Attack Chain Planner (research/chain.py)

Computes weighted shortest exploitation paths in a Neo4j attack graph, integrating edge difficulty, severity, and PoC validation to plan multi-step attack chains.

# Source: https://github.com/mperkins0155/Decepticon-Cobaltai | License: Apache-2.0 | Copyright You must retain, in the Source form of any Derivative Works
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"""Attack-chain planner — Neo4j Cypher-native path search.

Given a Neo4j attack graph, compute multi-hop exploitation paths from
``Entrypoint`` nodes to ``CrownJewel`` nodes using APOC's weighted
shortest-path algorithms. The cost model combines:

- edge weight (analyst-assigned difficulty, lower = easier)
- vulnerability severity (critical shrinks cost, info grows it)
- node-level validation state (validated PoCs halve the cost)

All path computation runs inside Neo4j via Cypher — no Python-side
graph traversal. Results are returned as plain data structures that
callers c

... (truncated -- full source via MCP)