it
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@ -131,7 +131,7 @@ class GraphManager:
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return all_correlations
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return all_correlations
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def add_node(self, node_id: str, node_type: NodeType, attributes: Optional[Dict[str, Any]] = None,
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def add_node(self, node_id: str, node_type: NodeType, attributes: Optional[Dict[str, Any]] = None,
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description: str = "", metadata: Optional[Dict[str, Any]] = None) -> bool:
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description: str = "", metadata: Optional[Dict[str, Any]] = None) -> bool:
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"""Add a node to the graph, update attributes, and process correlations."""
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"""Add a node to the graph, update attributes, and process correlations."""
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is_new_node = not self.graph.has_node(node_id)
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is_new_node = not self.graph.has_node(node_id)
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if is_new_node:
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if is_new_node:
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@ -157,51 +157,162 @@ class GraphManager:
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correlations = self._check_for_correlations(node_id, attributes)
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correlations = self._check_for_correlations(node_id, attributes)
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for corr in correlations:
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for corr in correlations:
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value = corr['value']
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value = corr['value']
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found_major_node_id = None
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# STEP 1: Substring check against all existing nodes
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if isinstance(value, str):
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if self._correlation_value_matches_existing_node(value):
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# Check if the value contains ANY existing major node ID from the entire graph
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# Skip creating correlation node - would be redundant
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for existing_node in self.graph.nodes():
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continue
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# Ensure the existing_node is a major type (domain/ip/asn) and is a substring of the correlation value
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if (self.graph.nodes[existing_node].get('type') in [NodeType.DOMAIN.value, NodeType.IP.value, NodeType.ASN.value] and
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# STEP 2: Filter out node pairs that already have direct edges
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existing_node in value):
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eligible_nodes = self._filter_nodes_without_direct_edges(set(corr['nodes']))
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found_major_node_id = existing_node
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break # Found a major node, no need to check further
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if len(eligible_nodes) < 2:
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# Need at least 2 nodes to create a correlation
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if found_major_node_id:
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continue
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# An existing major node is part of the value; link to it directly.
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for c_node_id in set(corr['nodes']):
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# STEP 3: Check for existing correlation node with same connection pattern
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if self.graph.has_node(c_node_id) and c_node_id != found_major_node_id:
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correlation_nodes_with_pattern = self._find_correlation_nodes_with_same_pattern(eligible_nodes)
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if correlation_nodes_with_pattern:
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# STEP 4: Merge with existing correlation node
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target_correlation_node = correlation_nodes_with_pattern[0]
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self._merge_correlation_values(target_correlation_node, value, corr)
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else:
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# STEP 5: Create new correlation node for eligible nodes only
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correlation_node_id = f"corr_{abs(hash(str(sorted(eligible_nodes))))}"
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self.add_node(correlation_node_id, NodeType.CORRELATION_OBJECT,
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metadata={'values': [value], 'sources': corr['sources'],
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'correlated_nodes': list(eligible_nodes)})
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# Create edges from eligible nodes to this correlation node
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for c_node_id in eligible_nodes:
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if self.graph.has_node(c_node_id):
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attribute = corr['sources'][0]['path'].split('.')[-1]
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attribute = corr['sources'][0]['path'].split('.')[-1]
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relationship_type = f"c_{attribute}"
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relationship_type = f"c_{attribute}"
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self.add_edge(c_node_id, found_major_node_id, relationship_type, confidence_score=0.9)
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self.add_edge(c_node_id, correlation_node_id, relationship_type, confidence_score=0.9)
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continue # Skip creating a redundant correlation node
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# Proceed to create a new correlation node if no major node was found.
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correlation_node_id = f"{value}"
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if not self.graph.has_node(correlation_node_id):
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self.add_node(correlation_node_id, NodeType.CORRELATION_OBJECT,
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metadata={'value': value, 'sources': corr['sources'],
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'correlated_nodes': list(set(corr['nodes']))})
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else: # Update existing correlation node
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existing_meta = self.graph.nodes[correlation_node_id]['metadata']
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existing_nodes = set(existing_meta.get('correlated_nodes', []))
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existing_meta['correlated_nodes'] = list(existing_nodes.union(set(corr['nodes'])))
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existing_sources = {(s['node_id'], s['path']) for s in existing_meta.get('sources', [])}
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for s in corr['sources']:
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existing_sources.add((s['node_id'], s['path']))
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existing_meta['sources'] = [{'node_id': nid, 'path': p} for nid, p in existing_sources]
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for c_node_id in set(corr['nodes']):
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attribute = corr['sources'][0]['path'].split('.')[-1]
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relationship_type = f"c_{attribute}"
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self.add_edge(c_node_id, correlation_node_id, relationship_type, confidence_score=0.9)
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self._update_correlation_index(node_id, attributes)
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self._update_correlation_index(node_id, attributes)
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self.last_modified = datetime.now(timezone.utc).isoformat()
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self.last_modified = datetime.now(timezone.utc).isoformat()
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return is_new_node
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return is_new_node
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def _filter_nodes_without_direct_edges(self, node_set: set) -> set:
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"""
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Filter out nodes that already have direct edges between them.
