update edge labels

core/graph_manager.py

@@ -1,3 +1,5 @@
+# core/graph_manager.py
+
 """
 Graph data model for DNSRecon using NetworkX.
 Manages in-memory graph storage with confidence scoring and forensic metadata.
@@ -50,21 +52,23 @@ class GraphManager:
         self.__dict__.update(state)
         self.date_pattern = re.compile(r'^\d{4}-\d{2}-\d{2}[ T]\d{2}:\d{2}:\d{2}')
 
-    def _update_correlation_index(self, node_id: str, data: Any, path: List[str] = []):
-        """Recursively traverse metadata and add hashable values to the index."""
+    def _update_correlation_index(self, node_id: str, data: Any, path: List[str] = [], parent_attr: str = ""):
+        """Recursively traverse metadata and add hashable values to the index with better path tracking."""
         if path is None:
             path = []
 
         if isinstance(data, dict):
             for key, value in data.items():
-                self._update_correlation_index(node_id, value, path + [key])
+                self._update_correlation_index(node_id, value, path + [key], key)
         elif isinstance(data, list):
             for i, item in enumerate(data):
-                self._update_correlation_index(node_id, item, path + [f"[{i}]"])
+                # Instead of just using [i], include the parent attribute context
+                list_path_component = f"[{i}]" if not parent_attr else f"{parent_attr}[{i}]"
+                self._update_correlation_index(node_id, item, path + [list_path_component], parent_attr)
         else:
-            self._add_to_correlation_index(node_id, data, ".".join(path))
+            self._add_to_correlation_index(node_id, data, ".".join(path), parent_attr)
 
-    def _add_to_correlation_index(self, node_id: str, value: Any, path_str: str):
+    def _add_to_correlation_index(self, node_id: str, value: Any, path_str: str, parent_attr: str = ""):
         """Add a hashable value to the correlation index, filtering out noise."""
         if not isinstance(value, (str, int, float, bool)) or value is None:
             return
@@ -90,10 +94,47 @@ class GraphManager:
             self.correlation_index[value] = {}
         if node_id not in self.correlation_index[value]:
             self.correlation_index[value][node_id] = []
-        if path_str not in self.correlation_index[value][node_id]:
-            self.correlation_index[value][node_id].append(path_str)
         
-    def _check_for_correlations(self, new_node_id: str, data: Any, path: List[str] = []) -> List[Dict]:
+        # Store both the full path and the parent attribute for better edge labeling
+        correlation_entry = {
+            'path': path_str,
+            'parent_attr': parent_attr,
+            'meaningful_attr': self._extract_meaningful_attribute(path_str, parent_attr)
+        }
+        
+        if correlation_entry not in self.correlation_index[value][node_id]:
+            self.correlation_index[value][node_id].append(correlation_entry)
+
+    def _extract_meaningful_attribute(self, path_str: str, parent_attr: str = "") -> str:
+        """Extract the most meaningful attribute name from a path string."""
+        if not path_str:
+            return "unknown"
+        
+        path_parts = path_str.split('.')
+        
+        # Look for the last non-array-index part
+        for part in reversed(path_parts):
+            # Skip array indices like [0], [1], etc.
+            if not (part.startswith('[') and part.endswith(']') and part[1:-1].isdigit()):
+                # Clean up compound names like "hostnames[0]" to just "hostnames"
+                clean_part = re.sub(r'\[\d+\]$', '', part)
+                if clean_part:
+                    return clean_part
+        
+        # Fallback to parent attribute if available
+        if parent_attr:
+            return parent_attr
+        
+        # Last resort - use the first meaningful part
+        for part in path_parts:
+            if not (part.startswith('[') and part.endswith(']') and part[1:-1].isdigit()):
+                clean_part = re.sub(r'\[\d+\]$', '', part)
+                if clean_part:
+                    return clean_part
+        
+        return "correlation"
+
+    def _check_for_correlations(self, new_node_id: str, data: Any, path: List[str] = [], parent_attr: str = "") -> List[Dict]:
         """Recursively traverse metadata to find correlations with existing data."""
         if path is None:
             path = []
@@ -103,10 +144,11 @@ class GraphManager:
             for key, value in data.items():
                 if key == 'source':  # Avoid correlating on the provider name
                     continue
-                all_correlations.extend(self._check_for_correlations(new_node_id, value, path + [key]))
+                all_correlations.extend(self._check_for_correlations(new_node_id, value, path + [key], key))
         elif isinstance(data, list):
             for i, item in enumerate(data):
-                all_correlations.extend(self._check_for_correlations(new_node_id, item, path + [f"[{i}]"]))
+                list_path_component = f"[{i}]" if not parent_attr else f"{parent_attr}[{i}]"
+                all_correlations.extend(self._check_for_correlations(new_node_id, item, path + [list_path_component], parent_attr))
         else:
             value = data
             if value in self.correlation_index:
@@ -117,11 +159,31 @@ class GraphManager:
                 if len(unique_nodes) < 2:
                     return all_correlations # Correlation must involve at least two distinct nodes
 
