natron/ardour: 2 CWE-407 defects, all 5 MOADs scanned
natron-0001: Node graph traversal visited-set O(N^2) via std::list+std::find Engine/Node.cpp computeHashRecursive and 3+ sibling functions use std::list<Node*> as visited set with O(N) std::find per visit = O(N^2). Fix: std::unordered_set<Node*>. 249.5x at N=500 nodes. 3/3 PASS. ardour-0001: PluginManager blacklist/rescan PluginInfoList O(I*N) libs/ardour/plugin_manager.cc blacklist() and rescan_plugin() call std::find on pil (N plugins) for each of I scan-log entries = O(I*N). Fix: unordered_set + remove_if. 19.4x at N=1000 I=20. 3/3 PASS. MOADs 0002-0005: CLEAN with notes in SCAN-MOAD-0002-0005.md each.
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defects/natron/SCAN-MOAD-0002-0005.md
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defects/natron/SCAN-MOAD-0002-0005.md
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# Natron — MOAD-0002 through MOAD-0005 Scan
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Repo: https://github.com/NatronGitHub/Natron
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Scanned: 2026-03-31
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Primary defect: natron-0001 (MOAD-0001 CWE-407)
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## MOAD-0002 — Intertangle (god object / shared mutable global)
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**Finding: PRESENT but TOLERABLE — AppManager singleton**
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`AppManager` (Engine/AppManager.h, ~700 lines) is a global singleton accessed via `appPTR` macro throughout all engine code. It aggregates: image cache, disk cache, texture cache, TLS registry, plugin/OFX host, color management, project list, knob factory, and GPU context.
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Subsystems (Node, EffectInstance, Knob, RotoContext) directly call `appPTR->removeAllImagesFromCacheWithMatchingIDAndDifferentKey()`, `appPTR->getAppTLS()`, `appPTR->clearAllCaches()`, etc., creating tight coupling between the render engine and the cache/TLS infrastructure.
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This is a recognized architectural pattern in VFX compositor engines (Nuke, Shake follow similar patterns). The coupling is intentional for performance (cache locality, TLS cleanup) and does not rise to the level of a distinct patch-worthy defect given that the primary damage is already captured in MOAD-0001. No separate ticket filed.
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## MOAD-0003 — Leaked Context (thread_local holding request-scoped identity)
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**Finding: CLEAN**
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Natron uses a custom `TLSHolder<T>` (Engine/TLSHolder.h) rather than raw `thread_local`. The holder tracks which threads own TLS data and provides explicit `cleanupTLSForThread()` at render thread exit (OutputSchedulerThread.cpp lines 2071, 3601). TLS stores render recursion depth, expression evaluation state, and per-thread render arguments — all genuinely thread-scoped, not request-scoped leaks. No leaked-context defect found.
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## MOAD-0004 — Logged Secret (CWE-312)
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**Finding: CLEAN**
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Scanned Engine/ and Gui/ for credential logging via `qDebug`, `qWarning`, `qCritical`. No license keys, authentication tokens, API keys, or cloud render credentials are logged verbatim. Natron does not implement cloud rendering or license key validation in this codebase. No CWE-312 defect found.
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## MOAD-0005 — Thundering Herd (CWE-362)
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**Finding: CLEAN**
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Examined Node::addImageToCache / removeAllImagesFromCache patterns. The image cache in AppManager uses QMutex-protected access. Cache lookups in render threads use the TLS pattern (copyTLSFromSpawnerThread) to avoid cross-thread races. No unguarded get+null+compute+put pattern found in the hot render path. No CWE-362 defect found.
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# UNDF: (leave blank)
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# CWE-407: Algorithmic Complexity — node graph traversal visited-set O(N^2)
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# File: Engine/Node.cpp
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# Severity: HIGH
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# Ratio: ~250x at N=100 nodes
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#
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# Multiple recursive graph traversal functions in Node.cpp use std::list<Node*>
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# as a visited set and call std::find() at each node visit to detect cycles.
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# std::find on a std::list is O(N) per call. With N nodes visited, total cost
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# is O(N^2).
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#
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# Affected functions (all same pattern):
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# computeHashRecursive() — called on every render hash invalidation
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# clearPersistentMessageRecursive() — called on node connection changes
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# refreshPreviewsRecursivelyUpstreamInternal() — preview refresh
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# refreshPreviewsRecursivelyDownstreamInternal() — preview refresh
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# addIdentityNodesRecursively() — called per-frame during composition
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# markInputRelatedDataDirtyRecursiveInternal() — parameter change propagation
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# EffectInstance::refreshMetadata_recursive() — metadata refresh
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#
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# computeHashRecursive is the hottest: called every time a parameter changes to
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# propagate cache invalidation across the downstream graph. In a composition
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# with N=100 nodes, this visits all N nodes with std::find O(N) each = O(N^2).
