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Written after five evolve rounds produced zero decisions distinguishable from noise, and after reading Clearwing, Big Sleep, and the AIxCC 2025 finals. The premise we got wrong: OpenUltraSAST treats the LLM as a noisy oracle to average (K runs), floor (noise budget), gate (sign test) and slowly improve (evolve loop). 120 runs produced 120 distinct trajectories -- the variance is the loop's freedom to search, not the model's uncertainty. And the premise is empirically false as a claim about LLMs: Big Sleep found a real SQLite zero-day in Nov 2024; AIxCC finalists uncovered 18 real 0-days across 54M LOC, with the 2nd-place system using non-reasoning LLMs at 90% accuracy and $181/point. The lever is architecture, not prompt optimization. What the winners share, and Clearwing is the open instance of: the LLM is a judgement layer on an execution substrate, and truth comes from the sandbox -- a crash, a sanitizer report, a patch that stops the crash -- not from a score against a labeled corpus. Clearwing's poc_runner (apply diff, recompile, re-run, does-the-crash-still-happen) replaces our entire noise architecture. We built K-runs because we had no ground truth; they generate their own. The course: adopt Clearwing as the substrate (the maintainer already forks it), delete the noise architecture rather than fix it, and contribute the one thing Clearwing lacks -- the web/logic detection path. Our IR candidate enumerator (12.1% ruleset vs 96.6% IR, measured) and our obligation/absence-bug checker reach the dangerous web bugs that never crash a sandbox, which Clearwing's crash-oracle model cannot. The open research problem is a differential oracle for those classes: the vulnerable-parent/fix-commit pair as ground truth, with a request the fixed version rejects and the vulnerable one serves. Recommendation is explicitly not to rebuild: eighteen defects this session, all ours, against a 19k-line battle-tested MIT substrate. Not approved. Co-Authored-By: Claude Opus 4.8 <[email protected]> Claude-Session: https://claude.ai/code/session_01T7XD7x5KonMdmGRkp63EQG
28 lines
2.0 KiB
JSON
28 lines
2.0 KiB
JSON
{
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"feature_name": "constrained-detector",
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"created_at": "2026-09-06T14:30:00Z",
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"updated_at": "2026-09-08T00:00:00Z",
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"language": "en",
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"phase": "tasks",
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"approvals": {
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"requirements": {
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"generated": true,
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"approved": true
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},
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"design": {
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"generated": true,
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"approved": true
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},
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"tasks": {
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"generated": true,
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"approved": false
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}
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},
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"ready_for_implementation": false,
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"depends_on": [
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"learning-harness"
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],
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"approval_note": "2026-09-06 brief drafted at the maintainer's direction ('I'd rather spend time to design the exact DSPy style interface and evolutionary / statistical prompt optimization than fixing piece by piece'). Not approved; requirements not generated.; 2026-09-06 renamed from detector-optimizer to constrained-detector after the trajectory measurement: the brief's own conclusion is that the optimiser is not the next thing to build, and the spec should be named for what it delivers; 2026-09-06 requirements generated at the maintainer's direction, with the maintainer's emphasis recorded as Requirement 3 ('don't forget the emphasis on the real world bugs from the larger projects to avoid overfitting. we otherwise benchmark for cases that are not relevant'); 2026-09-06 requirements approved by the maintainer in session ('approve the requirements and run the design phase'); 2026-09-06 design approved by the maintainer in session ('approve the design and generate the tasks'); 2026-09-08 SUPERSEDED by execution-grounded-detection: this session's measurements showed the noise architecture (K-runs, per-family floor, regression budget, sign test, evolve loop) is a statistical treatment for a structural problem, and that the field (Big Sleep, AIxCC finals, Clearwing) grounds detection in execution rather than in scoring against a labeled corpus. The taxonomy, the IR candidate enumerator (96.6% ceiling) and the obligation checker survive as the web/logic detection path to contribute to a Clearwing-based substrate.",
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"superseded_by": "execution-grounded-detection"
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}
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