Mindgard
Attack-led AI security platform that finds, validates, and fixes high-impact AI vulnerabilities.
By Mindgard · HQ Boston, US and London, UK · 4.0/5 Value-Position score (estimate)
Positioning guardrails
Best for
- Security, AppSec and red-team groups accountable for AI systems and agents in production
- Enterprises that need evidence-based AI red teaming ahead of audits or AI governance reviews
- Organizations running agentic workflows, RAG applications, or MCP/A2A-connected tools
- GRC teams that need continuous AI risk and compliance reporting rather than one-off pen tests
Ideal size: Security/AppSec team, 50+ employees people · Enterprise or scale-up with AI in production and a security function
Not for
- Teams looking only for runtime prompt guardrails or an AI firewall
- Companies with no models, agents or AI-connected workflows in development or production
- Buyers who want a free, self-serve open-source scanning tool they operate themselves
- Organizations unwilling to let a security vendor assess their AI systems, tools and data paths
Value metrics scorecard
Time-to-Value
Operational in minutes
~1 days to first production value
Total Cost of Ownership
On request
Not published; demo-led enterprise sales (no public price list)
Implementation Friction
2/5
Engineering + admin effort required
Value-Position score
out of 5 · model estimate
Full cost breakdown
Mandatory implementation fee
None
Seat tiers
Not listed
Add-on costs
- None
Company & support
Who is behind Mindgard, and how your team gets help once it is live.
Company
- Founded
- 2022 · 4 yrs in business
- Headquarters
- Boston, US and London, UK
How you get support
We haven’t recorded support channels for Mindgard yet. Nothing here means unverified — not absent.
Market position
Where Mindgard sits against its closest alternatives. Pick any two of cost, speed, friction and buyer score, and up to 9 companies to compare.
Quadrant view
Typical annual cost × Time-to-value
The lines cross at the median of the solutions shown, so about half sit on each side of each line.
Companies on the chart 6 / 10
- Mindgard
- Evinced
- Osano
- Didomi
- Prophet Security
- Bitdefender GravityZone
Add or change companies
Up to 10 companies including Mindgard. Listed closest first.
Stack fit signal
Compatibility with standard B2B ecosystems.
No supported MCP path today, so it cannot be driven from an AI client.
AI & MCP readiness
What Mindgard ships in AI, and what it asks of your ecosystem.
AI features shipped
Vendor pages describe AI governance and AI risk compliance reporting, shadow-AI discovery, automated AI infrastructure crawling, agent hardening and runtime AI protection. No source states which model providers power the platform, whether customers supply model keys, per-action AI logging, training-data use, or AI pricing.
Your data & models
- Trains on your data
- Not recorded — ask the vendor
- Runs on
- Not recorded
- AI pricing
- Not recorded
In your ecosystem
- AI connection
- Not supported
- Model key
- Not recorded
- AI usage audit
- Not recorded
Compliance attestations
* IAPP AIGP certifies individuals, not products. It means named staff hold the credential — not that the platform does.
Bottom line
Mindgard is an offensive AI security platform spun out of a decade of Lancaster University AI security research. It maps an organization's AI attack surface, performs attacker-style reconnaissance, and runs adaptive red teaming against models, agents, tools and infrastructure to expose exploitable vulnerabilities. Findings feed remediation guidance, runtime protection and AI governance reporting, with continuous reassessment as models, prompts and tools change. Deployment is via API, CI/CD, Burp Suite, CLI or one click.
Frequently asked questions
What does Mindgard actually do?
Mindgard is an offensive security platform purpose-built for AI systems and agents. It runs a continuous discover, recon, attack and defend cycle: enumerating AI assets and shadow AI, profiling models, agents and tools the way an attacker would, executing adaptive attacks to find and validate exploitable weaknesses, then supplying evidence, remediation guidance and runtime protection while reassessing as the AI estate changes.
How quickly can we be operational and see first results?
The vendor states Mindgard can be operational in minutes through APIs, CI/CD pipelines, Burp Suite or a single-click workflow, and that it reduces AI risk assessment from weeks to hours without requiring a specialist in-house AI security function or assembling and maintaining multiple testing tools.
What AI systems does Mindgard cover?
AI applications, agents, models, chatbots, agentic workflows, APIs, connected tools and supporting infrastructure, including systems built on open-source or managed models, RAG applications, tool-using agents, and systems connected through MCP or A2A servers.
How does Mindgard differ from open-source tools such as Garak, PyRIT and Promptfoo?
Mindgard's own comparison says those frameworks are useful but must be configured, operated, maintained and interpreted by the customer's own team. Mindgard positions itself as an enterprise-ready offensive security platform that is operational in minutes and adds continuous testing, risk prioritization, remediation guidance, workflow integrations, executive reporting and GRC evidence.
Does Mindgard replace AI guardrails or AI firewalls?
Mindgard states that guardrails and firewalls apply policy to prompts, responses or actions at runtime, while Mindgard tests whether those controls actually hold, degrade or fail as AI systems change. It also assesses beyond the prompt layer to agents, tools, permissions, APIs, data and infrastructure.
How is Mindgard priced?
Mindgard does not publish pricing on its website; the public path is a demo request and contact form, so commercial terms are set through sales. Buyers should ask for the scope of AI systems under test and the assessment cadence to be defined in the contract.