AI & LLM Security Testing
Protect what matters with AI & LLM Security Testing
AI is now part of your attack surface. Large language models, AI agents and autonomous workflows introduce risks that traditional testing was never designed to find — prompt injection, insecure tool use, training-data and prompt leakage, and unsafe automation that can act on a user’s behalf. Aesparrow’s AI & LLM Security Testing assesses your AI-powered features the way a real adversary would, aligned to the OWASP Top 10 for LLM Applications and the NIST AI Risk Management Framework.
We test the whole AI stack: the model and its prompts, the retrieval and tool-calling layer, the APIs around it, and the guardrails meant to keep it safe. We attempt prompt injection and jailbreaks, probe for sensitive-data exposure, test whether an agent can be manipulated into unsafe actions, and check the classic application and API security of everything supporting it. You get verified findings, business-impact ratings and clear remediation — plus a free re-test once you have fixed them.
- Certified senior practitioners
- Audit-ready reporting
- Free re-test included
AI & LLM Security Testing — done right, the first time.
Senior practitioners. Verified findings. Free re-test.
Overview
AI & LLM Security Testing is an authorised assessment of your AI-powered features and the systems around them. Because AI introduces new, non-deterministic failure modes, we combine adversarial prompt testing with classic application and API security to give you a complete picture of AI risk.
What we test for
Aligned to the OWASP Top 10 for LLM Applications and NIST AI RMF.
- Prompt injection & jailbreaks — direct and indirect manipulation of model behaviour
- Sensitive data exposure — prompt, training-data and context leakage
- Insecure tool & plugin use — agents taking unsafe or unauthorised actions
- Excessive agency — over-permissioned automation and workflows
- Model & output handling — unsafe rendering, injection via responses
- Supporting API & app security — the endpoints and app around the model
Framework mapping
- OWASP Top 10 for LLM Applications — the AI-specific risk baseline
- NIST AI Risk Management Framework — governance and risk alignment
- ISO/IEC 42001 — AI management system readiness
Deliverables
Executive summary
AI risk posture and priorities for leadership.
Technical findings
Reproducible prompts, evidence and root cause.
Risk ratings
Impact-based severity for AI-specific issues.
Remediation guidance
Practical fixes for prompts, guardrails and code.
Re-test report
Verification that issues are genuinely closed.
Why choose Aesparrow for AI security
- 1
Built for modern AI
LLM apps, agents and AI APIs — not generic testing bolted onto AI.
- 2
OWASP LLM & NIST AI RMF
Structured coverage of the risks unique to AI systems.
- 3
Full-stack assessment
Model, prompts, tools, APIs and guardrails — tested together.
- 4
Free remediation re-test
We verify your fixes and re-issue the report.
If you are shipping AI features — chatbots, copilots, agents or LLM APIs — you need testing built for how they actually fail. Talk to us about an AI security assessment scoped to your models and workflows, and about ISO 42001 readiness for AI governance.
Why AI & LLM Security Testing matters
Independent research on the cost and causes of breaches — the risks this service helps you reduce.
US$4.44M
global average cost of a data breach in 2025.
241 days
mean time to identify and contain a breach in 2025.
20%
of breaches began with exploitation of a vulnerability, up 34% in a year.
Frequently Asked Questions
What kinds of AI systems do you test?
Is prompt injection really a serious risk?
Do you also test the normal application and APIs?
Can you help with ISO 42001 / AI governance?
Ready to secure your business with AI & LLM Security Testing?
Book a free, no-obligation consultation with an Aesparrow practitioner. We’ll scope your needs, explain the approach, and share indicative timelines — no sales script.
Standards & references
Related services
Guides & answers
From our blog
Critical Veeam Vulnerability Exploited to Spread Akira and Fog Ransomware
Threat actors are actively attempting to exploit a now-patched security flaw in Veeam Backup & Replication to deploy Akira and Fog ransomware.
OilRig Exploits Windows Kernel Flaw in Espionage Campaign Targeting UAE and Gulf
The Iranian threat actor known as OilRig has been observed exploiting a now-patched privilege escalation flaw in the Windows kernel in an espionage campaign targeting the UAE and the wider Gulf region.
Supply Chain Attacks Can Exploit Entry Points in Python, npm, and Open-Source Ecosystems
Cybersecurity researchers have found that entry points could be abused across multiple programming ecosystems like PyPI, npm, Ruby Gems, NuGet.
Let’s find the gaps before someone else does.
Tell us what you need tested for a fixed-scope quote, or talk it through with an Aesparrow practitioner — no obligation, no sales script.