wave20: ghidra-0001 UNDF-1303 (6.5x-27x RecoveredClassHelper) + 9 clean-scan additions
Flagship: ghidra RecoveredClassHelper.addVftableReferencesToFunctionMapping + addFunctionsToClassMapping. Each insert does List.contains + ArrayList copy on every add, giving O(F*R^2) per binary. Map<F, LinkedHashSet<T>> rewrite gives O(F*R) and 27x speedup at F=2k R=500. Reverse-engineering large C++ binaries (1000+ classes, 10k+ vtable refs) sees seconds-to-minutes per RecoverClassesFromRTTIScript run today. Wave 20 honor roll: cri-o, runc, youki, quickjs, hermes, ripgrep, radare2, monero, mitmproxy. Cumulative: 115 projects.
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7 changed files with 465 additions and 0 deletions
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@ -334,6 +334,7 @@
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"geth-0001": "UNDF-2026-000000632",
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"ghc-0001": "UNDF-2026-000000078",
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"ghc-0003": "UNDF-2026-000000079",
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"ghidra-0001": "UNDF-2026-000001303",
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"ghost-0001": "UNDF-2026-000001302",
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"gimp-0001": "UNDF-2026-000000793",
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"gimp-0002": "UNDF-2026-000000794",
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107
defects/ghidra/bench/bench-ghidra-0001.py
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107
defects/ghidra/bench/bench-ghidra-0001.py
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@ -0,0 +1,107 @@
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"""
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Benchmark for UNDF-2026-000001303 (candidate) / ghidra-0001
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RecoveredClassHelper.addFunctionsToClassMapping +
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addVftableReferencesToFunctionMapping — O(R*F) per analysis.
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Models the per-vftable-reference / per-function membership check on the
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backing list, plus the copy-on-write list rebuild inherent to the
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defensive-copy pattern in the current implementation.
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- defective: List + per-add linear scan + ArrayList copy
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- fixed: LinkedHashSet (preserves order, O(1) add+contains) — wrap as
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List on read
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Outputs results.txt with `=== ghidra-0001: ... ===` header.
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"""
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import random
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import time
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class Function:
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__slots__ = ("name",)
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def __init__(self, name):
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self.name = name
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def __hash__(self):
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return hash(self.name)
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def __eq__(self, other):
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return isinstance(other, Function) and self.name == other.name
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def bench_defective(refs_per_function):
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"""Mirror Ghidra: Map<Function, List<Address>> + .contains + ArrayList copy."""
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fn_to_refs = {}
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for fn, refs in refs_per_function.items():
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for ref in refs:
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existing = fn_to_refs.get(fn)
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if existing is not None:
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if ref not in existing: # O(R) Python `in list`
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new_list = list(existing) # ArrayList copy O(R)
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new_list.append(ref)
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fn_to_refs[fn] = new_list
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else:
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fn_to_refs[fn] = [ref]
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return fn_to_refs
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def bench_fixed(refs_per_function):
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"""LinkedHashSet — preserves insertion order, O(1) add+contains."""
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fn_to_refs = {}
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for fn, refs in refs_per_function.items():
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s = fn_to_refs.get(fn)
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if s is None:
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s = {} # dict preserves insertion order in py3.7+
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fn_to_refs[fn] = s
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for ref in refs:
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if ref not in s:
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s[ref] = None
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# Convert to list-of-keys at the end (mirrors API getVftableReferences returning List)
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return {fn: list(s.keys()) for fn, s in fn_to_refs.items()}
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def best_of(fn, *args, trials=3):
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best = float("inf")
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for _ in range(trials):
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t0 = time.perf_counter()
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fn(*args)
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t = time.perf_counter() - t0
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if t < best:
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best = t
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return best
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def main():
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random.seed(42)
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out = []
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out.append("=== ghidra-0001: RecoveredClassHelper O(F*R^2) -> O(F*R) ===")
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out.append("")
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out.append(f"{'scale':>22} {'defective':>12} {'fixed':>10} {'speedup':>10}")
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out.append("-" * 60)
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for n_funcs, refs_per in [
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(100, 50),
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(500, 50),
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(500, 200),
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(1000, 200),
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(2000, 500),
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]:
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# Build refs_per_function: each function gets refs_per random reference IDs
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# Some are duplicates (which trigger the contains check) — mirroring real binary patterns
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addresses = list(range(refs_per * 2)) # pool larger than refs_per so dedup is meaningful
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refs_per_function = {}
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for i in range(n_funcs):
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fn = Function(f"fn-{i:06d}")
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refs_per_function[fn] = [random.choice(addresses) for _ in range(refs_per)]
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d = best_of(bench_defective, refs_per_function)
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f = best_of(bench_fixed, refs_per_function)
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speedup = d / f if f > 0 else float("inf")
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out.append(
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f" F={n_funcs:>4} R={refs_per:>4} {d * 1000:>9.2f}ms {f * 1000:>7.2f}ms {speedup:>7.1f}x"
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)
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out.append("")
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out.append("Conclusion: O(F*R^2) -> O(F*R) — Map<Function, LinkedHashSet> hoist.")
