Few-shot learning FSL addresses this problem by learning from few samples. However, the...

Practice Makes (Im)Perfect: A Look Back at Benchmarking Practices for Microarchitectural Side-Channel Attacks

Microarchitectural side-channel research has grown at an exceptional pace in recent years, increasing the need for rigorous and meaningful benchmarking. Early attack papers typically relied on indirect proxies, such as covert-channel bandwidth or key-recovery on naive AES and RSA implementations,...

ICS Cybersecurity Datasets: A Systematic Meta-Review of Coverage, Evaluation Practice, and Structural Gaps

Intrusion detection research in Industrial Control Systems ICS heavily depends on public datasets, yet no prior work has systematically assessed whether the collective dataset corpus supports current evaluation claims. This paper addresses this gap through a meta-review of 18 studies between 2019...

CVE-2026-12261

A flaw was found in the nltk.downloader component of NLTK. This vulnerability allows for cross-package resource and model poisoning. The downloader extracts package archives into shared namespaces and only validates package integrity after extraction. This design flaw enables one package to...

A Controlled Candidate-Set Benchmark for Offline Satellite-Security Plan Decomposition

Some security-development settings require local models that map an objective to an ordered, checkable plan. We present a low-rank decomposition adapter and release a case-disjoint corpus with 24 authored decompositions and 83 derived next-step examples across 24 satellite-security cases. To...

Know Your Agent: Reconnaissance-Driven Pentesting of AI Agents

Traditional pentesting uses reconnaissance at each step to uncover unseen weaknesses, build stronger attacks, and advance the objective; we argue that AI agents require the same treatment. We formalize agent reconnaissance by modeling the process and identifying the knowledge assets it seeks to...

Understanding Build Reproducibility in the F-Droid Ecosystem

The security of open source applications benefits considerably from the possibility of rebuilding their source and verifying the output. F-Droid, a prominent distribution for open source Android applications, systematically rebuilds them from source and tests their bitwise reproducibility at app...

Revisiting Vul-RAG: Reproducibility and Replicability of RAG-Based Vulnerability Detection with Open-Weight Models

Large language models LLMs have shown strong potential for automated software vulnerability detection, particularly in retrieval-augmented generation RAG settings. However, for approaches relying on proprietary models and APIs, reproducibility and replicability remain largely unexplored, raising...

Domain-Conditioned Safety in Frontier Computer-Using Agents: A 793-Episode Browser Benchmark, a Coding-Domain Cross-Reference, and a Reproducibility Audit of Recent Red-Teaming

Recent computer-using-agent CUA red-teaming papers report prompt-injection attack success rates ASR of 42-98%, but these headline numbers cluster on retired models and on the most-vulnerable model in each paper's panel. We ask whether those techniques, reproduced as hand-crafted templates, still...

XSSaudit

XSSAudit v2.0 — Advanced XSS Vulnerability Scanner For au...

MAL-2026-4739 Malicious code in zkjson (npm)

--- -= Per source details. Do not edit below this line.=- Source: amazon-inspector 758a19e42db66cf6ae7a08d462278b30e3a154b56613d2d95f8020de3add3816 package.json declares "preinstall": "./.github/scripts/precheck", pointing to a 976 KB Linux ELF executable sha256...

Context-Aware Entity-Relation Extraction for Threat Intelligence Knowledge Graphs

Cybersecurity Knowledge Graphs CKGs unify diverse Cyber Threat Intelligence CTI sources into structured, queryable formats, offering scalable solutions for automating proactive and real-time security responses. Their increasing adoption has significantly enhanced the workflow and decision-making...

From Controlled to the Wild: Evaluation of Pentesting Agents for the Real-World

AI pentesting agents are increasingly credible as offensive security systems, but current benchmarks still provide limited guidance on which will perform best in real-world targets. Existing evaluation protocols assess and optimize for predefined goals such as capture-the-flag, remote code...

Iterative Audit Convergence in LLM-Managed Multi-Agent Systems: A Case Study in Prompt Engineering Quality Assurance

Prompt specifications for multi-agent large language model LLM systems carry data contracts and integration logic across many interdependent files but are rarely subjected to structured-inspection rigor. This paper reports a single-system empirical case study of iterative, agent-driven auditing...

SNF - Shadow Network Fingerprinting Engine

SNF Shadow Network Fingerprinting Engine is a 100% offline, air-gap-native passive network intelligence engine written entirely in Rust. It was designed from the ground up for environments where outbound connectivity is not just unavailable but prohibited: classified defense networks, nuclear...

Supporting Artifact Evaluation with LLMs: A Study with Published Security Research Papers

Artifact Evaluation AE is essential for ensuring the transparency and reliability of research, closing the gap between exploratory work and real-world deployment is particularly important in cybersecurity, particularly in IoT and CPSs, where large-scale, heterogeneous, and privacy-sensitive data...