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SPIDER4TianoCore is a Python command-line tool designed to enhance patch-status evidence reporting within the TianoCore/UEFI firmware supply chain, providing insights into the integration-stage status of patches. The tool categorizes patches as Vulnerable, Already Patched, Not Applicable, or Uncertain, based on upstream pre-patch and post-patch comparisons against prepared downstream targets. Evaluation on 20 target/CVE pairs reveals that the tool generates high-confidence matches without misclassifications, showcasing its potential for reliable evidence generation in firmware development.
SPIDER4TianoCore achieves high-confidence patch-status classification without a single misclassification, setting a new standard for evidence generation in firmware development.
We propose and demonstrate SPIDER4TianoCore, a packaged Python command-line tool that provides integration-stage patch-status evidence for the TianoCore/UEFI firmware supply chain. Given an upstream pre-patch and post-patch pair and prepared downstream targets, the tool reports Vulnerable, Already Patched, Not Applicable, or Uncertain with supporting evidence for maintainer review. Our work is inspired by SPIDER's patch-propagation framing, but SPIDER4TianoCore does not itself prove that a patch is safe to propagate. We evaluate the engine on 20 prepared target/CVE pairs from eight public downstream EDK II repositories and two CVEs. The analyzers produce 10 high-confidence pre-patch matches and four high-confidence post-patch matches, conservatively abstain on six targets, and make no confidently wrong classifications relative to the recorded manual patch-state labels. These preliminary results demonstrate reproducible evidence generation for prepared targets rather than general downstream accuracy.
