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VOE9/README.md

Independent security researcher.

I build small, focused tools that help human researchers triage faster — heuristic or structurally-grounded, and honest about their own false positives. No model in the loop for detection, so nothing here can hallucinate a finding: every output traces back to a real commit, diff, git history, or published record a human can click and verify.

Status: all tools below are early-stage and independently developed. Read each one's METHODOLOGY.md before trusting a result — every one of them documents real bugs found during its own development, not just the happy path.


Tools

augur — three sections: radar flags commits in a local git clone that look like undisclosed security fixes; harness attempts an automatic differential AddressSanitizer proof for a real bug shape, deriving its own test input mechanically from the target function's source; provenance finds when a vulnerable pattern was actually introduced (structurally, not "last commit that touched the line" like classic SZZ) and maps it to the real tagged versions affected. Validated against a real, external repository's actual merged fix, independently re-checked by hand — see its METHODOLOGY.md.

cve-explain — turns a CVE ID into a plain-language explanation grounded entirely in NVD, EPSS, and GHSA data — including the actual fix commit's diff, when one is linked. Optionally re-derives the affected-version range from the fix repo's real git history via augur's provenance module, instead of trusting NVD's version field for the narrow class of fixes it can independently check.

regression-hunter — variant analysis: finds candidate files that may not have received a project's own previously-published security fix, seeded from that project's real advisory history.

silent-patch-finder — scans commit history for undisclosed security fixes: a defensive-shaped diff paired with a commit message that doesn't say so.


Selected upstream contributions

Small, verified fixes found by reading real projects' code and confirming the bug empirically before proposing anything — not by scanning at scale.


Every tool here produces candidates for manual review, never verdicts. Verification, judgment, and the actual report stay a human's job — on purpose.


Applying for a research-focused CS master's, Fall 2027 — interested in vulnerability discovery & security patch analysis.

Pinned Loading

  1. cve-explain cve-explain Public

    Turns a CVE ID into a plain-language explanation grounded in NVD data (description, CWE, CVSS, affected versions, references, CISA KEV status).

    Python

  2. regression-hunter regression-hunter Public

    Finds candidate sibling-code locations that may not have received a projects own previously-fixed security check (variant analysis, for human review).

    Python

  3. silent-patch-finder silent-patch-finder Public

    Scans a repo's recent commit history for commits that look like an undisclosed ("silent") security fix.

    Python

  4. augur augur Public

    Reads the signs in a project's commit history: flags likely undisclosed security fixes, and where possible, proves them with an automatic differential ASan harness.

    Python