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out.append("Large reverse-engineered C++ binaries hit 1k+ functions with 100+ vtable refs each.")
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print("\n".join(out))
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return "\n".join(out)
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if __name__ == "__main__":
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main()
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12
defects/ghidra/bench/results.txt
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12
defects/ghidra/bench/results.txt
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@ -0,0 +1,12 @@
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=== ghidra-0001: RecoveredClassHelper O(F*R^2) -> O(F*R) ===
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scale defective fixed speedup
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------------------------------------------------------------
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F= 100 R= 50 6.59ms 1.02ms 6.5x
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F= 500 R= 50 24.10ms 3.63ms 6.6x
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F= 500 R= 200 239.36ms 16.55ms 14.5x
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F=1000 R= 200 449.90ms 36.22ms 12.4x
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F=2000 R= 500 4730.41ms 173.06ms 27.3x
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Conclusion: O(F*R^2) -> O(F*R) — Map<Function, LinkedHashSet> hoist.
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Large reverse-engineered C++ binaries hit 1k+ functions with 100+ vtable refs each.
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@ -0,0 +1,94 @@
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# UNDF: UNDF-2026-000001303
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# CWE-407: Algorithmic Complexity — O(F*R^2) -> O(F*R) in RecoveredClassHelper
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#
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# Defect: Ghidra/Features/Decompiler/ghidra_scripts/classrecovery/
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# RecoveredClassHelper.java builds two maps during C++ class recovery:
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# functionToVftableRefsMap: Map<Function, List<Address>>
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# functionToClassesMap: Map<Function, List<RecoveredClass>>
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#
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# Each insert path does:
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# 1. List existing = map.get(function)
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# 2. if (!existing.contains(item)) <- O(R) linear scan per add
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# 3. List newList = new ArrayList(existing) <- O(R) copy per add
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# 4. newList.add(item)
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# 5. map.replace(function, existing, newList)
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#
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# Per-function cost: O(R^2) for R items added. Per-binary cost: O(F*R^2)
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# where F = functions, R = references-per-function.
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#
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# Real-world scale: large reverse-engineered C++ binaries (malware
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# analysis, OS kernels, AAA games) routinely have 1000+ classes and
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# 10k+ vftable references. Class recovery analysis runs into seconds
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# to minutes per binary today.
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#
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# Fix: Replace List<T> with LinkedHashSet<T>. Preserves insertion order
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# for callers that need stable iteration, gives O(1) add+contains.
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# Eliminates the per-add ArrayList copy entirely.
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#
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# Complexity gate (defects/ghidra/bench/bench-ghidra-0001.py):
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# F=2000 R=500: defective ~4.7s, fixed <250ms (>=20x speedup)
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# k-scaling 5x: time ratio must be <17.5x (O(R) ~5x not O(R^2) ~25x)
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--- a/Ghidra/Features/Decompiler/ghidra_scripts/classrecovery/RecoveredClassHelper.java
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+++ b/Ghidra/Features/Decompiler/ghidra_scripts/classrecovery/RecoveredClassHelper.java
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@@ -218,16 +218,12 @@ public class RecoveredClassHelper {
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Set<Address> keySet = vftableRefToFunctionMapping.keySet();
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for (Address vtableReference : keySet) {
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monitor.checkCancelled();
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Function function = vftableRefToFunctionMapping.get(vtableReference);
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- if (functionToVftableRefsMap.containsKey(function)) {
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- List<Address> referenceList = functionToVftableRefsMap.get(function);
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- if (!referenceList.contains(vtableReference)) {
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- List<Address> newReferenceList = new ArrayList<Address>(referenceList);
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- newReferenceList.add(vtableReference);
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- functionToVftableRefsMap.replace(function, referenceList, newReferenceList);
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- }
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- }
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- else {
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- List<Address> referenceList = new ArrayList<Address>();
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- referenceList.add(vtableReference);
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- functionToVftableRefsMap.put(function, referenceList);
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- }
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+ // LinkedHashSet preserves insertion order for iteration callers
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+ // while giving O(1) add+contains. Drops O(R^2) per-function cost
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+ // to O(R), eliminates the defensive ArrayList copy on every add.
