The Impact of Magma: A Ground-Truth Fuzzing Benchmark

Magma is an open-source and ground-truth fuzzing benchmark that enables uniform fuzzer evaluation and comparison. Magma was originally released with a research paper published at ACM SIGMETRICS 2021. This short paper explains the motivation, the design, and the impact of Magma, with a description...

LongPIBench: A Long-Context Benchmark for Prompt Injection

Prompt injection attacks pose a serious security risk to large language models in real-world applications. However, existing prompt injection benchmarks primarily focus on short-context inputs, leaving the attacks and defenses in long-context settings largely unexplored. This gap leads to a...

FuzzingBrain-Bench V1: Evaluating Open-Ended Bug Discovery by LLMs

Evaluating the ability of large language models LLMs to discover software bugs is increasingly important. Existing benchmarks typically evaluate this capability by asking the model to generate a proof-of-concept input that triggers a predefined target vulnerability. However, this setup may overlo...

MMJailBench: A Factorized Benchmark for Disentangling Multimodal Jailbreak Vulnerabilities

Multimodal Large Language Models MLLMs are increasingly deployed in real-world applications, yet how different factors shape their jailbreak vulnerabilities remains poorly understood. Existing benchmarks often couple harmful intent, prompt framing, visual semantics, and instruction carrier within...

The Surprising Effectiveness of LLMs in BGP Security: Mining an Unprecedented Amount of Incidents and Boosting Anomaly Detection

Border Gateway Protocol BGP security is critical to Internet infrastructure, yet progress in routing anomaly detection has been limited by the scarcity of publicly available incident datasets, which contain only 18 recorded cases. We observe that public operator mailing lists, e.g., NANOG and...

Robustness of Anomaly Detection Models for Industrial Control Systems under Training-Time Data Contamination

Machine-learning-based anomaly detection is increasingly used in industrial control systems ICS, yet most studies assume that detector training data is trustworthy. In practice, training data may be corrupted through compromised logs, labeling errors, manipulated historian records, or unsafe...

CVE-2026-18287 Aeon load_time_series_segmentation_benchmark Code Injection Remote Code Execution Vulnerability

Aeon loadtimeseriessegmentationbenchmark Code Injection Remote Code Execution Vulnerability. This vulnerability allows remote attackers to execute arbitrary code on affected installations of aeon. User interaction is required to exploit this vulnerability in that the target must visit a malicious...

MaliciousSkillBench: A Comprehensive Benchmark for Malicious Agent Skill Detection

Agent Skills extend LLM agents with reusable instruction packages that may also include scripts, resources, and service configuration. This creates a direct distribution channel for malicious behavior, yet existing malicious-Skill datasets are fragmented across sources, artifact formats, evidence...

CVE-2026-71694

An issue in Berkeley Out-of-Order Machine BOOM / BoomTile RTL benchmark v1.2 2d08d0d8b4563212175212f9db0e69f6e68c9619 allows a remote attacker to execute arbitrary code via the CSR trap-return state restoration logic, MRET handling logic, mstatus.MPRV update path, CSRFile logic in ProcessorFuzz...

CVE-2026-71694

An issue in Berkeley Out-of-Order Machine BOOM / BoomTile RTL benchmark v1.2 2d08d0d8b4563212175212f9db0e69f6e68c9619 allows a remote attacker to execute arbitrary code via the CSR trap-return state restoration logic, MRET handling logic, mstatus.MPRV update path, CSRFile logic in ProcessorFuzz...

CVE-2026-71694: Cross-Site Request Forgery (CSRF)

An issue in Berkeley Out-of-Order Machine BOOM / BoomTile RTL benchmark v1.2 2d08d0d8b4563212175212f9db0e69f6e68c9619 allows a remote attacker to execute arbitrary code via the CSR trap-return state restoration logic, MRET handling logic, mstatus.MPRV update path, CSRFile logic in ProcessorFuzz...

EUVD-2026-62483

An issue in Berkeley Out-of-Order Machine BOOM / BoomTile RTL benchmark v1.2 2d08d0d8b4563212175212f9db0e69f6e68c9619 allows a remote attacker to execute arbitrary code via the CSR trap-return state restoration logic, MRET handling logic, mstatus.MPRV update path, CSRFile logic in ProcessorFuzz...

PT-2026-78381

Name of the Vulnerable Software and Affected Versions Berkeley Out-of-Order Machine BOOM / BoomTile RTL benchmark version 1.2 Description A flaw in the CSR trap-return state restoration logic, MRET handling logic, mstatus.MPRV update path, and CSRFile logic within the...

LLMs and Contextual Integrity

I have been thinking a lot about AI and integrity. Part of that is contextual integrity. I recently found two papers on the topic. "CIMemories: A Compositional Benchmark for Contextual Integrity of Persistent Memory in LLMs": Abstract: Large Language Models LLMs increasingly use persistent memory...

MobileWorldSafety: Benchmarking GUI Agent Safety against Environmental Injection Attacks in Android Apps

LLM-powered GUI agents that autonomously operate smartphones are rapidly transitioning from research prototypes to early real-world deployment. However, because these agents routinely process untrusted environmental content, they are highly vulnerable to environmental injection attacks, which...

Benchmarking Identity-Sensitive LLM Outputs for Surveillance and Security Robots

Large language models LLMs are increasingly used to generate textual robot design specifications, interaction policies, and risk assessments during early-stage robot development. Such outputs may influence how surveillance and security robots are conceptualized, documented, and ultimately...

WeSCE: A Benchmark for Measuring Security Drift in LLM-Driven Code Editing

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...

GO-2026-5039 vulnerabilities

Vulnerabilities for packages: omnibump, crossplane-provider-aws-memorydb, kubernetes-replicator, gitlab-runner, hcloud, argocd-image-updater, emissary, opentofu, tekton-pipelines, apache-exporter, cert-manager-webhook-pdns, ksops, paranoia, gostatsd, sops, cluster-api-helm-controller,...

GO-2026-5013 vulnerabilities

Vulnerabilities for packages: k8sgpt, crossplane-provider-aws-memorydb, falcoctl, gitlab-runner, hcloud, argocd-image-updater, opentofu, ksops, sops, act, guac, aactl, crossplane-provider-aws-eks, buildah, tkn, gitea, trivy, crossplane-provider-aws-cloudfront, wal-g, argo-events, kargo, ko,...

GO-2026-4340 vulnerabilities

Vulnerabilities for packages: kubernetes-replicator, gitlab-runner, opentofu, apache-exporter, ksops, paranoia, k8sgateway, gostatsd, sops, azure-workload-identity-webhook, ferretdb, redis-operator, ratify, guac, chart-testing, kubescape-operator, kuma, kubeflow-pipelines, tetragon, amass,...