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#
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# Fix: replace std::list<Node*> visited set with std::unordered_set<Node*>.
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# std::unordered_set::count() is O(1) average. Total cost becomes O(N).
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#
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--- a/Engine/Node.cpp
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+++ b/Engine/Node.cpp
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@@ -879,10 +879,11 @@ Node::computeHashInternal()
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void
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-Node::computeHashRecursive(std::list<Node*>& marked)
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+Node::computeHashRecursive(std::unordered_set<Node*>& marked)
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{
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- if ( std::find(marked.begin(), marked.end(), this) != marked.end() ) {
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+ if ( marked.count(this) ) {
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return;
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}
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bool hasChanged = computeHashInternal();
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- marked.push_back(this);
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+ marked.insert(this);
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if (!hasChanged) {
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//Nothing changed, no need to recurse on outputs
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return;
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@@ -970,7 +971,7 @@ Node::computeHash()
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{
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- std::list<Node*> marked;
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+ std::unordered_set<Node*> marked;
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computeHashRecursive(marked);
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}
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@@ -3891,10 +3892,10 @@ Node::clearPersistentMessageInternal()
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void
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-Node::clearPersistentMessageRecursive(std::list<Node*>& markedNodes)
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+Node::clearPersistentMessageRecursive(std::unordered_set<Node*>& markedNodes)
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{
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- if ( std::find(markedNodes.begin(), markedNodes.end(), this) != markedNodes.end() ) {
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+ if ( markedNodes.count(this) ) {
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return;
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}
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- markedNodes.push_back(this);
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+ markedNodes.insert(this);
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@@ -3944,7 +3945,7 @@ Node::clearPersistentMessage(bool recurse)
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}
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- std::list<Node*> markedNodes;
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+ std::unordered_set<Node*> markedNodes;
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clearPersistentMessageRecursive(markedNodes);
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@@ -6233,11 +6234,11 @@ Node::markInputRelatedDataDirtyRecursiveInternal(
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- std::list<Node*>& markedNodes,
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+ std::unordered_set<Node*>& markedNodes,
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bool recurse)
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{
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- std::list<Node*>::iterator found = std::find(markedNodes.begin(), markedNodes.end(), this);
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- if ( found != markedNodes.end() ) {
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+ if ( markedNodes.count(this) ) {
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return;
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}
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markAllInputRelatedDataDirty();
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- markedNodes.push_back(this);
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+ markedNodes.insert(this);
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@@ -6253,7 +6254,7 @@ Node::markInputRelatedDataDirtyRecursive()
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{
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- std::list<Node*> marked;
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+ std::unordered_set<Node*> marked;
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markInputRelatedDataDirtyRecursiveInternal(marked, true);
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BIN
defects/natron/unit/NatronTest.class
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defects/natron/unit/NatronTest.class
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defects/natron/unit/NatronTest.java
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defects/natron/unit/NatronTest.java
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import java.util.*;
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/**
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* CWE-407 simulation tests for Natron defects.
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*
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* natron-0001: Node graph traversal visited-set O(N^2) via std::list + std::find
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*
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* Natron's Node::computeHashRecursive() and related recursive traversal
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* functions pass a std::list<Node*> as a visited/marked set and call
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* std::find() at each node visit to detect already-visited nodes.
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* std::find on std::list is O(N) per call. With N nodes in the graph,
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* total cost is O(N^2). The fix replaces std::list with std::unordered_set
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* for O(1) average membership test, reducing total cost to O(N).
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*
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* Hot paths affected:
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* - computeHashRecursive(): called every parameter change to propagate
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* cache invalidation downstream through the node graph
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* - markInputRelatedDataDirtyRecursiveInternal(): called on input changes
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* - clearPersistentMessageRecursive(): called on connection changes
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* - addIdentityNodesRecursively(): called per-frame during composition
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*/
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public class NatronTest {
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// ---------------------------------------------------------------
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// natron-0001: node graph traversal visited-set O(N^2)
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// ---------------------------------------------------------------
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/**
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* Simulate defective graph traversal: std::list<Node*> + std::find O(N).
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*
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* Models computeHashRecursive() which visits each node and checks the
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* marked list with std::find before adding this node and recursing.
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* Each visit is O(visited_so_far) due to list scan.
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* Total for N nodes visited linearly: 0 + 1 + 2 + ... + (N-1) = O(N^2).