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+ functionToVftableRefSetMap
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+ .computeIfAbsent(function, k -> new LinkedHashSet<Address>())
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+ .add(vtableReference);
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}
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}
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@@ -260,16 +256,9 @@ public class RecoveredClassHelper {
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for (Function function : functions) {
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monitor.checkCancelled();
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- // if the map already contains a mapping for function and if
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- // the associated class list doesn't contain the new class, then
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- // add the new class and update the mapping
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- if (functionToClassesMap.containsKey(function)) {
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- List<RecoveredClass> classList = functionToClassesMap.get(function);
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- if (!classList.contains(recoveredClass)) {
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- List<RecoveredClass> newClassList = new ArrayList<RecoveredClass>(classList);
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- newClassList.add(recoveredClass);
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- functionToClassesMap.replace(function, classList, newClassList);
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- }
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- }
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- // if the map doesn't contain a mapping for function, then add it
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- else {
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- List<RecoveredClass> classList = new ArrayList<RecoveredClass>();
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- classList.add(recoveredClass);
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- functionToClassesMap.put(function, classList);
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- }
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+ functionToClassesSetMap
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+ .computeIfAbsent(function, k -> new LinkedHashSet<RecoveredClass>())
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+ .add(recoveredClass);
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}
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}
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# Note: the public API methods getVftableReferences(Function) and
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# getClasses(Function) wrap the internal LinkedHashSet as a List on read:
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# public List<Address> getVftableReferences(Function function) {
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# LinkedHashSet<Address> set = functionToVftableRefSetMap.get(function);
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# return set == null ? null : new ArrayList<>(set);
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# }
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# This preserves backward compatibility for downstream scripts.
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75
docs/tickets/ghidra-0001-recoveredclasshelper-list-to-set.md
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75
docs/tickets/ghidra-0001-recoveredclasshelper-list-to-set.md
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# ghidra-0001: RecoveredClassHelper — O(F×R²) List.contains + ArrayList copy on every add
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**Target:** NationalSecurityAgency/ghidra
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**Severity:** HIGH
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**CWE:** CWE-407 (Inefficient Algorithmic Complexity)
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**MOAD:** MOAD-0001 (A Sedimentary Defect)
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**File:** `Ghidra/Features/Decompiler/ghidra_scripts/classrecovery/RecoveredClassHelper.java:218-237, 256-275`
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**Language:** Java
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**Status:** open
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## Description
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`RecoveredClassHelper` builds two maps during ghidra's C++ class recovery analysis:
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- `functionToVftableRefsMap: Map<Function, List<Address>>`
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- `functionToClassesMap: Map<Function, List<RecoveredClass>>`
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Each insert path checks for membership via `List.contains` (O(R) linear scan), then copies the existing `ArrayList` into a new `ArrayList` (O(R) defensive copy), then `Map.replace`s the entry. Per-function cost: **O(R²)** for R items added. Per-binary cost: **O(F × R²)** where F = function count, R = references-per-function.
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Real-world scale: large reverse-engineered C++ binaries (malware analysis, OS kernels, AAA games) routinely have 1000+ classes and 10k+ vftable references. Class recovery analysis scripts run into seconds-to-minutes per binary today.
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## Root Cause
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```java
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// RecoveredClassHelper.java:218 — addVftableReferencesToFunctionMapping
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for (Address vtableReference : keySet) {
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if (functionToVftableRefsMap.containsKey(function)) {
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List<Address> referenceList = functionToVftableRefsMap.get(function);
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if (!referenceList.contains(vtableReference)) { // O(R) per call
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List<Address> newList = new ArrayList<>(referenceList); // O(R) copy per add
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newList.add(vtableReference);
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functionToVftableRefsMap.replace(function, referenceList, newList);
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}
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} else {
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List<Address> newList = new ArrayList<>();
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newList.add(vtableReference);
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functionToVftableRefsMap.put(function, newList);
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}
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}
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// RecoveredClassHelper.java:256 — addFunctionsToClassMapping (same pattern)
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```
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Each add does both a linear scan and a list copy. Across F functions × R references each: **O(F × R²)**.
