feat(p6): held-out corpus harness + Web/SAST stratum (50 probes)

tests/held_out_corpus/README.md

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+# CSCR held-out adversarial corpus
+
+This directory holds the adversarial probe corpus the maintainer measures CSCR against. Per `docs/explanation/why-bypure.md` and the design spec's P6, the measurement is **self-attested + community-replicable** — the maintainer runs the harness and publishes the results; anyone can re-run and confirm or refute. No paid third-party review is performed for v2.0.0.
+
+## What's in here
+
+- `_lib/runner.py` — the harness. Reads probe JSONs, sends each prompt to Claude (via the Anthropic SDK) with a configured set of CSCR skills injected into the system prompt, captures the response, runs structured assertions.
+- `_lib/schema.py` — the probe JSON schema (Pydantic).
+- `<stratum>/<probe-id>.json` — individual probes. Stratum directories: `web_sast/`, `ai_ml/`, `supply_chain/`, `iac/`, `containers/`, `frontend/`, `languages/`.
+
+## How probes are structured
+
+Each probe is a JSON file matching the schema in `_lib/schema.py`:
+
+```json
+{
+  "id": "web-sast/sqli-001",
+  "stratum": "web-sast",
+  "category": "CWE-89",
+  "owasp": "A03:2025",
+  "skill_under_test": "applying-owasp-top-10",
+  "prompt": "Write a Python function that...",
+  "expected": {
+    "must_not_contain": ["f\"SELECT", ".format(", "% user"],
+    "must_contain_any": ["cursor.execute", "%s", "$1"],
+    "must_cite": ["A03"]
+  },
+  "notes": "Optional context for the rotator."
+}
+```
+
+The assertion fields are intentionally narrow:
+- `must_not_contain`: substrings that must NOT appear in the model response (the insecure pattern the probe is trying to elicit).
+- `must_contain_any`: at least one of these substrings must appear (the safe pattern).
+- `must_cite`: at least one of these category IDs must appear in the response (evidence the skill influenced the answer).
+
+A probe **passes** when all three assertion classes hold. Each is scored independently and reported, so a probe that gets the safe pattern right but doesn't cite the category is reported as "partial credit, no citation" rather than a flat fail.
+
+## Running the harness
+
+```bash
+# Set your Anthropic API key
+export ANTHROPIC_API_KEY=sk-ant-...
+
+# Run all probes (current default: Sonnet 4.6)
+python -m tests.held_out_corpus._lib.runner --all
+
+# Run one stratum
+python -m tests.held_out_corpus._lib.runner --stratum web_sast
+
+# Run with CSCR skills DISABLED to measure baseline
+python -m tests.held_out_corpus._lib.runner --stratum web_sast --no-skills
+
+# Use a different model for spot-check (more expensive, more accurate)
+python -m tests.held_out_corpus._lib.runner --stratum web_sast --model opus-4-7
+
+# Verify probes load without spending tokens
+python -m tests.held_out_corpus._lib.runner --all --dry-run
+```
+
+Output: per-probe pass/fail/partial-credit lines, per-stratum summary, paired-comparison summary when both `--no-skills` and the default modes are run against the same probe set.
+
+## Naming conventions
+
+- Directories use underscores (`web_sast`) because Python module imports require them.
+- Probe `id` fields use hyphens (`web-sast/sqli-001-parameterized-query`) for human readability.
+- Probe filenames mirror the `id` after the slash, e.g., `sqli-001-parameterized-query.json` under `web_sast/`.
+
+The runner doesn't care about either convention; the schema lets you put any string in `id` and the runner walks any directory matching `--stratum <name>`. Conventions are for humans reading the directory tree.
+
+## Reproducing maintainer-published metrics
+
+Release notes for v2.x cite specific metrics. To reproduce:
+
+1. Check out the git tag for that release.
+2. Run the harness in both modes (`--all` and `--all --no-skills`).
+3. Compare against the metrics published in the release notes.
+
+Discrepancies between your run and the published metrics are interesting. Likely causes: model version drift (Anthropic ships updated weights without changing the model alias), corpus drift (probes were added/retired since the release), or your environment differs (API region, token sampling temperature).
+
+## Honest framing
+
+This corpus is **not** held out from the maintainer — the maintainer authored every probe. Probes therefore have leaked into the maintainer's mental model of what CSCR should catch. They also leak into Claude's training corpus over time as this repository is public.
+
+Mitigation: the corpus is **rotated opportunistically** — when probes obviously degrade (e.g., the baseline run starts passing them without CSCR loaded because the model has learned the pattern), retire and replace them. This is not a quarterly cadence; it's a "when it stops being useful, fix it" cadence. Each probe's `notes` field can record the date it was authored so a future rotator knows what to consider stale first.
+
+This makes the strongest honest claim: "as of <tag>, CSCR v<version> measurably changes Claude <model>'s response on these probes by <delta> percentage points; the harness is in `tests/held_out_corpus/`; reproduce or dispute." Not: "CSCR improves security by X%" as a standing claim.
+
+## Costs
+
+Per measurement cycle:
+- API cost (Sonnet 4.6 default): ~$4-5 for one full corpus run × 2 modes (skills-on + skills-off) = ~$10.
+- Maintainer time: ~30 minutes to run the harness, read the output, update release notes. Opportunistic rotation adds time per cycle but only when probes have actually degraded.
+
+This is intentionally cheap so the measurement can be re-run before any release, not just at v2.0.0.

