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HAVE: Host Active Verification Engine for Closing the Contextual Reality Gap in Security Digital Twins

arXiv Security Archived Jun 08, 2026 ✓ Full text saved

arXiv:2606.06968v1 Announce Type: new Abstract: Security Digital Twins (SDTs) provide continuously updated virtual replicas of infrastructure for threat simulation, yet they rely on theoretical CVSS scores to assign lateral-movement probabilities -- creating the Contextual Reality Gap: risk is overestimated where unacknowledged mitigations neutralize exploits, and drastically underestimated where logic flaws bypass all memory-safety defenses. We present the Host Active Verification Engine (HAVE)

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    Computer Science > Cryptography and Security [Submitted on 5 Jun 2026] HAVE: Host Active Verification Engine for Closing the Contextual Reality Gap in Security Digital Twins Vincenzo Sammartino, Marco Pasquini Security Digital Twins (SDTs) provide continuously updated virtual replicas of infrastructure for threat simulation, yet they rely on theoretical CVSS scores to assign lateral-movement probabilities -- creating the Contextual Reality Gap: risk is overestimated where unacknowledged mitigations neutralize exploits, and drastically underestimated where logic flaws bypass all memory-safety defenses. We present the Host Active Verification Engine (HAVE), an SDT extension that deploys a safety-constrained host agent to measure the empirical probability of compromise \hat{p} via maximum-likelihood estimation over snapshot-isolated Bernoulli trials. A Wilson interval-width confidence weight \alpha_w propagates \hat{p} into Monte Carlo simulations via a Bayesian blending rule formally related to the Beta-Binomial posterior. Evaluation across four vulnerability classes, three security tiers, and two production binaries shows HAVE reduces P_{\text{reach}} by 38.2% in false-positive scenarios and increases it by 132.4% in false-negative scenarios, with a net +124.1% correction; post-HAVE estimates vary by only 1.12\times across calibration exponents \kappa, versus 4.6\times for CVSS-only baselines. Comments: This work has been submitted to the IEEE for possible publication Subjects: Cryptography and Security (cs.CR) Cite as: arXiv:2606.06968 [cs.CR]   (or arXiv:2606.06968v1 [cs.CR] for this version)   https://doi.org/10.48550/arXiv.2606.06968 Focus to learn more Submission history From: Vincenzo Sammartino [view email] [v1] Fri, 5 Jun 2026 06:54:23 UTC (102 KB) Access Paper: view license Current browse context: cs.CR < prev   |   next > new | recent | 2026-06 Change to browse by: cs References & Citations NASA ADS Google Scholar Semantic Scholar Export BibTeX Citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Demos Related Papers About arXivLabs Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)
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    arXiv Security
    Category
    ◬ AI & Machine Learning
    Published
    Jun 08, 2026
    Archived
    Jun 08, 2026
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