mirror of
https://github.com/norandom/OpenUltraSAST.git
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Marius CiepluchandClaude Opus 4.8
091303c7c0
Maintainer correction: execution isn't possible for all SAST targets, and the bugs this project owns -- IDOR, missing authz, injection -- don't crash anything. Execution is the easy arbiter only for memory-safety-in-C, which is not our world. What execution provided was an independent, deterministic arbiter of whether a claim is real -- not the same LLM that made it, not a noisy vote. That arbiter can be built statically, from the code, as a program model the claim is checked against. LLM proposes; the model disposes. Same architecture, same repair of the root cause, no runnable target required. The evidence ladder becomes static and deterministic: suspicion -> model_corroborated (claim consistent with resolved dataflow / a guard its siblings carry is absent) -> model_entailed (the model alone establishes it) -> execution_confirmed (deferred tier, C memory-safety only). model_corroborated and above are deterministic -- run the checker twice, same verdict -- which removes the run-to-run noise the same way a crash would, with no K-runs and no target to build. Our IR candidate enumerator (96.6% ceiling), binding chains and obligation checker stop being prompt context and become the arbiter itself. The course: promote those assets from inputs to arbiter, delete the noise layer, make the LLM a proposer the model audits, keep the corpus as the model's calibration set (the fix diff is what the model should see), and defer execution to Clearwing for the memory-safety classes only. Build the arbiter we can build from code; adopt the one we cannot, when a class demands it. Co-Authored-By: Claude Opus 4.8 <[email protected]> Claude-Session: https://claude.ai/code/session_01T7XD7x5KonMdmGRkp63EQG
29 lines
1.8 KiB
JSON
29 lines
1.8 KiB
JSON
{
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"feature_name": "model-grounded-detection",
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"created_at": "2026-09-08T00:00:00Z",
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"updated_at": "2026-09-08T01:00:00Z",
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"language": "en",
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"phase": "brief",
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"approvals": {
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"requirements": {
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"generated": false,
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"approved": false
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},
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"design": {
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"generated": false,
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"approved": false
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},
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"tasks": {
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"generated": false,
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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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"supersedes": [
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"learning-harness",
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"constrained-detector"
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],
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"depends_on": [],
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"approval_note": "2026-09-08 corrective brief drafted at the maintainer's direction ('can you produce a corrective spec that supersedes the project and sets a course'). Written after the learning-harness evolve rounds produced zero decisions distinguishable from noise, and after researching Clearwing (/home/mc/Source/clearwing, fork norandom/deepwing), Google Big Sleep, and the DARPA AIxCC 2025 finals. Not approved; requirements not generated. The central recommendation is to adopt Clearwing as the execution substrate rather than rebuild, and to contribute the web/logic detection path (taxonomy + IR candidate enumeration + obligation checker + a differential web oracle) that Clearwing's crash-oracle model does not reach. ; 2026-09-08 renamed execution-grounded-detection -> model-grounded-detection after the maintainer's correction: execution is not possible for all SAST targets and the bugs we own do not crash, so the arbiter is a program model built deterministically from code (IR candidate enumeration, binding-chain dataflow, obligation/guard-dominance) that checks LLM claims, producing a static evidence ladder (suspicion -> model_corroborated -> model_entailed); execution is a deferred tier for memory-safety-in-C only, adopted from Clearwing when a class needs it."
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}
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