Holster Cybersecurity delivers adversarial AI assessment, purple team operations, AI security architecture, and governance advisory to organisations deploying AI at scale. We find the vulnerabilities in your AI systems before attackers do.
Every Holster engagement draws on four interdependent disciplines. We attack to understand exposure, engineer defences to close gaps, design architectures that prevent recurrence, and build governance to sustain security over time.
We execute real-world attack campaigns against your deployed AI systems — LLMs, RAG pipelines, AI agents, and ML classifiers — using the same techniques documented in MITRE ATLAS and exploited by real-world threat actors. Every vulnerability we find is one attackers cannot exploit.
Finding vulnerabilities is only the beginning. We build the detection rules, monitoring frameworks, guardrail configurations, and incident playbooks that convert attack findings into durable defensive capability — capability your security team can operate, measure, and prove to regulators and auditors.
Regulatory obligations for AI are live and enforceable. We build the governance frameworks, AI system inventories, risk registers, and compliance evidence that protect your organisation legally — and give your board and regulators genuine oversight of your AI risk posture.
Secure AI systems must be designed correctly from the outset — not hardened after breaches occur. We design and review the security architectures that underpin AI deployments: access controls, model isolation, API gateway security, and zero-trust principles applied to every layer of the AI stack.
Comprehensive adversarial testing of your AI deployment — from LLM applications and RAG knowledge bases to AI agents and ML classifiers — executed against a structured, gate-controlled attack methodology.
A structured red-versus-blue exercise: your security team attempts real-time detection while our red team executes documented AI attack scenarios — with detection engineering built into every step.
A comprehensive assessment of your AI programme against regulatory obligations and governance best practice — producing the inventory, risk register, and roadmap your organisation needs to be defensible.
Security designed into AI systems from the beginning is structurally more effective — and significantly cheaper — than security retrofitted after a breach. We design, review, and harden the architectures that AI deployments run on.
Traditional penetration testing enhanced by AI — accelerated reconnaissance, deeper vulnerability correlation, and realistic simulation of the AI-powered attacks your organisation will face.
A 7-phase structured assessment mapping your AI systems against EU Regulation 2024/1689 — from prohibited use checks and high-risk classification through technical documentation, conformity assessment preparation, and GPAI model obligations.
A purpose-built offensive assessment targeting AI agent architectures — covering tool abuse, prompt injection chains, memory poisoning, MCP server security, and multi-step exfiltration attacks against systems where AI takes autonomous action in the real world.
A structured audit of your AI management system against ISO/IEC 42001:2023 — the international standard for responsible AI management — delivered across 7 phases aligned to clauses 4–10, with a certification readiness verdict and roadmap at conclusion.
NCSC-backed baseline certification covering all five technical security controls — delivered via the Montpellier questionnaire route or the NCSC Assured Cyber Advisor-supported pathway. CE+ adds independent technical verification by an NCSC Assured assessor against IASME 2024.
Every Holster engagement follows the same disciplined, gate-controlled process. You always know what we are doing, when, and what you will receive at each stage.
Holster was created specifically for AI security — not a traditional penetration testing firm with an AI practice added on. Every methodology, assessment framework, and engagement is designed for the specific attack surface of machine learning systems.
Our red team deploys the same adversarial techniques documented in MITRE ATLAS and exploited by real threat actors. We don't simulate AI attacks — we execute them, within agreed scope, so you understand your real exposure rather than a theoretical one.
Every engagement closes the loop with blue team validation and detection engineering. Clients leave with measurably improved security posture and deployed detection rules — not a report of vulnerabilities to address eventually.
Every technical finding is mapped to its EU AI Act, GDPR, and sector-specific regulatory implication. One engagement serves your CISO, your Data Protection Officer, and your legal team — reducing the compliance overhead significantly.
Beyond finding vulnerabilities and closing detection gaps, Holster designs the security architecture that AI systems should have been built on from the outset — zero-trust access models, secure API gateway design, model isolation, and identity controls that make future attacks structurally harder.
of LLM deployments contain at least one critical injection vulnerability detectable within minutes by an adversarial security assessment. Most organisations have never tested their AI systems.
is the typical pre-exercise AI threat detection rate for organisations without dedicated AI security monitoring. The majority of SIEM deployments contain zero AI-specific detection rules.
maximum penalty for deploying a prohibited AI system. High-risk AI systems without conformity assessments face significant enforcement risk. Most organisations have not formally classified their AI deployments.
Our deliverables are designed to serve three audiences simultaneously — your technical team, your executive leadership, and your board and regulators.
Every finding with reproduction steps, evidence, severity rating, attack framework mapping, business impact, and specific remediation guidance.
A concise non-technical summary for C-suite — risk posture, key findings, regulatory exposure, and investment priorities clearly stated.
Production-ready detection rules for every undetected finding — compatible with your SIEM and ready for immediate deployment.
Pre and post exercise detection rates, MITRE ATLAS coverage map, detection gap analysis, and guardrail effectiveness benchmark.
Phased programme from 30-day critical actions to an 18-month governance maturity plan — with named owners and success criteria.
Every finding mapped to its applicable regulatory obligation — EU AI Act, GDPR, and applicable sector regulation — as audit-ready compliance evidence.
A board-ready deck translating technical findings into business risk language — suitable for audit committee and board-level review.
Complimentary retest of critical and high findings within 90 days. Certificate of remediation issued for all formally closed vulnerabilities.
Representative engagements from organisations deploying AI at scale. All client details anonymised. All findings are real.
A lender had deployed an AI-assisted credit scoring model without adversarial robustness testing. Assessment revealed that structured input manipulation could materially shift credit decisions without triggering any existing fraud controls. The system also lacked GDPR Article 22 documentation and a human oversight mechanism — a compounding regulatory exposure.
A rapidly growing fintech had deployed multiple AI features across its mobile banking platform with no governance documentation and no AI inventory. Shadow AI discovery identified consumer AI tools processing customer data without data processing agreements — a direct exposure under applicable data protection and financial services regulations.
A SaaS platform allowing customer document uploads to an AI knowledge base was found vulnerable to indirect prompt injection. A test document caused the AI to follow injected instructions in all subsequent user responses for hours — undetected. Pre-exercise: zero of eleven attack scenarios detected. Post-exercise: nine had validated detection rules deployed in the client SIEM.
"Holster extracted our system prompt — including a live internal API credential — in under fifteen minutes. The purple team exercise that followed transformed that single finding into the most significant security capability improvement we have made in three years. We now have genuine visibility into AI threats for the first time."
Every day your AI systems operate without adversarial testing, attackers are mapping vulnerabilities you cannot see. The conversation starts with a 45-minute confidential threat briefing — your systems, your risks, no obligation.