Fix PR #47 review findings

CHANGELOG.md

@@ -9,6 +9,9 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ### Fixed
 
+- **Doppler horizon thrashed on slow corpus cycles** (`core/power_doppler.py`): a cycle longer than the fixed abandon horizon dropped every frame one tick before its seed returned. The horizon now doubles when a dropped seed comes back.
+- **Stale corpus-membership memo** (`services/fuzzer.py`): keyed on corpus length, so an in-place trim of the parent kept a "member" verdict. Hits are now re-validated by slot identity; misses are not memoized.
+
 - **`--mod-solving trace` clobbered `targets`** (`services/fuzzer.py`): the trace block reassigned the directed-targets parameter, disabling the Katz channel and directing at the fuzz target. Renamed the local.
 - **Doppler never scored corpora > 64 seeds picked in turn** (`core/power_doppler.py`): LRU evicted every partial frame. New seeds now wait for a slot; abandoned frames are scored early and freed. Flow-edge ids are int64 arrays under a global cap (frozensets could reach hundreds of MiB).
 - **Doppler mixed targets' edges** (`services/fuzzer.py`): multi-target frames are keyed per target. Without SHM, `--schedule doppler` now falls back to `base` with a warning instead of reporting enabled.

docs/DEEP_DIVE.md

@@ -85,7 +85,7 @@ For production and sensitive binaries using AFL family fuzzers is the best cours
 - **AFLGo SHM-tail distance channel**: compiled into EVERY shim-linked target since `__AFL_DISTANCE_MODE` defaulted to 1 (2026-08-24; `-D__AFL_DISTANCE_MODE=0` opts out). Inert unless directed mode uploads a distance table (`DistanceTableShm`/`__AFL_DIST_SHM_ID`): without one, sum/count stay 0 and every reader takes the Python-side path. `build_targets.sh --distance` additionally builds the trace-pc-instrumented `*_dist.so`/`*_dist_asan.so` variants, where the shim accumulates per-block distances in `__sanitizer_cov_trace_pc()` — the PC (relative to the dladdr-derived object base) probes an open-addressing table of `{key, dist}` entries (packed 12-byte layout; the 4-byte header holds the slot *capacity*, a power of two ≥ 2×entries so empty slots exist, and the builder hash-inserts at `key % capacity` with linear probing to mirror the shim's probe — uploaded by the fuzzer at startup via `DistanceTableShm`/`__AFL_DIST_SHM_ID`), accumulating sum/count into the 16-byte SHM **tail** (after the edge table: `u64 dist_sum`, `u64 dist_count`), written at reset, at process exit (subprocess runs never call reset), and per-iteration in in-process modes via `__afl_dist_flush` (direct_lite has no process boundary, so the runner flushes the tail after each `run_one`). Per-execution `avg_distance = sum/count/100` is read straight from the tail and preferred over Python-side computation; blocks without a table entry don't count (AFLGo semantics). The table's PC keys are recovered by scanning text for `call __sanitizer_cov_trace_pc` sites (modern clang emits no `__sancov_pcs` for trace-pc) mapped to valued blocks via the CFGs — `TargetDistance.pc_distance_table()`. The shim's sanitizer-coverage callbacks are hidden-visibility so a libasan LD_PRELOAD cannot interpose over them in PIE builds. `tools/gen_distance_table.py` emits the table as C or text for inspection. Without the table (count==0) everything degrades to the Python-side path. Works in subprocess, direct_lite, and persistent modes (ASAN direct_lite requires libasan preloaded at fuzzer-process start — the `use_direct_lite` gate). The periodic stats line shows live distance when directed mode is active: `dist: avg:<tail avg> min:<observed min> max:<observed max>` (or `no-data`). `build_targets.sh --distance` builds both `*_dist.so` (no-ASAN) and `*_dist_asan.so` (ASAN) variants with the cmplog shim linked in, so `--cmplog` keeps them in direct_lite mode. Startup reports `[*] Distance instrumentation: detected` when the target carries the channel (the shim's `__afl_dist_flush` or a defined `__sanitizer_cov_trace_pc`), mirroring the AFL-instrumentation check. With `--elo` in directed mode, `aflgo` joins the Elo-arbitrated seed-strategy pool — a distance-pure arm picking `P(seed) ∝ exp(-2·norm_dist)` (distinct from the generic `weighted` arm, which blends distance with speed/size/entropy).
 - **AFLGo distance-annealed schedule** (`--schedule go`, requires `--target-functions`): wires the precomputed `avg_distance` (per-seed distance to directed targets) and `_anneal_progress` (exploration/exploitation annealing variable) into `SeedScorer.score()` for mutation budget scaling. During exploration phase (`anneal_progress` ≈ 0): uniform energy. During exploitation phase (`anneal_progress` → 1): `energy *= exp(β · (1 - norm_dist))` where `β = anneal_progress * 5`, capping at 100x. Seeds near the target get exponentially more mutations as the campaign matures. Previously these metrics only influenced seed selection but not mutation intensity.