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Returns set of nodes that should be included in correlation.
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"""
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nodes_list = list(node_set)
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eligible_nodes = set(node_set) # Start with all nodes
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# Check all pairs of nodes
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for i in range(len(nodes_list)):
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for j in range(i + 1, len(nodes_list)):
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node_a = nodes_list[i]
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node_b = nodes_list[j]
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# Check if direct edge exists in either direction
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if self._has_direct_edge_bidirectional(node_a, node_b):
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# Remove both nodes from eligible set since they're already connected
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eligible_nodes.discard(node_a)
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eligible_nodes.discard(node_b)
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return eligible_nodes
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def _has_direct_edge_bidirectional(self, node_a: str, node_b: str) -> bool:
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"""
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Check if there's a direct edge between two nodes in either direction.
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Returns True if node_a→node_b OR node_b→node_a exists.
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"""
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return (self.graph.has_edge(node_a, node_b) or
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self.graph.has_edge(node_b, node_a))
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def _correlation_value_matches_existing_node(self, correlation_value: str) -> bool:
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"""
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Check if correlation value contains any existing node ID as substring.
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Returns True if match found (correlation node should NOT be created).
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"""
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correlation_str = str(correlation_value).lower()
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# Check against all existing nodes
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for existing_node_id in self.graph.nodes():
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if existing_node_id.lower() in correlation_str:
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return True
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return False
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def _find_correlation_nodes_with_same_pattern(self, node_set: set) -> List[str]:
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"""
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Find existing correlation nodes that have the exact same pattern of connected nodes.
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Returns list of correlation node IDs with matching patterns.
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"""
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correlation_nodes = self.get_nodes_by_type(NodeType.CORRELATION_OBJECT)
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matching_nodes = []
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for corr_node_id in correlation_nodes:
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# Get all nodes connected to this correlation node
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connected_nodes = set()
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# Add all predecessors (nodes pointing TO the correlation node)
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connected_nodes.update(self.graph.predecessors(corr_node_id))
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# Add all successors (nodes pointed TO by the correlation node)
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connected_nodes.update(self.graph.successors(corr_node_id))
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# Check if the pattern matches exactly
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if connected_nodes == node_set:
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matching_nodes.append(corr_node_id)
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return matching_nodes
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def _merge_correlation_values(self, target_node_id: str, new_value: Any, corr_data: Dict) -> None:
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"""
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Merge a new correlation value into an existing correlation node.
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Uses same logic as large entity merging.
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"""
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if not self.graph.has_node(target_node_id):
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return
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target_metadata = self.graph.nodes[target_node_id]['metadata']
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# Get existing values (ensure it's a list)
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existing_values = target_metadata.get('values', [])
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if not isinstance(existing_values, list):
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existing_values = [existing_values]
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# Add new value if not already present
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if new_value not in existing_values:
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existing_values.append(new_value)
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# Merge sources
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existing_sources = target_metadata.get('sources', [])
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new_sources = corr_data.get('sources', [])
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# Create set of unique sources based on (node_id, path) tuples
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source_set = set()
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for source in existing_sources + new_sources:
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source_tuple = (source['node_id'], source['path'])
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source_set.add(source_tuple)
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# Convert back to list of dictionaries
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merged_sources = [{'node_id': nid, 'path': path} for nid, path in source_set]
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# Update metadata
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target_metadata.update({
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'values': existing_values,
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'sources': merged_sources,
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'correlated_nodes': list(set(target_metadata.get('correlated_nodes', []) + corr_data.get('nodes', []))),
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'merge_count': len(existing_values),
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'last_merge_timestamp': datetime.now(timezone.utc).isoformat()
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})