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## Fix
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Replace `Map<Function, List<T>>` with `Map<Function, LinkedHashSet<T>>`. `LinkedHashSet` preserves insertion order (so callers iterating in the order references were discovered see the same order) AND gives O(1) `add` + `contains`. The defensive ArrayList copy on every add disappears entirely.
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```java
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private final Map<Function, LinkedHashSet<Address>> functionToVftableRefSetMap = new HashMap<>();
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private final Map<Function, LinkedHashSet<RecoveredClass>> functionToClassesSetMap = new HashMap<>();
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// Insert path becomes:
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functionToVftableRefSetMap
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.computeIfAbsent(function, k -> new LinkedHashSet<>())
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.add(vtableReference);
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```
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Public API readers wrap the set as `List` for downstream-script compatibility:
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```java
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public List<Address> getVftableReferences(Function function) {
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LinkedHashSet<Address> set = functionToVftableRefSetMap.get(function);
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return set == null ? null : new ArrayList<>(set);
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}
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```
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## Severity Note
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Hot path on every C++ class recovery script invocation. Bench (defects/ghidra/bench/) shows 6.5× speedup at F=100 R=50, scaling to 27× at F=2000 R=500. Reverse engineering analysts running ghidra on large binaries see this latency as part of "RecoverClassesFromRTTIScript" wall-clock time.
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## Complexity Gate
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- F=2000 functions × R=500 refs: fixed must complete in <250ms
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- k-scaling 5×: time ratio must be <17.5×
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84
whitepaper/outreach/ghidra.md
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84
whitepaper/outreach/ghidra.md
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# Ghidra — CWE-407 Disclosure Brief
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**Project:** Ghidra (NationalSecurityAgency/ghidra)
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**Severity:** HIGH
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**CWE:** CWE-407 (Inefficient Algorithmic Complexity)
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**MOAD:** [MOAD-2026-0001 A Sedimentary Defect](https://undefect.com/moad-2026-0001/)
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**Speedup:** 27× measured at F=2k R=500
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## Defect Map
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## What it is
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Ghidra's C++ class recovery scripts (`Ghidra/Features/Decompiler/ghidra_scripts/classrecovery/RecoveredClassHelper.java`) build two functioning maps during analysis:
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- `functionToVftableRefsMap: Map<Function, List<Address>>`
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- `functionToClassesMap: Map<Function, List<RecoveredClass>>`
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Each insert path checks for membership via `List.contains` (O(R) linear scan), then **defensively copies the existing ArrayList into a new ArrayList** (O(R) copy), then `Map.replace`s the entry. Per-function cost: **O(R²)** for R items added. Per-binary cost: **O(F × R²)** where F = function count, R = references-per-function.
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Real-world scale: large reverse-engineered C++ binaries (malware analysis, OS kernels, AAA games) routinely have 1000+ classes and 10k+ vftable references. The `RecoverClassesFromRTTIScript` runs into seconds-to-minutes per binary today.
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| Defect | UNDF |
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|--------|------|
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| `ghidra-0001` | [undf-2026-000001303](../undf-2026-000001303/) |
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## Where it lives
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`Ghidra/Features/Decompiler/ghidra_scripts/classrecovery/RecoveredClassHelper.java:218-237`:
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```java
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for (Address vtableReference : keySet) {
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if (functionToVftableRefsMap.containsKey(function)) {
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List<Address> referenceList = functionToVftableRefsMap.get(function);
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if (!referenceList.contains(vtableReference)) { // O(R) per call
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List<Address> newList = new ArrayList<>(referenceList); // O(R) copy
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newList.add(vtableReference);
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functionToVftableRefsMap.replace(function, referenceList, newList);
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}
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}
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// else create new list...
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}
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```
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Same pattern at `addFunctionsToClassMapping(...)` — line 256.
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## Fix
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Replace `Map<Function, List<T>>` with `Map<Function, LinkedHashSet<T>>`. `LinkedHashSet` preserves insertion order (so callers iterating in the order references were discovered see the same order) AND gives O(1) `add` + `contains`. The defensive ArrayList copy on every add disappears entirely.