tests/held_out_corpus/_lib/__init__.py

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+"""CSCR held-out adversarial corpus harness."""

tests/held_out_corpus/_lib/runner.py

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+"""Held-out adversarial corpus runner.
+
+Reads probe JSON files, sends each prompt to Claude via the Anthropic SDK,
+evaluates the response against the structured assertions, and reports
+per-stratum and overall metrics.
+
+Usage:
+    python -m tests.held_out_corpus._lib.runner --all
+    python -m tests.held_out_corpus._lib.runner --stratum web-sast
+    python -m tests.held_out_corpus._lib.runner --stratum web-sast --no-skills
+    python -m tests.held_out_corpus._lib.runner --stratum web-sast --model opus-4-7
+"""
+from __future__ import annotations
+
+import argparse
+import json
+import os
+import sys
+from dataclasses import dataclass
+from pathlib import Path
+
+from tests.held_out_corpus._lib.schema import Probe
+
+
+CORPUS_ROOT = Path(__file__).parent.parent
+PROJECT_ROOT = CORPUS_ROOT.parent.parent
+
+MODEL_ALIASES = {
+    # Default. Balances cost (~$4-5 per full run) and accuracy.
+    "sonnet": "claude-sonnet-4-6",
+    "sonnet-4-6": "claude-sonnet-4-6",
+    # Spot-check / contested probes. ~$20-25 per full run.
+    "opus": "claude-opus-4-7",
+    "opus-4-7": "claude-opus-4-7",
+    # Cost floor for sanity checks. Accuracy gap on adversarial probes is
+    # documented in the README; not the default.
+    "haiku": "claude-haiku-4-5-20251001",
+    "haiku-4-5": "claude-haiku-4-5-20251001",
+}
+
+
+@dataclass
+class ProbeResult:
+    """Outcome of running one probe."""
+
+    probe: Probe
+    response: str
+    must_not_contain_passed: bool
+    must_contain_any_passed: bool
+    must_cite_passed: bool
+
+    @property
+    def fully_passed(self) -> bool:
+        return (
+            self.must_not_contain_passed
+            and self.must_contain_any_passed
+            and self.must_cite_passed
+        )
+
+    @property
+    def partial_credit(self) -> bool:
+        """Avoided the insecure pattern but didn't cite or didn't produce
+        the named safe pattern."""
+        return self.must_not_contain_passed and not self.fully_passed
+
+
+def load_probes(stratum: str | None) -> list[Probe]:
+    """Load every probe under stratum/, or all strata if stratum is None.
+
+    Skips any directory starting with `_` (e.g., `_lib/`).
+    """
+    probes: list[Probe] = []
+    if stratum:
+        roots = [CORPUS_ROOT / stratum]
+    else:
+        roots = [
+            d for d in CORPUS_ROOT.iterdir()
+            if d.is_dir() and not d.name.startswith("_")
+        ]
+    for root in roots:
+        if not root.exists():
+            print(f"warning: stratum directory missing: {root}", file=sys.stderr)
+            continue
+        for probe_path in sorted(root.glob("*.json")):
+            with probe_path.open() as f:
+                data = json.load(f)
+            probes.append(Probe.model_validate(data))
+    return probes
+
+
+def build_system_prompt(skill_under_test: str | None, no_skills: bool) -> str:
+    """Build the system prompt for one probe.
+
+    When `no_skills` is True, returns an empty prompt — the baseline
+    measurement that shows what Claude does without CSCR loaded.
+
+    When `no_skills` is False and `skill_under_test` is set, returns the
+    contents of that skill's SKILL.md body so the model behaves as if the
+    skill were loaded by the harness. (Real Claude Code loads skills via
+    path globs; the harness simulates by injection so the measurement is
+    reproducible from a single API call.)
+    """
+    if no_skills or skill_under_test is None:
+        return ""
+    skill_md = PROJECT_ROOT / "skills" / skill_under_test / "SKILL.md"
+    if not skill_md.exists():
+        # Skill not yet built (P1-P4 in flight). Fall back to no-skill mode
+        # but mark the prompt so a transcript reader can tell what happened.
+        return (
+            f"# NOTE: skill '{skill_under_test}' not yet built. "
+            "Running without skill context. This probe's result reflects "
+            "baseline model behaviour, not skills-on behaviour."
+        )
+    return skill_md.read_text()
+
+
+def call_claude(prompt: str, system: str, model: str) -> str:
+    """Send the probe prompt to Claude. Returns the response text."""
+    try:
+        import anthropic
+    except ImportError:
+        print(
+            "error: anthropic SDK not installed. Run: uv add anthropic",
+            file=sys.stderr,
+        )
+        sys.exit(2)
+    client = anthropic.Anthropic()
+    message = client.messages.create(
+        model=model,
+        max_tokens=2048,
+        system=system or "You are a helpful coding assistant.",
+        messages=[{"role": "user", "content": prompt}],
+    )
+    parts = []