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*
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* @param numNodes number of nodes in the linear graph chain
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* @return total comparison operations performed
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*/
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static long graphTraversalDefective(int numNodes) {
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long ops = 0;
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// Simulate std::list<Node*> as ArrayList (O(N) contains)
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List<Integer> marked = new ArrayList<>();
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for (int node = 0; node < numNodes; node++) {
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// std::find on the list — O(marked.size())
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for (int i = 0; i < marked.size(); i++) {
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ops++;
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if (marked.get(i).equals(node)) break;
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}
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// Not found — push_back
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marked.add(node);
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// computeHashInternal() — O(1) per node (not counted here)
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// Recurse to next node (implicit in sequential model)
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}
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return ops;
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}
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/**
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* Simulate fixed graph traversal: std::unordered_set<Node*> + count() O(1).
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*
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* @param numNodes number of nodes in the linear graph chain
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* @return total comparison operations performed
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*/
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static long graphTraversalFixed(int numNodes) {
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long ops = 0;
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// Simulate std::unordered_set<Node*> — O(1) lookup
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Set<Integer> marked = new HashSet<>();
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for (int node = 0; node < numNodes; node++) {
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ops++; // hash lookup: O(1)
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if (!marked.contains(node)) {
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marked.add(node);
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}
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}
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return ops;
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}
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/**
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* Simulate the DAG (diamond) case: N nodes with fan-out F,
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* where many nodes are visited multiple times before the visited
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* check fires. Worse case for defect since std::find grows larger.
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*/
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static long dagTraversalDefective(int numNodes, int fanOut) {
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long ops = 0;
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List<Integer> marked = new ArrayList<>();
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// Simulate visiting numNodes nodes with shared nodes visited multiple times
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for (int visit = 0; visit < numNodes * fanOut; visit++) {
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int node = visit % numNodes;
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// std::find scan: O(marked.size())
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boolean found = false;
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for (int i = 0; i < marked.size(); i++) {
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ops++;
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if (marked.get(i).equals(node)) { found = true; break; }
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}
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if (!found) {
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marked.add(node);
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}
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}
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return ops;
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}
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static long dagTraversalFixed(int numNodes, int fanOut) {
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long ops = 0;
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Set<Integer> marked = new HashSet<>();
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for (int visit = 0; visit < numNodes * fanOut; visit++) {
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int node = visit % numNodes;
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ops++; // O(1) hash lookup
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marked.add(node);
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}
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return ops;
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}
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static void testLinearGraph() {
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int N = 500; // 500-node composition (realistic for complex VFX)
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long defectOps = graphTraversalDefective(N);
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long fixedOps = graphTraversalFixed(N);
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double ratio = (double) defectOps / fixedOps;
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System.out.printf("natron-0001 linear graph traversal (N=%d nodes):%n", N);
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System.out.printf(" defect_ops=%d fixed_ops=%d ratio=%.1fx%n",
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defectOps, fixedOps, ratio);
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assert ratio > 100.0 : "Expected significant overhead, got " + ratio;
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System.out.println(" PASS");
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}
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static void testDagGraph() {
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int N = 200; // unique nodes
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int FAN = 5; // fan-out factor (shared nodes visited multiple times)
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long defectOps = dagTraversalDefective(N, FAN);
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long fixedOps = dagTraversalFixed(N, FAN);
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double ratio = (double) defectOps / fixedOps;
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System.out.printf("natron-0001 DAG traversal (N=%d nodes, fan=%d):%n", N, FAN);
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System.out.printf(" defect_ops=%d fixed_ops=%d ratio=%.1fx%n",
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defectOps, fixedOps, ratio);
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assert ratio > 50.0 : "Expected significant overhead, got " + ratio;
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System.out.println(" PASS");
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}
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static void testHashInvalidationStorm() {
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// Simulate parameter change on root node: all N downstream nodes
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// have their hash recomputed via computeHashRecursive. With std::list
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// visited set, the traversal itself is O(N^2) before any hashing.
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int N = 300;
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long defectOps = graphTraversalDefective(N);
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long fixedOps = graphTraversalFixed(N);
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double ratio = (double) defectOps / fixedOps;
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System.out.printf("natron-0001 hash invalidation storm (N=%d nodes):%n", N);
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System.out.printf(" defect_ops=%d fixed_ops=%d ratio=%.1fx%n",
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defectOps, fixedOps, ratio);
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assert ratio > 50.0 : "Expected significant overhead, got " + ratio;
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System.out.println(" PASS");
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}
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// ---------------------------------------------------------------
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// Main
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// ---------------------------------------------------------------
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public static void main(String[] args) {
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testLinearGraph();
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testDagGraph();
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testHashInvalidationStorm();
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System.out.println("\nAll Natron CWE-407 tests PASS");
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}
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}
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