 - **Power schedules** (`--schedule base|fast|coe|rare|mopt|lin|quad|go|aflgo|entropic|doppler`): AFL++ power schedules ported to control mutation budget per seed via `SeedScorer`. Each schedule modifies a base score (100) by frequency-based factors. Honggfuzz-style novelty decay, density, fertility, freshness, and entropy factors are applied multiplicatively on top. `entropic` (libFuzzer `-entropic`) scales energy by `1 + log2(1 + rare)`, where `rare` is the larger of `rare_edge_count`/`tc_ref` already collected for RARE/honggfuzz scoring — an approximation of libFuzzer's feature-frequency Shannon entropy using signal the fuzzer already tracks.
-- **Power Doppler schedule** (`--schedule doppler`, `core/power_doppler.py`): ultrasound power Doppler on coverage. Slow time = successive mutants of one seed (32 per ensemble); pixel = edge; sample = `log2(1 + hits)` (raw SHM counts, not buckets). Wall filter: mean removal (static path), then SVD components whose participation ratio spans ≥ half the seed's edges (and ≥ 4) are dropped as clutter — an early reject moving the whole path at once ("flash"). CFAR: residual power per edge vs `σ² · χ²_{dof}(1 − 10⁻³)`, `σ²` = median residual variance (floor 10⁻³). Seed power = summed flow power / dof; energy = `log1p(p)/log1p(max p)` ∈ [0, 1], scaled to `[1, max_mult]` like `katz`. Unscored or static seeds stay 1×. Gram eigendecomposition (n×n) replaces the full SVD (~6× faster). Bounded: 64 open ensembles × 2048 edges (float32, ≤16 MiB); when full, new seeds wait instead of evicting partial frames (LRU eviction never closed a frame once >64 seeds were picked in turn), and a frame untouched for 4 frames' worth of samples is scored early (≥ 3 samples) and freed. Scores: 4096 (LRU), flow-edge ids in int64 arrays capped at 2²⁰ total (8 MiB). Multi-target frames are keyed per target (edge ids are per-target). SHM coverage only — without it the schedule falls back to `base` with a warning; cost ~100 µs/exec at 2k live edges (dict→array conversion dominates), zero when off. Unmeasured — see `docs/TODO.md`.
+- **Power Doppler schedule** (`--schedule doppler`, `core/power_doppler.py`): ultrasound power Doppler on coverage. Slow time = successive mutants of one seed (32 per ensemble); pixel = edge; sample = `log2(1 + hits)` (raw SHM counts, not buckets). Wall filter: mean removal (static path), then SVD components whose participation ratio spans ≥ half the seed's edges (and ≥ 4) are dropped as clutter — an early reject moving the whole path at once ("flash"). CFAR: residual power per edge vs `σ² · χ²_{dof}(1 − 10⁻³)`, `σ²` = median residual variance (floor 10⁻³). Seed power = summed flow power / dof; energy = `log1p(p)/log1p(max p)` ∈ [0, 1], scaled to `[1, max_mult]` like `katz`. Unscored or static seeds stay 1×. Gram eigendecomposition (n×n) replaces the full SVD (~6× faster). Bounded: 64 open ensembles × 2048 edges (float32, ≤16 MiB); when full, new seeds wait instead of evicting partial frames (LRU eviction never closed a frame once >64 seeds were picked in turn), and a frame untouched for 4 frames' worth of samples is scored early (≥ 3 samples) and freed; that horizon doubles whenever a dropped seed returns (slow, not abandoned), so it converges past the corpus revisit time. Scores: 4096 (LRU), flow-edge ids in int64 arrays capped at 2²⁰ total (8 MiB). Multi-target frames are keyed per target (edge ids are per-target). SHM coverage only — without it the schedule falls back to `base` with a warning; cost ~100 µs/exec at 2k live edges (dict→array conversion dominates), zero when off. Unmeasured — see `docs/TODO.md`.
 - **Favored set / cull_queue** (`core/schedules.py`, `services/fuzzer.py`): AFL-style `top_rated` minimal-set-cover selection. For each edge, the cheapest seed covering it is selected, then a greedy cover builds the favored set. FAST and COE schedules apply energy bonuses to favored seeds (`_fast_factor`, `_coe_factor`, `coe_skip`). `_cull_queue()` runs periodically during fuzzing and updates `self._favored`; the score call site passes `favored=(seed_key in self._favored)` so the scheduler actually uses it.
 - **Bayesian seed quality** (`--bayesian`): `BayesianSeedQuality` (`core/seed_quality.py`) maintains a Beta-Bernoulli posterior per seed over `P(outcome = new_coverage)`. Thompson sampling naturally balances explore/exploit without a manual temperature knob — unexplored seeds have high posterior variance and get sampled. The `record_outcome()` feedback loop is now wired in `fuzz_one()` (was previously a dead code path with all posteriors stuck at Beta(1,1)). State is persisted to `seed_quality.json` and restored on resume.
 

