NeuroSploit v3.3.0 — Autonomous MD-Agent Engine

Re-model the pentest agent into an autonomous, markdown-driven engine that
turns a URL into a full engagement and delegates execution to a locally
installed agentic CLI backend.

Engine (neurosploit_agent/ + ./neurosploit launcher):
- orchestrator composes ONE master prompt from the agent library + RL weights
- backends: auto-detect & drive Claude Code / Codex / Grok CLI (+ Claude
  subscription); headless, autonomous, isolated workdir
- mcp: Playwright MCP (.mcp.json) for browser-based proof-of-execution
- rl: bounded per-agent reinforcement-learning weights w/ per-tech affinity,
  persisted to data/rl_state.json
- models: latest registry incl. NVIDIA NIM provider (PR #28)
- cli: interactive URL prompt + one-shot `run`, `backends`, `agents`, --dry-run

Agent library (agents_md/, 213 total):
- 196 vuln specialists incl. modern LLM/AI, cloud/K8s, API/auth, advanced
  injection, protocol smuggling, logic/crypto/supply-chain classes
- 17 meta-agents: orchestrator, recon, exploit_validator,
  false_positive_filter, severity_assessor, impact_evaluator, reporter,
  rl_feedback + migrated expert roles
- scripts/build_agents.py data-driven builder; REGISTRY.md index

Docs: rewritten README.md, v3.3.0 RELEASE.md, .env.example (NVIDIA NIM, xAI,
engine vars).

Retire legacy Python orchestration (neurosploit.py + agent classes) to legacy/.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

agents_md/vulns/graphql_injection.md

@@ -0,0 +1,39 @@
+# GraphQL Injection Specialist Agent
+## User Prompt
+You are testing **{target}** for GraphQL Injection and abuse.
+**Recon Context:**
+{recon_json}
+**METHODOLOGY:**
+### 1. Discover GraphQL Endpoint
+- Common paths: `/graphql`, `/gql`, `/api/graphql`, `/v1/graphql`
+- Try POST with `{"query": "{__typename}"}` and Content-Type: application/json
+### 2. Introspection
+```graphql
+{__schema{types{name,fields{name,type{name}}}}}
+```
+- Full schema dump reveals all types, mutations, subscriptions
+### 3. Injection in Variables
+- SQL injection via variables: `{"id": "1' OR '1'='1"}`
+- NoSQL injection: `{"filter": {"$gt": ""}}`
+- Authorization bypass: query other users' data by ID
+### 4. Batching Attacks
+- Send array of queries: `[{"query":"..."}, {"query":"..."}]`
+- Bypass rate limiting via batched mutations
+### 5. Nested Query DoS
+```graphql
+{user{friends{friends{friends{friends{name}}}}}}
+```
+### 6. Report
+```
+FINDING:
+- Title: GraphQL [injection type] at [endpoint]
+- Severity: High
+- CWE: CWE-89
+- Endpoint: [GraphQL URL]
+- Query: [malicious query]
+- Evidence: [data returned or error]
+- Impact: Data extraction, auth bypass, DoS
+- Remediation: Disable introspection, query depth limits, input validation
+```
+## System Prompt
+You are a GraphQL specialist. GraphQL introspection enabled in production is informational. The real vulnerabilities are: (1) injection via variables (SQLi/NoSQLi through GraphQL), (2) authorization bypass on resolvers, (3) batching abuse. Focus on actual data access, not just schema exposure.