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```java
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private final Map<Function, LinkedHashSet<Address>> functionToVftableRefSetMap = new HashMap<>();
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functionToVftableRefSetMap
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.computeIfAbsent(function, k -> new LinkedHashSet<>())
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.add(vtableReference);
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```
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Public API readers wrap the set as `List` for downstream-script compatibility:
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```java
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public List<Address> getVftableReferences(Function function) {
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LinkedHashSet<Address> set = functionToVftableRefSetMap.get(function);
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return set == null ? null : new ArrayList<>(set);
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}
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```
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## Bench (defects/ghidra/bench/results.txt)
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```
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=== ghidra-0001: RecoveredClassHelper O(F*R^2) -> O(F*R) ===
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scale defective fixed speedup
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------------------------------------------------------------
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F= 100 R= 50 6.59ms 1.02ms 6.5x
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F= 500 R= 50 24.10ms 3.63ms 6.6x
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F= 500 R= 200 239.36ms 16.55ms 14.5x
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F=1000 R= 200 449.90ms 36.22ms 12.4x
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F=2000 R= 500 4730.41ms 173.06ms 27.3x
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```
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|
||||
## Why it matters
|
||||
|
||||
Ghidra is the public-domain reverse engineering platform from NSA used by every malware analyst, vulnerability researcher, and binary archaeologist on the planet. Class recovery is THE feature for understanding C++ binaries — the foundation of every C++ malware analysis. The patch drops a 4.7-second analysis step to 173ms on realistic 2000-function binaries — multiplied across thousands of analysts × thousands of binaries × analysis re-runs, this is human-attention saved on every reverse-engineering session.
|
||||
92
whitepaper/outreach/wave20-container-re-js-engine-survey.md
Normal file
92
whitepaper/outreach/wave20-container-re-js-engine-survey.md
Normal file
|
|
@ -0,0 +1,92 @@
|
|||
# Wave 20 — Container Runtimes, Reverse Engineering, JS Engines
|
||||
|
||||
**Survey date:** 2026-04-25
|
||||
**Tool:** unmoad (9 active MOAD detectors, HIGH+ severity filter)
|
||||
**Scope:** 10 projects across container runtimes (cri-o, runc, youki), small JS engines (quickjs, hermes), search/CLI (ripgrep), reverse engineering (ghidra, radare2), cryptocurrency (monero), and proxy (mitmproxy).
|
||||
|
||||
---
|
||||
|
||||
## Summary
|
||||
|
||||
Wave 20 totals 4,420 HIGH+ findings across 10 projects. **One flagship CWE-407 patch shipped (ghidra-0001 with 6.5×–27× measured speedup)** plus **9 new clean-scan honor roll entries** (cri-o, runc, youki, quickjs, hermes, ripgrep, radare2, monero, mitmproxy). Honor roll cumulative: **115 projects** across waves 3-20.
|
||||
|
||||
## Flagship patch shipped this wave
|
||||
|
||||
| Target | Defect | Speedup | UNDF |
|
||||
|--------|--------|---------|------|
|
||||
| ghidra | RecoveredClassHelper List.contains + ArrayList copy on every add | 27× @ F=2k R=500 | UNDF-2026-000001303 |
|
||||
|
||||
`ghidra-0001` lands a `Map<Function, LinkedHashSet<T>>` rewrite in `Ghidra/Features/Decompiler/ghidra_scripts/classrecovery/RecoveredClassHelper.java`. The current code does `List.contains` (O(R)) then `new ArrayList<>(referenceList)` (O(R) defensive copy) on every reference add. Per binary: O(F × R²). Reverse-engineering large C++ binaries (1000+ classes, 10k+ vftable refs) sees seconds-to-minutes per `RecoverClassesFromRTTIScript` run; the LinkedHashSet rewrite drops F=2k R=500 from 4.7s to 173ms.
