Security and compliance
AI system security
AI system security addresses the risks specific to systems built on language models and agents: prompt injection, data exfiltration through model outputs, over-privileged tools, and model access control. Hexploits reviews and hardens AI systems using the OWASP guidance for LLM applications and the governance patterns it built for swarmd.ai.
A named engineer replies within one working day. A written scope and an indicative price within two.
Who this is for
- Businesses about to connect an AI assistant or agent to internal systems.
- AI vendors answering enterprise security questionnaires.
- Security teams asked to approve a system they have not seen before.
What you get
Deliverables, not slogans. Each one appears in the statement of work.
- A threat model for the AI system: inputs, tools, data sources and trust boundaries.
- Controls: input and output filtering, scoped tool credentials, rate limits, tenant isolation, logging.
- Testing for prompt injection and data leakage, with results.
- Model access control and secrets management.
- Documentation for security review and customer questionnaires.
Our engineers work across the major languages, frameworks and cloud platforms. We build on the stack you already run, with technology choices explained in writing before work begins.
How it is delivered
The same four stages as every Hexploits engagement, applied to this capability.
Stage 1
Model the threats
What the system can reach, who can influence its inputs, and what an attacker would gain.
Stage 2
Harden
Least-privilege tools, filtering, isolation and logging built in.
Stage 3
Test
Adversarial testing against the deployed system, repeated on change.
Stage 4
Monitor
Anomalous prompts, tool calls and outputs alert an engineer.
How success is measured
Every engagement agrees its measures and the measurement period in writing before work starts.
- Adversarial test results before and after hardening.
- Tools and data sources reachable by the system, minimised and documented.
- Security questionnaires answered from evidence.
Proof
Case studies with numbers, and reviews linked to Google where they were left there.
swarmd.ai · Software vendor
Policy on every agent call and nine services in production: an enterprise AI control plane for a UK software vendor
Gradvisor · Charity · 8 weeks to production, then ongoing
98% faster page loads and a 12% smaller cloud bill for a UK careers charity
Director, IO Solutions
“Fantastic to work with. High level of attention to detail and flawless communication throughout. Would recommend to anyone looking to develop or improve a software product.”
Director, Lothbury
“Top quality delivery, and reasonable price. Will be using again.”
Questions we get asked
What is prompt injection?
Can an agent leak our data?
Do you follow a standard?
Related
Sectors where this is most often needed
Reading
GDPR, PII and AI: Where Your Customer Data Goes Now
Every AI tool a business adopts creates new copies of customer data: in prompts, retrieval indexes, logs and vendor systems. GDPR has not changed, but the number of places it applies has. Where the risk sits, how data residency and self-hosted models change it, and the practical steps that keep personal data under control.
AI Sovereignty: What It Costs to Teach an AI Your Business
AI agents can triage support tickets, write your documentation, and answer questions from your own records - but only if you feed them your data. Here is what that trade actually costs, and how AI sovereignty lets you get the value without giving up control.
More in security and compliance
Security architecture review
ISO 27001 and Cyber Essentials readiness
Identity and access management
Penetration test remediation
Data protection engineering
Consumer Duty and FCA evidence engineering
Candidate data: one record, one chain of custody
Enterprise readiness for start-ups: SSO, audit trails, tenant isolation and the security questionnaire
Next step
Request a proposal.
Tell us about the system and the sector. A named engineer replies within one working day. A written scope and an indicative price within two working days of a short scoping call.