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A Large-Scale Multi-Source Dataset Linking Hacker Community Discourse to the CVE Vulnerability Lifecycle

NeurIPS 2026 · Label-efficient and robust learning › Recognition and long-tail · approach: Dense features and foundation priors

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Introduces HackerSignal, a 7.45M-document multi-source CTI corpus linking hacker-forum discourse, exploit archives, advisories and fix commits via CVE IDs, with three temporal benchmark tasks and a baseline ladder.

Problem

Public datasets rarely link hacker-community discourse to the CVE vulnerability lifecycle (exploit, advisory, fix), and existing CTI benchmarks lack temporal OOD splits and provenance governance.

Approach

A governed, temporally split multi-source corpus unified by a shared CVE identifier space, with three benchmark tasks (CVE linkage retrieval, 8-class exploit type classification, CVE-disjoint temporal generalization) and a heterogeneous baseline ladder plus leakage and audit diagnostics.

Key results

Surprising findings

Limitations

Experimental setup

Datasets: NVD ExploitDB 0day.today Packet Storm GitHub Advisory CISA KEV HackerOne CVEfixes Gayanku HackForums DeepDarkCTI CrackingArena

Benchmarks: HackerSignal CVE-R HackerSignal ETC HackerSignal TG

Metrics: Recall@1 Recall@5 Recall@10 MRR macro-F1 per-class F1

Baselines: BM25 MiniLM-L6-v2 all-mpnet-base-v2 BGE-base-v1.5 E5-base-v2 Hybrid BM25+mpnet Decision Tree TF-IDF+LR SVM RNN GRU LSTM

Builds on: BEIR WILDS WRENCH KILT CVEfixes

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