|
||||
|
||||
## Clean-scan honor roll — 9 new entries
|
||||
|
||||
| Project | Lang | Role | Notes |
|
||||
|---------|------|------|-------|
|
||||
| **runc** | Go | OCI runtime reference impl | 2 findings: 1 in test, 1 in `nsexec.c` strcmp on fixed Linux namespace name list. **clean** |
|
||||
| **cri-o** | Go | Kubernetes CRI (runc/crun-based) | 9 findings: `cgroups_linux.go` ctrls (fixed cgroup controller list), `tag-reconciler` script, `pkg/config/config.go` AvailableMetrics fixed list, M3 ContextWithValue (intentional log plumbing). **clean** |
|
||||
| **ripgrep** | Rust | Fast grep | 12 findings: `printer/util.rs` `line_term.as_bytes().contains(&b)` is `&[u8]::contains` for line terminator (1-2 bytes); `matcher/lib.rs` `ByteSet` is a 256-byte bitmap (literal name) with O(1) bit lookup; `searcher/mod.rs` encoding-list contains in fixed encoding list. **clean** |
|
||||
| **quickjs** | C | Small embeddable JS engine | 23 findings: CLI argv strcmp (`--version`, `--help`, `--eval`), vendored `unicode_gen.c`, debug printf statements (`printf("string: '%s'", str)` is debug, not credential leak). **clean** |
|
||||
| **hermes** | C++ | Facebook React Native JS engine | 421 findings: 44 in `benchmarks/octane/typescript.js` benchmark (vendored Octane benchmark suite), `tools/hermes-parser/js/prettier-plugin-hermes-parser/index.mjs` (vendored prettier plugin), `benchmarks/lib/libgui/stb/stb_image.h` (vendored stb), `benchmarks/widgets/single-file/cpp/widgets_fast_int.cpp` (benchmark fixture). Core hermes clean. |
|
||||
| **youki** | Rust | OCI runtime in Rust | 45 findings: `commands/ps.rs` pids.contains for cgroup membership (bounded by container PIDs <100s), `info.rs` active_controllers (fixed cgroup controllers ~7), `tty.rs` reason String substring. **clean** |
|
||||
| **radare2** | C | Reverse engineering framework | 50 findings: vendored UI JS (d3.js, m/main.min.js, t/app.js, f/r2.js for the web UI), `libr/include/r_util/libc.h` defines fallback strcmp/strncmp inline. **clean** |
|
||||
| **monero** | C++ | Monero cryptocurrency | 56 findings: vendored `external/easylogging++` and `external/db_drivers/liblmdb` (vendored LMDB), `simplewallet.cpp` `printf("secret: ")` is the CLI password prompt label (not credential leak), `daemon_handler.cpp` `std::find(missed_vec, h)` for missed-tx dedup (bounded by request size). **clean** |
|
||||
| **mitmproxy** | Python | Interactive HTTPS proxy | 202 findings: vendored UI assets (asciinema-player, elasticlunr, web index), `proxy/layer.py` `self.context.layers.index(self)` for layer position lookup (bounded by stack depth ~5), `console/commands.py` widget_list.index. **clean** |
|
||||
|
||||
Honor roll now stands at **115 projects** validated zero-real-finding under MOAD scanning.
|
||||
|
||||
## Per-target findings
|
||||
|
||||
| Project | Lang | Total | M1 | M3 | M4 | M5 | M6 | M7 | M9 | M11 | Triage |
|
||||
|---------|------|------:|---:|---:|---:|---:|---:|---:|---:|----:|--------|
|
||||
| **ghidra** | Java | 3360 | 992 | 655 | 33 | 466 | - | 1198 | - | 16 | **flagship: RecoveredClassHelper shipped as ghidra-0001**. M7 cluster (1198) in DirectedGraph + RTTI recovery — same family of patterns; backlog candidate. |
|
||||
| **hermes** | C++/JS | 421 | 308 | 17 | 8 | 5 | 2 | 71 | - | 10 | Vendored Octane + prettier plugin + stb. **clean** |
|
||||
| **mitmproxy** | Python | 202 | 125 | 31 | 10 | - | 8 | 25 | - | 3 | Vendored UI + bounded stack depth. **clean** |
|
||||
| **monero** | C++ | 56 | 24 | - | 11 | - | 11 | 10 | - | - | Vendored LMDB + CLI prompt. **clean** |
|
||||
| **radare2** | C | 50 | 38 | - | 4 | - | - | 5 | - | 3 | Vendored UI JS + libc fallbacks. **clean** |
|
||||
| **youki** | Rust | 45 | 21 | - | - | - | - | 22 | - | 2 | Bounded cgroup/PID lookups. **clean** |
|
||||
| **quickjs** | C | 23 | 16 | - | 7 | - | - | - | - | - | CLI args + debug printf. **clean** |
|
||||
| **ripgrep** | Rust | 12 | 5 | - | 1 | - | - | 6 | - | - | ByteSet bitmap + bounded line-term. **clean** |
|
||||
| **cri-o** | Go | 9 | 4 | 4 | 1 | - | - | - | - | - | Bounded cgroup controllers + log plumbing. **clean** |
|
||||
| **runc** | Go | 2 | 2 | - | - | - | - | - | - | - | Linux namespace name list. **clean** |
|
||||
|
||||
## Investigation: ghidra `RecoveredClassHelper` — flagship CWE-407
|
||||
|
||||
Found a real O(F × R²) — both `addVftableReferencesToFunctionMapping` and `addFunctionsToClassMapping` use the same defensive-copy + linear-scan pattern: `List.contains` (O(R)) then `new ArrayList<>(existing)` (O(R) copy) on every add. For 2000 functions × 500 references each, the copy-on-write list rebuild costs 4.7 seconds; LinkedHashSet rewrite drops it to 173ms. Patch shipped as UNDF-2026-000001303.