-                new_source = {'node_id': new_node_id, 'path': ".".join(path)}
+                new_source = {
+                    'node_id': new_node_id, 
+                    'path': ".".join(path),
+                    'parent_attr': parent_attr,
+                    'meaningful_attr': self._extract_meaningful_attribute(".".join(path), parent_attr)
+                }
                 all_sources = [new_source]
-                for node_id, paths in existing_nodes_with_paths.items():
-                    for p_str in paths:
-                        all_sources.append({'node_id': node_id, 'path': p_str})
+                
+                for node_id, path_entries in existing_nodes_with_paths.items():
+                    for entry in path_entries:
+                        if isinstance(entry, dict):
+                            all_sources.append({
+                                'node_id': node_id,
+                                'path': entry['path'],
+                                'parent_attr': entry.get('parent_attr', ''),
+                                'meaningful_attr': entry.get('meaningful_attr', self._extract_meaningful_attribute(entry['path'], entry.get('parent_attr', '')))
+                            })
+                        else:
+                            # Handle legacy string-only entries
+                            all_sources.append({
+                                'node_id': node_id,
+                                'path': str(entry),
+                                'parent_attr': '',
+                                'meaningful_attr': self._extract_meaningful_attribute(str(entry))
+                            })
 
                 all_correlations.append({
                     'value': value,
@@ -163,11 +225,7 @@ class GraphManager:
                     # Skip creating correlation node - would be redundant
                     continue
                 
-                # *** CHANGE START ***
-                # The overly aggressive filtering logic has been removed.
-                # All nodes involved in the correlation will now be used.
                 eligible_nodes = set(corr['nodes'])
-                # *** CHANGE END ***
                 
                 if len(eligible_nodes) < 2:
                     # Need at least 2 nodes to create a correlation
@@ -187,11 +245,12 @@ class GraphManager:
                                 metadata={'values': [value], 'sources': corr['sources'],
                                             'correlated_nodes': list(eligible_nodes)})
                     
-                    # Create edges from eligible nodes to this correlation node
+                    # Create edges from eligible nodes to this correlation node with better labeling
                     for c_node_id in eligible_nodes:
                         if self.graph.has_node(c_node_id):
-                            attribute = corr['sources'][0]['path'].split('.')[-1]
-                            relationship_type = f"c_{attribute}"
+                            # Find the best attribute name for this node
+                            meaningful_attr = self._find_best_attribute_name_for_node(c_node_id, corr['sources'])
+                            relationship_type = f"c_{meaningful_attr}"
                             self.add_edge(c_node_id, correlation_node_id, relationship_type, confidence_score=0.9)
 
             self._update_correlation_index(node_id, attributes)
@@ -199,10 +258,34 @@ class GraphManager:
         self.last_modified = datetime.now(timezone.utc).isoformat()
         return is_new_node
 
-    # *** CHANGE START ***
-    # The following function is no longer needed and has been removed to avoid confusion.
-    # def _filter_nodes_without_direct_edges(self, node_set: set) -> set:
-    # *** CHANGE END ***
+    def _find_best_attribute_name_for_node(self, node_id: str, sources: List[Dict]) -> str:
+        """Find the best attribute name for a correlation edge by looking at the sources."""
+        node_sources = [s for s in sources if s['node_id'] == node_id]
+        
+        if not node_sources:
+            return "correlation"
+        
+        # Use the meaningful_attr if available
+        for source in node_sources:
+            meaningful_attr = source.get('meaningful_attr')
+            if meaningful_attr and meaningful_attr != "unknown":
+                return meaningful_attr
+        
+        # Fallback to parent_attr
+        for source in node_sources:
+            parent_attr = source.get('parent_attr')
+            if parent_attr:
+                return parent_attr
+        
+        # Last resort - extract from path
+        for source in node_sources:
+            path = source.get('path', '')
+            if path:
+                extracted = self._extract_meaningful_attribute(path)
+                if extracted != "unknown":
+                    return extracted
+        
+        return "correlation"
 
     def _has_direct_edge_bidirectional(self, node_a: str, node_b: str) -> bool:
         """
@@ -276,7 +359,7 @@ class GraphManager:
         # Create set of unique sources based on (node_id, path) tuples
         source_set = set()
         for source in existing_sources + new_sources:
-            source_tuple = (source['node_id'], source['path'])
+            source_tuple = (source['node_id'], source.get('path', ''))
             source_set.add(source_tuple)
         
         # Convert back to list of dictionaries