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# Update description to reflect merged nature
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value_count = len(existing_values)
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node_count = len(target_metadata['correlated_nodes'])
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self.graph.nodes[target_node_id]['description'] = (
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f"Correlation container with {value_count} merged values "
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f"across {node_count} nodes"
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)
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def add_edge(self, source_id: str, target_id: str, relationship_type: str,
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def add_edge(self, source_id: str, target_id: str, relationship_type: str,
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confidence_score: float = 0.5, source_provider: str = "unknown",
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confidence_score: float = 0.5, source_provider: str = "unknown",
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raw_data: Optional[Dict[str, Any]] = None) -> bool:
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raw_data: Optional[Dict[str, Any]] = None) -> bool:
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@ -1000,6 +1000,46 @@ input[type="text"]:focus, select:focus {
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font-style: italic;
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font-style: italic;
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}
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}
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.correlation-values-list {
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margin-top: 1rem;
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}
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.correlation-value-details {
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margin-bottom: 0.5rem;
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border: 1px solid #333;
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border-radius: 3px;
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}
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.correlation-value-details summary {
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padding: 0.5rem;
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background-color: #3a3a3a;
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cursor: pointer;
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outline: none;
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color: #c7c7c7;
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}
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.correlation-value-details summary:hover {
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background-color: #4a4a4a;
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}
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.correlation-value-details .detail-row {
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margin-left: 1rem;
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margin-right: 1rem;
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padding: 0.5rem 0;
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}
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.correlation-value-details .detail-label {
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color: #999;
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font-weight: 500;
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}
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.correlation-value-details .detail-value {
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color: #c7c7c7;
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word-break: break-all;
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font-family: 'Roboto Mono', monospace;
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font-size: 0.9em;
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}
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@keyframes fadeIn {
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@keyframes fadeIn {
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from {opacity: 0; transform: scale(0.95);}
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from {opacity: 0; transform: scale(0.95);}
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to {opacity: 1; transform: scale(1);}
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to {opacity: 1; transform: scale(1);}
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@ -365,11 +365,24 @@ class GraphManager {
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}
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}
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}
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}
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// Handle merged correlation objects (similar to large entities)
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if (node.type === 'correlation_object') {
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if (node.type === 'correlation_object') {
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const value = node.metadata.value;
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const metadata = node.metadata || {};
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const label = Array.isArray(value) ? `Correlated (${value.length})` : String(value);
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const values = metadata.values || [];
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processedNode.label = this.formatNodeLabel(label, node.type);
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const mergeCount = metadata.merge_count || 1;
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processedNode.title = Array.isArray(value) ? value.join(', ') : value;
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if (mergeCount > 1) {
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// Display as merged correlation container
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processedNode.label = `Correlations (${mergeCount})`;
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processedNode.title = `Merged correlation container with ${mergeCount} values: ${values.slice(0, 3).join(', ')}${values.length > 3 ? '...' : ''}`;
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processedNode.borderWidth = 3; // Thicker border for merged nodes
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} else {
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// Single correlation value
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const value = Array.isArray(values) && values.length > 0 ? values[0] : (metadata.value || 'Unknown');
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const displayValue = typeof value === 'string' && value.length > 20 ? value.substring(0, 17) + '...' : value;
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processedNode.label = `Corr: ${displayValue}`;
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processedNode.title = `Correlation: ${value}`;
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}
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}
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}
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return processedNode;
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return processedNode;
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@ -799,10 +799,51 @@ class DNSReconApp {
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*/
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*/
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generateNodeDetailsHtml(node) {
