Autonomous Cyber Red Team MCP Server

Adversarial attack graph simulation with advanced mathematical modeling for AI agents via the Model Context Protocol. This MCP server orchestrates 15 cybersecurity data sources and applies 8 mathematical frameworks -- POSG belief-space planning, AND-OR A* exploit chain synthesis, Hawkes process vulnerability forecasting, Colonel Blotto game-theoretic defense allocation, Exp3 adversary modeling, absorbing Markov chain lateral movement analysis, GPD extreme value tail risk, and replicator dynamics threat evolution -- to deliver quantitative cyber risk intelligence.

What data can you access?

Data Point	Source	Coverage
CVE vulnerability data with CVSS scores	NVD CVE Search	All published CVEs
Known exploited vulnerabilities	CISA KEV Catalog	Actively exploited CVEs
Internet-wide host and service data	Censys Search	IPv4 scan data
DNS records and configuration	DNS Lookup	Any domain
SSL/TLS certificate data	SSL Certificate Search	Certificate transparency
Domain registration data	WHOIS Lookup	All TLDs
IP geolocation and ASN mapping	IP Geolocation	Global coverage
Website technology identification	Tech Stack Detector	Any website
Security tools and exploit code	GitHub Repo Search	All public repos
Security Q&A discussions	StackExchange Search	Security communities
Security news and discussions	Hacker News Search	Tech community
US Treasury sanctions	OFAC Sanctions Search	SDN list
Global sanctions and watchlists	OpenSanctions Search	100+ programs
Security website changes	Website Change Monitor	Tracked sites
Cybersecurity economic data	FRED Economic Data	Market indicators

MCP Tools

Tool	Price	Description
simulate_attack_defense_posg	$0.04	Simulate attack-defense as a Partially Observable Stochastic Game via HSVI2 point-based value iteration on belief space with alpha-vector pruning. Returns optimal attack path, defense allocation, and game value.
synthesize_exploit_chains	$0.04	Synthesize multi-step exploit chains via AND-OR graph A* search with CVSS admissible heuristic. Finds optimal-cost attack paths from entry points to high-value targets.
predict_vulnerability_emergence	$0.04	Predict vulnerability emergence using Hawkes self-exciting point process with power-law kernel. Forecasts CVE clustering, burst probability, and 30/90-day vulnerability counts.
optimize_defender_allocation	$0.04	Optimize security resource allocation using Colonel Blotto game theory with asymmetric attacker-defender budgets. Finds Nash equilibrium defense strategy via fictitious play.
model_adaptive_adversary	$0.04	Model adversary learning via Exp3 multi-armed bandit with importance-weighted rewards. Predicts which attack techniques adapt fastest against defenses.
compute_lateral_movement_risk	$0.04	Compute lateral movement risk using absorbing Markov chain fundamental matrix N=(I-Q)^-1. Includes epidemic threshold analysis for supercritical compromise spread.
assess_zero_day_tail_risk	$0.04	Assess zero-day tail risk using Generalized Pareto Distribution extreme value theory. Computes VaR, CVaR, return periods, and portfolio cyber risk.
forecast_threat_landscape_evolution	$0.04	Forecast threat landscape evolution using replicator dynamics. Classifies techniques as EMERGING/GROWING/MATURE/DECLINING with evolutionary stable strategy identification.

Data Sources

• NVD CVE Search -- National Vulnerability Database with CVSS severity scores, CWE classifications, and affected products
• CISA KEV Catalog -- Cybersecurity and Infrastructure Security Agency Known Exploited Vulnerabilities with remediation deadlines
• Censys Search -- Internet-wide scan data revealing exposed services, open ports, and certificate information
• DNS Lookup -- DNS record enumeration including A, AAAA, MX, TXT, CNAME, and security records
• SSL Certificate Search -- Certificate transparency logs for subdomain discovery and certificate chain validation
• WHOIS Lookup -- Domain registration details, registrar information, and ownership data
• IP Geolocation -- IP address to geographic location mapping with ASN and ISP identification
• Tech Stack Detector -- Website technology identification for vulnerability matching
• GitHub Repo Search -- Open-source exploit code, proof-of-concept repositories, and security tools
• StackExchange Search -- Security community Q&A for technique discussions and vulnerability context
• Hacker News Search -- Technology community discussions on vulnerabilities and security incidents
• OFAC Sanctions Search -- Treasury SDN list for threat actor attribution
• OpenSanctions Search -- Multi-jurisdiction watchlists for attribution and geopolitical context
• Website Change Monitor -- Security advisory and policy page change detection
• FRED Economic Data -- Cybersecurity spending and cyber insurance market data

How the scoring works

Each tool implements a distinct mathematical framework applied to the attack graph built from all 15 data sources.

POSG Belief-Space Planning (Tool 1): HSVI2 point-based value iteration solves the attack-defense interaction as a Partially Observable Stochastic Game on the belief simplex. Alpha-vector pruning maintains tractability on this NEXPTIME-complete problem.

AND-OR A Exploit Chains* (Tool 2): AND nodes require all prerequisites satisfied; OR nodes need any single one. The CVSS admissible heuristic h(n) = max CVSS on remaining path guarantees optimality.

Hawkes Vulnerability Forecasting (Tool 3): Self-exciting intensity function with power-law kernel captures long-memory CVE clustering. Thinning simulation forecasts 30-day and 90-day vulnerability counts.

