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AI Security Audit & Remediation That Finds and Fixes AI Risks Before Attackers Do
Test Microsoft Copilot, AI agents, and custom AI applications against AI-specific attack techniques, manually validate every finding, and remediate the vulnerabilities that create real business risk.
10 OWASP LLM
Risk Categories Assessed
4 Phases
Scope, Test, Remediate & Retest
100% of Reported
Findings Manually Validated
Find Out What Your AI Can Be Made to Do
Once AI moves into production, security is no longer only about what the system was designed to do. The real question is what an attacker, malicious user, compromised document, or over-permissioned agent could make it do. Exigo Tech's AI Security Audit & Remediation tests Microsoft 365 Copilot environments, Copilot Studio agents, Microsoft Foundry applications, and other LLM-powered systems against AI-specific attack paths.
Microsoft Partner
Independent Assurance
An outside view of whether your AI estate is secure, controlled and behaving as intended.
Real Attacks, Not Checklists
Automated adversarial testing plus manual red teaming across prompts, data, tools and integrations.
Findings You Can Trust
Every issue confirmed by hand, with evidence, so teams fix real risks rather than chase noise.
Audit-Ready Evidence
Results mapped to OWASP, NIST AI RMF and MITRE ATLAS that boards, auditors and regulators recognise.
Gaps Closed, Not Just Reported
A prioritised fix plan, optional hands-on remediation and a retest to confirm closure.
Core Offerings: AI Security Audit & Remediation Services
The engagement moves from understanding your AI attack surface through adversarial testing, actionable remediation, and verification that identified weaknesses have been addressed.
AI Estate Inventory & Threat Model
›
Adversarial Testing & Red Teaming
›
Risk-Rated Audit Report
›
Prioritised Remediation Plan
›
Remediation Support & Retest
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We map your AI systems, including Copilots, Copilot Studio agents, Foundry apps and third-party assistants, with their data flows, permissions and trust boundaries, then agree which systems carry the most risk and should be tested first.
We combine automated attack tools with manual testing across all ten OWASP LLM categories, including direct and indirect prompt injection, sensitive data disclosure, excessive agency, system prompt leakage, RAG weaknesses and runaway consumption.
You receive confirmed findings with evidence, severity scoring, framework mapping and a plain-language summary of business impact for executives.
We rank fixes by risk and effort, such as Prompt Shields and content filtering, least-privilege agent permissions, approval steps, data loss prevention and output validation, with a named owner for each fix and a clear note on which findings need action before wider rollout.
Our engineers can apply or guide the agreed fixes, then retest each finding and issue a closure attestation for your records, ready to share with auditors and your board.
Talk to Our Experts
Business Outcomes Enabled
Fewer Surprises in Production
Find weaknesses in a controlled test, not through an incident or a customer complaint.
Confident Board Reporting
Give leaders and auditors clear, framework-mapped evidence of how AI risk is managed.
Safer Scaling
Expand Copilot, agents and AI apps knowing the controls have been tested.
Focused Security Spend
Fix the issues that matter most first, rather than spreading effort and budget thinly.
Stronger Customer Trust
Show clients and partners that your AI systems have been independently tested.
Fewer Surprises in Production
Find weaknesses in a controlled test, not through an incident or a customer complaint.
Confident Board Reporting
Give leaders and auditors clear, framework-mapped evidence of how AI risk is managed.
Safer Scaling
Expand Copilot, agents and AI apps knowing the controls have been tested.
Focused Security Spend
Fix the issues that matter most first, rather than spreading effort and budget thinly.
Stronger Customer Trust
Show clients and partners that your AI systems have been independently tested.
Know How Your AI Holds Up Before Someone Else Tests It
Book an AI security audit and get an independent, evidence-based view of your AI risks, a clear plan to fix them and confirmation that the fixes work.
Partner Ecosystem
STORIES OF IMPACT
CASE STUDY
LATEST THINKING
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Learn moreAn AI security audit is a structured test of your AI systems, such as Microsoft 365 Copilot, agents and LLM-powered apps, against AI-specific attacks. It covers prompt injection, data leakage, excessive agency and other risks in the OWASP Top 10 for LLM Applications, and ends with confirmed findings, a prioritised fix plan and a retest.
A standard penetration test looks at networks, servers and web applications. It does not test how a model responds to manipulated prompts, poisoned documents or misuse of agent tools. An AI security audit focuses on those AI-specific paths, and works best alongside your existing penetration testing and security assessments.
We test against every category in the OWASP Top 10 for LLM Applications and map findings to the NIST AI Risk Management Framework and MITRE ATLAS. For agents that plan, use tools and act on their own, we also draw on OWASP guidance for agentic applications, so newer agent risks are covered too.
Yes. The audit tests real, deployed AI systems, so it usually follows a Copilot rollout, an agent build or an AI application launch. If you are still planning, start with an AI readiness assessment or governance work, then audit once the first systems are live and in use.
We agree scope, test accounts and timing with you before any testing begins. Most testing runs against non-production environments or controlled test accounts, so end users are not affected. Any testing in production is planned with your team in advance and kept within agreed limits.
AI estates change quickly as new agents, data sources and models are added. We recommend retesting after major changes and at least once a year for systems in active use. Many organisations pair the audit with ongoing monitoring, such as Microsoft Defender for Cloud AI threat protection, between audits.
Yes. We run AI security audits for organisations across Australia, including Sydney, Melbourne, Adelaide and Wollongong. Scoping and threat modelling can run on-site or online, and testing is delivered by our security and AI specialists, so findings reflect both attacker techniques and how your AI systems are actually built.
The audit tests whether your AI systems can expose personal information, which supports your obligations under the Privacy Act 1988, including the Notifiable Data Breaches scheme. We flag findings with privacy impact and where legal advice may be needed. Final compliance depends on your environment, data and legal obligations.
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