docs/TODO.md

@@ -25,7 +25,7 @@
 - [ ] **ptrace breakpoints only on dominator-tree leaves** (2026-09-26) — a hit block implies its dominators ran, so `ptrace_coverage.py` could place int3 on leaves only and infer the rest. Edges `(prev, curr)` are not implied the same way; measure breakpoint count and edge-set loss on fuzzgoat first. See `docs/learnings/2026-09-26-dominators-chk-worst-case.md`.
 
 ## Scheduling
-- [ ] **A/B `--schedule doppler`** (2026-10-01) — power Doppler seed energy (`core/power_doppler.py`) is unit-tested and wired; never measured. Paired `bench_paired.py` vs `fast` on clang-built fuzzgoat (Hard Rule 52). Open: (a) ~100 µs/exec at 2k edges, mostly `get_edge_counts()` dict → numpy; a numpy accessor on `ShmCoverage` (exposes `_active_columns`, Hard Rule 34 — needs approval) removes it; (b) ensembles span picks, so a seed needs 32 picks to score — tune `ensemble` vs pick rate; (c) unused: `flow_edges()` (input-sensitive edge set) could feed position/operator targeting; (d) scores not persisted across `--resume`; (e) `STALE_FRAMES = 4` (abandoned-frame window) and early-close scoring of partial frames are untuned — log `stats()['refused']` on fuzzgoat.
+- [ ] **A/B `--schedule doppler`** (2026-10-01) — power Doppler seed energy (`core/power_doppler.py`) is unit-tested and wired; never measured. Paired `bench_paired.py` vs `fast` on clang-built fuzzgoat (Hard Rule 52). Open: (a) ~100 µs/exec at 2k edges, mostly `get_edge_counts()` dict → numpy; a numpy accessor on `ShmCoverage` (exposes `_active_columns`, Hard Rule 34 — needs approval) removes it; (b) ensembles span picks, so a seed needs 32 picks to score — tune `ensemble` vs pick rate; (c) unused: `flow_edges()` (input-sensitive edge set) could feed position/operator targeting; (d) scores not persisted across `--resume`; (e) `STALE_FRAMES = 4` (initial abandoned-frame window, self-widening) and early-close scoring of partial frames are untuned — log `stats()['refused']` on fuzzgoat.
 - [ ] **A/B the OS / network scheduler ports** (2026-09-30) — `mlfq`, `stride`, `eevdf`, `bfq`, `sfq`, `codel`, `aimd`, `p2c` seed arms and `op_stride`, `op_p2c` are unit- and wiring-tested only. Run `tools/lib/bench_paired.py` per arm vs `seed_round_robin` / `drr` on fuzzgoat (clang, ASAN). Untuned: MLFQ allotment/boost, BFQ budget range, CoDel target/interval, AIMD alpha/beta/loss run. Open: (a) `sfq` groups only direct siblings (`parent_key`), and only under `--lineage`; a lineage-root flow would group whole families; (b) no arm persists state.
 - [ ] **A/B the effector/token/chunk/changed/rare_mask position arms** (2026-09-30) — wired and unit-tested; a 3k-exec fuzzgoat run confirms live signal (`changed`: 673 moved / 96 unmoved / 2231 unmeasured rounds; `rare_mask`: target on 328/3000 rounds) but fuzzgoat cannot rank position arms (see `pos_fibonacci` entry). Run `tools/lib/bench_paired.py` `pos-arena-{token,chunk,changed,rare-mask}` vs `pos-arena-uniform` on png_read (`chunk` needs a container corpus). Open: (a) `effector` had no drained map in 3k execs (SkipDet skipped 111/112 seeds) -- measure its reach on long runs before A/B, it is not subset-testable (needs the det stage); (b) `changed` credits only ~25% of rounds: parents without a recorded path hash (spliced/generated inputs) -- record one at admission or accept; (c) neither `changed` nor `rare_mask` persists state.
 - [ ] **Pre-existing, found 2026-09-30:** `tools/build_targets.sh` ASAN variants fail in the cloud container (non-ASAN builds fine).