Colonel Blotto Game Theory (Tool 4): Nash equilibrium via fictitious play on the marginal polytope for asymmetric attacker-defender budget allocation across security domains.

Exp3 Adversary Modeling (Tool 5): Weight update w_i(t+1) = w_i(t) * exp(eta * r_hat / K) with importance-weighted rewards tracks adversary learning across attack techniques.

Absorbing Markov Lateral Movement (Tool 6): Fundamental matrix N = (I-Q)^-1 gives expected steps to compromise. Epidemic threshold analysis determines if compromise spreads supercritically through the network.

GPD Zero-Day Tail Risk (Tool 7): Generalized Pareto Distribution fitted to CVSS exceedances. Returns VaR(95%), VaR(99%), CVaR, and return periods for cyber portfolio risk.

Replicator Dynamics Evolution (Tool 8): dx_i/dt = x_i(f_i - phi) identifies evolutionary stable strategies resistant to invasion, classifying threat techniques by lifecycle stage.

How to connect this MCP server

Claude Desktop

Add to your claude_desktop_config.json:

{
  "mcpServers": {
    "autonomous-cyber-red-team": {
      "url": "https://autonomous-cyber-red-team-mcp.apify.actor/mcp"
    }
  }
}

Programmatic (HTTP)

curl -X POST https://autonomous-cyber-red-team-mcp.apify.actor/mcp \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_APIFY_TOKEN" \
  -d '{"jsonrpc":"2.0","method":"tools/call","params":{"name":"synthesize_exploit_chains","arguments":{"query":"apache log4j corporate network"}},"id":1}'

This MCP server also works with Cursor, Windsurf, Cline, and any other MCP-compatible client.

Use cases for cyber red team intelligence

Penetration Testing Automation

Use synthesize_exploit_chains to identify critical multi-step attack paths through infrastructure. The A* search guarantees optimal-cost chains, prioritizing remediation efforts.

Security Budget Optimization

Apply optimize_defender_allocation to determine Nash equilibrium defense spending across security domains. Identifies dominated strategies and optimal budget distribution.

Vulnerability Management Forecasting

Predict vulnerability disclosure rates with predict_vulnerability_emergence to plan patch cycles. The Hawkes process identifies clustering patterns and burst probability for specific technologies.

Cyber Insurance Pricing

Quantify tail risk with assess_zero_day_tail_risk using GPD extreme value theory. VaR and CVaR metrics enable actuarial pricing of cyber insurance portfolios.

Threat Intelligence Strategy

Forecast which attack techniques will dominate with forecast_threat_landscape_evolution. Replicator dynamics identifies emerging threats before they become prevalent.

Network Segmentation Validation

Validate segmentation effectiveness with compute_lateral_movement_risk. The epidemic threshold analysis reveals whether compromise can spread supercritically through the network.

How much does it cost?

This MCP server uses pay-per-event pricing at $0.04 per tool call with no subscription fees.

The Apify Free plan includes $5 of monthly platform credits -- enough for 125 tool calls at no cost.

Each tool call runs up to 15 actors in parallel for comprehensive data collection.

Example costs:

• Full POSG attack-defense simulation: $0.04
• Exploit chain synthesis for target network: $0.04
• Complete 8-tool assessment: $0.32

How it works

1. Your AI agent calls a tool via MCP (e.g., synthesize_exploit_chains with a target query)
2. The server dispatches parallel queries to up to 15 Apify actors (NVD, CISA KEV, Censys, DNS, SSL, WHOIS, etc.)
3. Results are combined into an attack graph with nodes (assets, vulnerabilities) and edges (attack paths)
4. The specified mathematical framework is applied to the attack graph
5. A structured JSON response is returned with quantitative results and graph summary

All 15 data sources are queried in parallel. Response time is 60-180 seconds depending on result volume.

FAQ

Q: Is this active or passive scanning? A: Entirely passive. The server uses publicly available vulnerability databases, certificate transparency logs, DNS records, and community discussions. No packets are sent to target infrastructure.

Q: What format are results returned in? A: All tools return structured JSON via the MCP protocol with mathematical outputs (game values, probability distributions, equilibria) alongside graph summaries.

Q: Can this replace a human red team? A: No. This provides quantitative analysis to augment red team operations. Human judgment is essential for interpreting results and validating attack feasibility.

Q: Is it legal to use this data? A: This tool accesses only publicly available data from government registries (NVD, CISA) and open databases. See Apify's guide on web scraping legality.

Q: How accurate are the vulnerability predictions? A: The Hawkes process model is calibrated on historical CVE data. Predictions are probabilistic forecasts, not certainties. Accuracy improves with more historical data (use higher maxResults).

Q: Can I run multiple tools on the same target? A: Yes. Each tool provides a different analytical lens on the same attack surface. Running all 8 tools gives a comprehensive security assessment for $0.32 total.

Related MCP servers

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adversarial-corporate-opacity-mcp	Corporate structure opacity and shell company detection

Integrations

This MCP server runs on the Apify platform and supports:

• Scheduling -- Set up recurring threat landscape assessments via Apify Schedules
• Webhooks -- Trigger alerts when vulnerability emergence predictions exceed thresholds
• API access -- Call tools directly via the Apify API for SIEM/SOAR integration
• Dataset export -- Export results as JSON for integration with security platforms