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generateNodeDetailsHtml(node) {
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if (!node) return '<div class="detail-row"><span class="detail-value">Details not available.</span></div>';
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if (!node) return '<div class="detail-row"><span class="detail-value">Details not available.</span></div>';
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let detailsHtml = '<div class="modal-details-grid">';
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let detailsHtml = '<div class="modal-details-grid">';
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// Section for Incoming Edges (Source Nodes)
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// Handle merged correlation objects similar to large entities
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if (node.type === 'correlation_object') {
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const metadata = node.metadata || {};
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const values = metadata.values || [];
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const mergeCount = metadata.merge_count || 1;
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detailsHtml += '<div class="modal-section">';
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detailsHtml += '<h4>Correlation Details</h4>';
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if (mergeCount > 1) {
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detailsHtml += `<p><strong>Merged Correlations:</strong> ${mergeCount} values</p>`;
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detailsHtml += '<div class="correlation-values-list">';
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values.forEach((value, index) => {
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detailsHtml += `<details class="correlation-value-details">`;
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detailsHtml += `<summary>Value ${index + 1}: ${typeof value === 'string' && value.length > 50 ? value.substring(0, 47) + '...' : value}</summary>`;
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detailsHtml += `<div class="detail-row"><span class="detail-label">Full Value:</span><span class="detail-value">${value}</span></div>`;
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detailsHtml += `</details>`;
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});
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detailsHtml += '</div>';
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} else {
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const singleValue = values.length > 0 ? values[0] : (metadata.value || 'Unknown');
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detailsHtml += `<div class="detail-row"><span class="detail-label">Correlation Value:</span><span class="detail-value">${singleValue}</span></div>`;
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}
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// Show correlated nodes
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const correlatedNodes = metadata.correlated_nodes || [];
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if (correlatedNodes.length > 0) {
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detailsHtml += `<div class="detail-row"><span class="detail-label">Correlated Nodes:</span><span class="detail-value">${correlatedNodes.length}</span></div>`;
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detailsHtml += '<ul>';
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correlatedNodes.forEach(nodeId => {
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detailsHtml += `<li><a href="#" class="node-link" data-node-id="${nodeId}">${nodeId}</a></li>`;
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});
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detailsHtml += '</ul>';
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}
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detailsHtml += '</div>';
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}
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// Continue with standard node details for all node types
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// Section for Incoming Edges (Source Nodes)
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if (node.incoming_edges && node.incoming_edges.length > 0) {
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if (node.incoming_edges && node.incoming_edges.length > 0) {
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detailsHtml += '<div class="modal-section">';
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detailsHtml += '<div class="modal-section">';
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detailsHtml += '<h4>Source Nodes (Incoming)</h4>';
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detailsHtml += '<h4>Source Nodes (Incoming)</h4>';
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@ -812,7 +853,7 @@ class DNSReconApp {
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});
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});
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detailsHtml += '</ul></div>';
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detailsHtml += '</ul></div>';
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}
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}
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// Section for Outgoing Edges (Destination Nodes)
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// Section for Outgoing Edges (Destination Nodes)
|
||||||
if (node.outgoing_edges && node.outgoing_edges.length > 0) {
|
if (node.outgoing_edges && node.outgoing_edges.length > 0) {
|
||||||
detailsHtml += '<div class="modal-section">';
|
detailsHtml += '<div class="modal-section">';
|
||||||
@ -824,24 +865,28 @@ class DNSReconApp {
|
|||||||
detailsHtml += '</ul></div>';
|
detailsHtml += '</ul></div>';
|
||||||
}
|
}
|
||||||
|
|
||||||
// Section for Attributes
|
// Section for Attributes (skip for correlation objects - already handled above)
|
||||||
detailsHtml += '<div class="modal-section">';
|
if (node.type !== 'correlation_object') {
|
||||||
detailsHtml += '<h4>Attributes</h4>';
|
detailsHtml += '<div class="modal-section">';
|
||||||
detailsHtml += this.formatObjectToHtml(node.attributes);
|
detailsHtml += '<h4>Attributes</h4>';
|
||||||
detailsHtml += '</div>';
|
detailsHtml += this.formatObjectToHtml(node.attributes);
|
||||||
|
detailsHtml += '</div>';
|
||||||
|
}
|
||||||
|
|
||||||
// Section for Description
|
// Section for Description
|
||||||
detailsHtml += '<div class="modal-section">';
|
detailsHtml += '<div class="modal-section">';
|
||||||
detailsHtml += '<h4>Description</h4>';
|
detailsHtml += '<h4>Description</h4>';
|
||||||
detailsHtml += `<p class="description-text">${node.description || 'No description available.'}</p>`;
|
detailsHtml += `<p class="description-text">${node.description || 'No description available.'}</p>`;
|
||||||
detailsHtml += '</div>';
|
detailsHtml += '</div>';
|
||||||
|
|
||||||
// Section for Metadata
|
// Section for Metadata (skip detailed metadata for correlation objects - already handled above)
|
||||||
detailsHtml += '<div class="modal-section">';
|
if (node.type !== 'correlation_object') {
|
||||||
detailsHtml += '<h4>Metadata</h4>';
|
detailsHtml += '<div class="modal-section">';
|
||||||
detailsHtml += this.formatObjectToHtml(node.metadata);
|
detailsHtml += '<h4>Metadata</h4>';
|
||||||
detailsHtml += '</div>';
|
detailsHtml += this.formatObjectToHtml(node.metadata);
|
||||||
|
detailsHtml += '</div>';
|
||||||
|
}
|
||||||
|
|
||||||
detailsHtml += '</div>';
|
detailsHtml += '</div>';
|
||||||
return detailsHtml;
|
return detailsHtml;
|
||||||
}
|
}
|
||||||
|
Loading…
x
Reference in New Issue
Block a user