src/fuzzer_tool/core/power_doppler.py

@@ -40,7 +40,8 @@
 DEFAULT_MAX_SCORES = 4096
 # Flow-edge ids kept across all scores: 8 B each bounds them at 8 MiB.
 DEFAULT_MAX_FLOW_IDS = 1 << 20
-# Open frame untouched for this many full frames of samples is abandoned.
+# Open frame untouched for this many full frames of samples is abandoned
+# (initial horizon; doubles whenever a dropped seed comes back).
 STALE_FRAMES = 4
 # CFAR false-alarm probability per edge.
 FALSE_ALARM = 1e-3
@@ -235,6 +236,8 @@ def __init__(
         self._max_scores = max_scores
         self._max_flow_ids = max_flow_ids
         self._stale_after = max_seeds * ensemble * STALE_FRAMES
+        # Keys whose frames were dropped as abandoned; bounded like _open.
+        self._dropped_keys: LRUCache = LRUCache(max_seeds)
         # Insertion order is recency order; capacity is enforced by hand
         # (_admit, _trim) so evicted frames can be scored / ids uncounted.
         self._open: dict[str, _Ensemble] = {}
@@ -257,6 +260,7 @@ def observe(self, seed_key: str, hits: Mapping[int, int]) -> None:
         self._ticks += 1
         ens = self._open.pop(seed_key, None)
         if ens is None:
+            self._revisit(seed_key)
             ens = self._admit()
         if ens is None:
             self._refused += 1
@@ -279,6 +283,19 @@ def observe(self, seed_key: str, hits: Mapping[int, int]) -> None:
         del self._open[seed_key]
         self._close(seed_key, ens)
 
+    def _revisit(self, seed_key: str) -> None:
+        """A dropped seed came back: it was slow, not gone. Widen the horizon.
+
+        A fixed horizon thrashes once the corpus cycle outlasts it, e.g. 13
+        seeds in turn vs a 12-tick horizon: every frame is dropped one tick
+        before its seed returns. Doubling converges past the revisit time.
+        """
+        if seed_key not in self._dropped_keys:
+            return
+
+        del self._dropped_keys[seed_key]
+        self._stale_after *= 2
+
     def _admit(self) -> _Ensemble | None:
         """Fresh frame if a slot is free or the oldest frame is abandoned.
 
