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90 lines
4.6 KiB
Markdown
90 lines
4.6 KiB
Markdown
# Determinism Benchmark (cross-scanner) — Stable (2025-11)
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Source: advisory “23-Nov-2025 - Benchmarking Determinism in Vulnerability Scoring”. This doc captures the runnable harness pattern and expected outputs for task BENCH-DETERMINISM-401-057.
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## Goal
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- Measure determinism rate, order-invariance, and CVSS delta σ across scanners when fed identical SBOM+VEX inputs with frozen feeds.
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## Minimal harness (Python excerpt)
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```python
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# run_bench.py (excerpt) — deterministic JSON hashing
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def canon(obj):
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return json.dumps(obj, sort_keys=True, separators=(',', ':')).encode()
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def shas(b):
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return hashlib.sha256(b).hexdigest()
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for sbom, vex in zip(SBOMS, VEXES):
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for scanner, tmpl in SCANNERS.items():
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for mode in ("canonical", "shuffled"):
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for i in range(10):
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if mode == "shuffled":
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sb, vx = shuffle(sbom), shuffle(vex)
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out = run(tmpl.format(sbom=sb, vex=vx))
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norm = normalize(out) # purl, vuln id, base_cvss, effective
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blob = canon({"scanner": scanner, "sbom": sbom,
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"vex": vex, "findings": norm})
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results.append({
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"hash": shas(blob), "mode": mode,
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"run": i, "scanner": scanner, "sbom": sbom
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})
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```
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## Inputs
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- 3–5 SBOMs (CycloneDX 1.6 / SPDX 3.0.1) + matching VEX docs covering affected/not_affected/fixed.
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- Feeds bundle: vendor DBs (NVD, GHSA, OVAL) hashed and frozen.
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- Policy: single normalization profile (e.g., prefer vendor scores, CVSS v3.1).
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- Reachability dataset (optional combined run): `tests/reachability/samples-public` corpus; graphs produced via `stella graph lift` for each language sample; runtime traces optional.
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## Metrics
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- Determinism rate = identical_hash_runs / total_runs (20 per scanner/SBOM).
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- Order-invariance failures (# distinct hashes between canonical vs shuffled).
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- CVSS delta σ vs reference; VEX stability (σ_after ≤ σ_before).
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## Deliverables
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- Harness at `src/Bench/StellaOps.Bench/Determinism` (offline-friendly mock scanner included).
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- `results/*.csv` with per-run hashes plus `summary.json` determinism rate.
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- `results/inputs.sha256` listing SBOM, VEX, and config hashes (deterministic ordering).
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- `bench/reachability/dataset.sha256` listing reachability corpus inputs (graphs, runtime traces) when running combined bench.
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- CI target `bench:determinism` producing determinism% and σ per scanner; optional `bench:reachability` to recompute graph hash and runtime hit stability.
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## Links
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- Source advisory: `docs/product-advisories/23-Nov-2025 - Benchmarking Determinism in Vulnerability Scoring.md`
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- Sprint task: BENCH-DETERMINISM-401-057 (SPRINT_0401_0001_0001_reachability_evidence_chain.md)
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---
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## How to run (local)
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```sh
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cd src/Bench/StellaOps.Bench/Determinism
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# Run determinism bench (uses built-in mock scanner by default; defaults to 10 runs)
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python run_bench.py --sboms inputs/sboms/*.json --vex inputs/vex/*.json \
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--config configs/scanners.json --shuffle --output results
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# Reachability dataset (optional)
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python run_reachability.py --graphs ../reachability/graphs/*.json \
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--runtime ../reachability/runtime/*.ndjson.gz --output results-reach.csv
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```
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Outputs are written to `results.csv` (determinism) and `results-reach.csv` (reachability stability) plus SHA manifests.
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## How to run (CI)
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- Workflow `.gitea/workflows/bench-determinism.yml` calls `scripts/bench/determinism-run.sh`, which runs the harness with the bundled mock scanner and uploads `out/bench-determinism/**` (results, manifests, summary). Set `DET_EXTRA_INPUTS` to include frozen feed bundles in `inputs.sha256`.
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- Optional `bench:reachability` target (future) will replay reachability corpus, recompute graph hashes, and compare against expected `dataset.sha256`.
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- CI fails when `determinism_rate` < `BENCH_DETERMINISM_THRESHOLD` (defaults to 0.95; set via env in the workflow).
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## Offline/air-gap workflow
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1. Place feeds bundle, SBOMs, VEX, and reachability corpus under `offline/inputs/` with matching `inputs.sha256` and `dataset.sha256`.
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2. Run `./offline_run.sh --inputs offline/inputs --outputs offline/results` to execute both benches without network.
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3. Verify hashes: `sha256sum -c offline/inputs/inputs.sha256` and `sha256sum -c offline/inputs/dataset.sha256`.
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4. Store outputs plus manifests in Offline Kit; include DSSE envelope if signing is enabled (`./sign_results.sh`).
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## Notes
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- Keep file ordering deterministic (lexicographic) when generating manifests.
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- Do not pull live feeds during bench runs; use frozen bundles only.
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- For reachability runs, require symbol manifest availability; otherwise mark missing symbols and fail the run.
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