Evaluation & testing
UK vendor running automated red-team tests against AI models, applications and agents. It profiles the target, enumerates attack surface, executes techniques from a maintained attack library via CLI or SDK, and reports exploitable findings with remediation guidance. Documentation covers testing mechanics rather than audit, retention or access controls.
commercial · generally available · Research snapshot 2026-09-06
Visit the official product source ↗Evaluation & testing · Agent security & threat detection
Useful conversation with: CISO, AI security engineer.
Show me an automated red-team run against my production agent, including which attack techniques were executed and the remediation guidance produced.
Support labels reflect the supplied research. Documentation and vendor claims are not independent product tests. “Not established” means the researcher did not find support; it does not prove a capability is absent.
Documented by provider
Mindgard documents testing applications and models against an ever-growing list of LLM and ML attack techniques, with a quickstart, CLI-based testing, attack library, remediations and SDK reference.
Limit: The documentation index does not list specific attack categories, scoring methodology or evidence retention.
Vendor claim
The product page states Mindgard profiles AI systems the way attackers do by mapping models, agents, tools and behaviours before attack execution, and lists AI attack surface enumeration, agent evaluation and security scanning, guardrail testing and AI risk compliance reporting.
Limit: Marketing page; no reference documentation was found for the compliance reporting or runtime protection claims.
Listing does not imply partnership, supplier status, a working DutyGraph integration, or a compliance certification.
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