@@ -294,6 +311,7 @@ def _admit(self) -> _Ensemble | None:
 
             # Abandoned: score what it has rather than throw it away.
             del self._open[key]
+            self._dropped_keys[key] = True
             if old.n >= _MIN_ENSEMBLE:
                 self._close(key, old)
         return _Ensemble(self._ensemble, self._max_edges)
@@ -356,5 +374,6 @@ def stats(self) -> dict[str, float]:
             "dropped_edges": self._dropped,
             "refused": self._refused,
             "flow_ids": self._flow_ids,
+            "stale_after": self._stale_after,
             "max_power": self._peak(),
         }

src/fuzzer_tool/services/fuzzer.py

@@ -2745,8 +2745,8 @@ def __init__(
             )
             if arm is not None
         )
-        # (parent, corpus size, in corpus?): one membership test per pick.
-        self._parent_memo: tuple[bytes, int, bool] | None = None
+        # (parent, corpus list, slot, seed there): one membership test per pick.
+        self._parent_memo: tuple[bytes, list[bytes], int, bytes] | None = None
         if self._seed_os_arms:
             log.info("OS/network seed arms enabled: %d", len(self._seed_os_arms))
         # LST override: no seed waits more than lst_revisit seconds between
@@ -4548,18 +4548,27 @@ def _in_corpus(self, parent: bytes) -> bool:
         """Live-corpus membership of *parent*, memoized across its executions.
 
         Checked against the seed picker's cached key map (rebuilt only on
-        corpus change), not ``seed_meta``. The memo is keyed on corpus size
-        too, so a parent admitted mid-pick is seen.
+        corpus change), not ``seed_meta``. A hit is memoized with the slot it
+        sits in and re-validated by identity, O(1): an in-place replacement
+        (trim) or a rebuilt list misses. A miss is never memoized, so a
+        parent admitted mid-pick is seen.
         """
-        n = len(self.corpus)
+        corpus = self.corpus
         memo = self._parent_memo
-        if memo is not None and memo[0] is parent and memo[1] == n:
-            return memo[2]
+        if memo is not None and memo[0] is parent and memo[1] is corpus:
+            slot = memo[2]
+            if slot < len(corpus) and corpus[slot] is memo[3]:
+                return True
 
         key_to_seed, _ = self._seed_picker._corpus_keys()
-        hit = self._seed_key(parent) in key_to_seed
-        self._parent_memo = (parent, n, hit)
-        return hit
+        seed = key_to_seed.get(self._seed_key(parent))
+        if seed is None:
+            self._parent_memo = None
+            return False
+
+        slot = corpus.index(seed)
+        self._parent_memo = (parent, corpus, slot, corpus[slot])
+        return True
 
     def _seed_key(self, data: bytes) -> str:
         """Return content hash for *data*."""

tests/test_os_net_scheduler_wiring.py

@@ -282,6 +282,34 @@ def test_adversarial_parent_admitted_later_is_recorded(self, tmp_path):
         for arm in f._seed_os_arms:
             assert arm.bandit_stats() == {key: (1.0, 0.0)}
 
+    def test_regression_parent_replaced_in_place_not_recorded(self, tmp_path):
+        """Falsification (PR #47 review): same-length in-place replacement retires the parent."""
+        kwargs = {kw: True for kw, _a, _c in SEED_ARMS.values()}
+        f = _real_fuzzer(tmp_path, **kwargs)
+        f.corpus.append(SEED_A)
+        f._record_seed_os_arms(SEED_A, success=True, weight=1.0)
+
+        f.corpus[f.corpus.index(SEED_A)] = SEED_B
+        f._record_seed_os_arms(SEED_A, success=True, weight=1.0)
+
+        key = f._seed_key(SEED_A)
+        for arm in f._seed_os_arms:
+            assert arm.bandit_stats()[key] == (1.0, 0.0)
+
+    def test_adversarial_parent_kept_across_corpus_rebuild(self, tmp_path):
+        """A rebuilt corpus list that still holds the parent keeps recording it."""
+        kwargs = {kw: True for kw, _a, _c in SEED_ARMS.values()}
+        f = _real_fuzzer(tmp_path, **kwargs)
+        f.corpus.append(SEED_A)
+        f._record_seed_os_arms(SEED_A, success=True, weight=1.0)
+
+        f.corpus = [SEED_C, SEED_A]
+        f._record_seed_os_arms(SEED_A, success=True, weight=1.0)
+
+        key = f._seed_key(SEED_A)
+        for arm in f._seed_os_arms:
+            assert arm.bandit_stats()[key] == (2.0, 0.0)
+
     def test_op_arms_get_priors_registration_and_records(self):
         """The op arms sit in _register_arms and in fuzz_one's shared record loop."""
         from fuzzer_tool.services import fuzzer as fz