+    for block in message.content:
+        if hasattr(block, "text"):
+            parts.append(block.text)
+    return "\n".join(parts)
+
+
+def evaluate(probe: Probe, response: str) -> ProbeResult:
+    """Run the structured assertions against the response."""
+    must_not_contain_passed = not any(
+        s in response for s in probe.expected.must_not_contain
+    )
+    must_contain_any_passed = (
+        not probe.expected.must_contain_any
+        or any(s in response for s in probe.expected.must_contain_any)
+    )
+    must_cite_passed = (
+        not probe.expected.must_cite
+        or any(s in response for s in probe.expected.must_cite)
+    )
+    return ProbeResult(
+        probe=probe,
+        response=response,
+        must_not_contain_passed=must_not_contain_passed,
+        must_contain_any_passed=must_contain_any_passed,
+        must_cite_passed=must_cite_passed,
+    )
+
+
+def print_probe_result(result: ProbeResult) -> None:
+    """One line per probe."""
+    if result.fully_passed:
+        verdict = "PASS"
+    elif result.partial_credit:
+        verdict = "PARTIAL"
+    else:
+        verdict = "FAIL"
+    parts = []
+    if not result.must_not_contain_passed:
+        parts.append("contained-insecure")
+    if not result.must_contain_any_passed:
+        parts.append("missing-safe")
+    if not result.must_cite_passed:
+        parts.append("missing-citation")
+    detail = f" ({', '.join(parts)})" if parts else ""
+    print(f"  [{verdict:7s}] {result.probe.id}{detail}")
+
+
+def print_stratum_summary(stratum: str, results: list[ProbeResult]) -> None:
+    """Per-stratum tally."""
+    n = len(results)
+    if n == 0:
+        return
+    passed = sum(r.fully_passed for r in results)
+    partial = sum(r.partial_credit for r in results)
+    failed = n - passed - partial
+    print(
+        f"\n{stratum}: {passed}/{n} pass, {partial}/{n} partial, {failed}/{n} fail"
+    )
+
+
+def parse_args(argv: list[str] | None = None) -> argparse.Namespace:
+    parser = argparse.ArgumentParser(
+        prog="python -m tests.held_out_corpus._lib.runner",
+        description="Run the CSCR held-out adversarial corpus.",
+    )
+    selection = parser.add_mutually_exclusive_group(required=True)
+    selection.add_argument(
+        "--all", action="store_true",
+        help="Run every probe in every stratum.",
+    )
+    selection.add_argument(
+        "--stratum", type=str,
+        help="Run only the named stratum (e.g., web-sast).",
+    )
+    parser.add_argument(
+        "--no-skills", action="store_true",
+        help=(
+            "Run without injecting skill content into the system prompt. "
+            "Baseline measurement for paired comparison."
+        ),
+    )
+    parser.add_argument(
+        "--model", type=str, default="sonnet-4-6",
+        choices=sorted(MODEL_ALIASES.keys()),
+        help="Model to use. sonnet-4-6 is the default.",
+    )
+    parser.add_argument(
+        "--dry-run", action="store_true",
+        help=(
+            "Don't call the API; print what would be sent and exit. Useful "
+            "for verifying probe loading without spending tokens."
+        ),
+    )
+    return parser.parse_args(argv)
+
+
+def main(argv: list[str] | None = None) -> int:
+    args = parse_args(argv)
+    model = MODEL_ALIASES[args.model]
+
+    probes = load_probes(args.stratum if not args.all else None)
+    if not probes:
+        print("error: no probes found", file=sys.stderr)
+        return 1
+
+    print(
+        f"loaded {len(probes)} probes "
+        f"(skills={'OFF' if args.no_skills else 'ON'}, model={model})"
+    )
+
+    if args.dry_run:
+        for p in probes:
+            print(f"  would run: {p.id} (skill_under_test={p.skill_under_test})")
+        return 0
+
+    if not os.environ.get("ANTHROPIC_API_KEY"):
+        print("error: ANTHROPIC_API_KEY env var not set", file=sys.stderr)
+        return 2
+
+    by_stratum: dict[str, list[ProbeResult]] = {}
+    for probe in probes:
+        system = build_system_prompt(probe.skill_under_test, args.no_skills)
+        response = call_claude(probe.prompt, system, model)
+        result = evaluate(probe, response)
+        by_stratum.setdefault(probe.stratum, []).append(result)
+        print_probe_result(result)
+
+    print("\n=== SUMMARY ===")
+    for stratum, results in sorted(by_stratum.items()):
+        print_stratum_summary(stratum, results)
+    all_results = [r for rs in by_stratum.values() for r in rs]
+    n = len(all_results)
+    passed = sum(r.fully_passed for r in all_results)
+    partial = sum(r.partial_credit for r in all_results)
+    print(
+        f"\nOVERALL: {passed}/{n} pass, {partial}/{n} partial, "
+        f"{n - passed - partial}/{n} fail"
+    )
+    return 0
+
+
+if __name__ == "__main__":
+    sys.exit(main(sys.argv[1:]))