opfor 0.4.0

AI-assisted offensive reconnaissance and attack surface mapping.

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AI-assisted offensive reconnaissance and attack surface mapping.

One generic engine drives every scenario, web, internal network, AI agents, phishing. You change scenario by swapping data, plugins, and knowledge, never by editing the engine.

It mirrors codejury's "generic engine, knowledge as data" decoupling. The difference is that codejury reads code and judges, while opfor acts on live targets: it grows a live situation graph, gates every action by authorized scope, survives async waits, and keeps an audit ledger.

Layers

Layer	What it owns	Form
Capabilities	How to reach a target and report the raw facts	Capability, one tool per verb
Planner	What to try next, gated on facts	RuleSet under a scenario
Knowledge	What a finding is and how severe	Markdown the triage reads
Triage	The verdict, the only place findings are minted	Rule-based or model-backed
Kernel	The blackboard, phase spine, scope, ledger, budget	opfor/core/

The kernel is generic and names no host, contract, or person. A scenario is a plugin under opfor/scenarios/<name>/ that supplies capabilities, a planner, a triage, a declared terminal phase, and a knowledge/ tree.

Install

pip install opfor

The base install is keyless. Triage runs on the operator's Claude Code subscription by default, and a vendor API is used instead when a key is set. For the vendor SDKs install an extra, opfor[anthropic] or opfor[openai].

Use

opfor scenarios
opfor run attacksurface --root example.com

Develop

python -m venv .venv && . .venv/bin/activate
pip install -e ".[dev]"
pytest

See AGENTS.md for the architecture and the non-negotiable invariants.