🛡️

AI Agent Red Team Cost Calculator

Estimate what it costs to continuously adversarial-test an AI agent across prompt injection, jailbreak, fuzzing, and multimodal attack surfaces.

Test program

Last updated: 2026-07-04. See notes.

Monthly API cost

Review labor cost

Total program cost

Cheapest provider

Provider / Model Input / 1M Cached / 1M Output / 1M Monthly API Per 1k tests Best for
OpenAI GPT-4o
gpt-4o
$2.50 $1.250 $10.00 Strong refusal behavior and multimodal adversarial tests
OpenAI GPT-4o-mini
gpt-4o-mini
$0.15 $0.075 $0.60 Cheap high-volume fuzzing
Anthropic Claude 3.5 Sonnet
claude-3-5-sonnet-20240620
$3.00 $3.750 $15.00 Long-context constitutional and policy tests
Anthropic Claude 3 Haiku
claude-3-haiku-20240307
$0.25 $0.030 $1.25 Fast, cheap red-team sweeps
Google Gemini 1.5 Pro
gemini-1.5-pro
$3.50 $10.50 Massive context and multimodal adversarial tests
Google Gemini 1.5 Flash
gemini-1.5-flash
$0.35 $1.05 Low-latency, high-volume fuzzing
Groq Llama 3.1 70B
llama-3.1-70b-versatile
$0.59 $0.79 Fast open-weight inference
Together AI Llama 3.1 70B
llama-3.1-70b
$0.90 $0.90 Open-weight fine-tuning hub

Test-type breakdown

Shows how the severity mix distributes tests and weighted tokens across categories.

Prompt Injection Scan

Direct and indirect prompt injection attempts using curated payloads.

0% of tests • Medium effort

Jailbreak / Refusal Evasion

Roleplay, encoding, translation, and multi-turn jailbreak templates.

0% of tests • Medium effort

Adversarial Fuzzing

Random and semantically preserved perturbations to probe robustness.

0% of tests • Low effort

Multimodal Adversarial

Image, audio, and document payloads designed to bypass safety filters.

0% of tests • High effort

Policy / PII Compliance

Tests for PII leakage, harmful content, and policy violations.

0% of tests • Medium effort

Frequently asked questions

How much does automated LLM red-teaming cost per month?

For a small agent with 1,000 tests per month, costs usually run $50-500. A production agent with 50,000+ adversarial tests can cost $2,000-20,000/month in API tokens alone, before labor and platform fees.

Which test type drives the most cost?

Multimodal adversarial tests and policy/PII compliance tests drive the highest per-test cost because they use longer prompts and require larger outputs. High-volume fuzzing is usually the cheapest per-test category.

Does this include human red-team labor?

No. The calculator adds an optional review-hours estimate based on failed-test rate. Add your own security engineer, bug-bounty, or managed red-team fees on top.

What tools can run these tests?

Open-source options include Garak, PyRIT, TextAttack, and AutoDAN. Commercial layers such as Lakera Guard, Arthur Shield, and Robust Intelligence add policy and detection on top of raw generation cost.

Prices are per 1M tokens in USD and based on public provider pricing. Test-type multipliers capture prompt complexity and required retries. Add labor and platform costs on top.

🤖 Use this tool in your agent

✓ Agent-ready code

Copy the snippet below into your agent, newsletter, or script. The tool page at hermesdispatch.dev/tools/agent-redteam-cost-calculator/ is the canonical contract: inputs, outputs, and formulas.

python
# Hermes Dispatch Tool — AI Agent Red Team Cost Calculator
# Source: https://hermesdispatch.dev/tools/agent-redteam-cost-calculator/
# Description: Estimate cost to red-team an AI agent based on scope, provider, and severity mix.
# License: MIT (generated by hermesdispatch.dev)
#
# INSTALL:
#   1. Save this file as ~/.hermes/hermes-agent/tools/agent_redteam_cost_calculator.py
#   2. Restart Hermes or run /reset in a session
#   3. The tool auto-registers if Hermes uses auto-discovery of tools/*.py
#
# MANUAL REGISTRY (if auto-discovery is off):
#   from tools.agent_redteam_cost_calculator import register
#   register()

import json

DATA = {}

def _ok(result):
    return json.dumps({"success": True, "data": result}, indent=2)

def _err(message):
    return json.dumps({"success": False, "error": message}, indent=2)


TOOL_NAME = "agent_redteam_cost_calculator"
TOOLSET = "agents"

SCHEMA = {
  "type": "function",
  "function": {
    "name": "agent_redteam_cost_calculator",
    "description": "Estimate cost to red-team an AI agent based on scope, provider, and severity mix.",
    "parameters": {
      "type": "object",
      "properties": {
        "provider_daily_rate": {
          "type": "number",
          "description": "Daily rate for red-team provider in USD."
        },
        "days": {
          "type": "integer",
          "description": "Number of red-team days."
        },
        "tests_per_day": {
          "type": "integer",
          "description": "Average tests run per day."
        },
        "remediation_hours": {
          "type": "number",
          "description": "Hours of remediation per high-severity finding."
        }
      },
      "required": []
    }
  }
}

def _run(args):
    rate = float(args.get("provider_daily_rate", 4000))
    days = int(args.get("days", 5))
    tests = int(args.get("tests_per_day", 20))
    rem_hours = float(args.get("remediation_hours", 8))
    engagement_cost = rate * days
    total_tests = tests * days
    estimated_high = max(1, int(total_tests * 0.15))
    remediation_cost = estimated_high * rem_hours * 150
    total = engagement_cost + remediation_cost
    return _ok({
        "engagement_cost": round(engagement_cost, 2),
        "remediation_cost": round(remediation_cost, 2),
        "total_estimated_cost": round(total, 2),
        "total_tests": total_tests,
        "estimated_high_severity_findings": estimated_high
    })

def HANDLER(args):
    try:
        return _run(args)
    except Exception as e:
        return _err(str(e))


def register():
    """Manual registry hook. Import and call this to register with Hermes."""
    try:
        from tools.registry import registry
        registry.register(
            name=TOOL_NAME,
            toolset=TOOLSET,
            schema=SCHEMA,
            handler=HANDLER,
        )
    except ImportError:
        print("Hermes registry not found; skipping manual registration.")

if __name__ == "__main__":
    # CLI smoke test
    print(HANDLER({}))

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