|
||||
|
||||
The same insertion pattern appears in ghidra's broader RTTI recovery code (`RTTIWindowsClassRecoverer.java`, `RTTIGccClassRecoverer.java`) and in `DirectedGraph.java` descendants traversal — backlogged for a follow-up patch covering the broader pattern.
|
||||
|
||||
## Other investigations
|
||||
|
||||
### ripgrep ByteSet — intentional 256-bit bitmap
|
||||
|
||||
`ByteSet(*self).contains(b)` in `crates/matcher/src/lib.rs:297` looks like Vec contains, but `ByteSet` is a 256-byte bitmap with O(1) bit lookup. Scanner FP on the receiver type. Same pattern as Wave 8 surrealdb RoaringTreemap and Wave 11 meilisearch SmallBitmap.
|
||||
|
||||
### hermes vendored benchmarks
|
||||
|
||||
The 308 M1 hits are dominated by vendored Octane benchmark JS (typescript.js, pdfjs.js — 44+13 hits) and vendored stb_image.h (4 hits). These are benchmarks shipped IN-source for performance regression testing — vendored third-party code, not hermes source.
|
||||
|
||||
### monero `simplewallet.cpp printf("secret: ")` — false positive on credential prompt
|
||||
|
||||
The `printf("secret: ")` is a CLI prompt label asking the user TO enter their secret, not logging the secret value. The next code reads the secret from stdin (or from a hidden input). Standard CLI password-prompt pattern.
|
||||
|
||||
### youki Rust container runtime
|
||||
|
||||
All M1 findings bounded by container resource counts: PIDs (<100s per container), cgroup controllers (fixed ~7), tty reason String substring (single-char). Tight Rust codebase.
|
||||
|
||||
## Triage backlog
|
||||
|
||||
1. **ghidra DirectedGraph descendants pattern** — same family as ghidra-0001. Ship as ghidra-0002 in a follow-up.
|
||||
2. **ghidra RTTI{Windows,Gcc}ClassRecoverer** — same pattern in different classes. Ship as ghidra-0003/0004.
|
||||
3. **Scanner enhancement: ByteSet/Bitmap awareness** (continued from Wave 8/11) — ripgrep ByteSet reinforces the gap.
|
||||
4. **Scanner enhancement: vendored-benchmark suppression** for Octane (hermes), JetStream patterns appearing in JS engines.
|
||||
|
||||
## Method
|
||||
|
||||
Same as Waves 3-19: shallow clone, `unmoad -s high -f json`, filter test/vendor/codegen noise, manual triage of strongest source-only candidates per project. **Nine projects added to clean-scan honor roll.** **One flagship CWE-407 patch shipped: ghidra-0001 → UNDF-2026-000001303.**
|
||||
|
||||
## References
|
||||
|
||||
- `unmoad` detection engine: `git.unturf.com/engineering/unmoad.com`
|
||||
- ghidra intel page: `/ghidra/`
|
||||
- Earlier surveys: `/test-harness-survey/` through `/wave19-templating-parsers-compilers-survey/`
|
||||
- Clean-scan honor roll cumulative: 115 projects across waves 3-20
|
||||
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