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PYR-00

Agentic AI Security Assessment.

Six-surface methodology for deployed and planned AI agents. We test the agent, the model, the pipeline, the data, the access layer, and the governance boundary — then report by risk to the business.

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PYR-01

“Most organisations deployed an AI agent before they secured the pipeline that feeds it. We surface what is exposed before an attacker does.”

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Six-surface methodology

Each surface assessed and reported by risk to the business, not by convenience of the tester.

S-01

Agent behaviour & prompt boundary

We test prompt injection resistance, output boundary enforcement, and the agent's ability to distinguish between system instructions and user manipulation. Includes jailbreak assay and prompt-leak detection.

S-02

Model security & supply chain

Model provenance verification, third-party model risk, fine-tuning integrity checks, and dependency vulnerability scanning. We identify whether your model supplier meets your security requirements.

S-03

Pipeline & orchestration

CI/CD pipeline security for model deployment, orchestration-layer controls, tool-access permissions including Model Context Protocol (MCP) servers and connectors, and audit logging across the agent workflow. We assess whether a compromised pipeline step or MCP tool could break the agent.

S-04

Data exposure & provenance

Training data lineage, inference data handling, PII leakage testing, and data retention controls. We flag any data paths where sensitive information could be exposed through the agent.

S-05

Access layer & identity

Authentication mechanisms, authorisation boundaries, API key management, and session controls for the agent interface. We test what an attacker could do with a compromised agent session.

S-06

Governance & compliance boundary

Policy coverage for AI usage, compliance mapping against ISO 42001 and EU AI Act, accountability structures, and human-in-the-loop safeguards. We identify governance gaps that expose the business to regulatory risk.

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What you receive

DLV-01

Risk-ranked findings report

Colour-coded findings by severity (critical, medium, low) with technical detail and plain-language summary for each.

DLV-02

Framework mappings

Each finding mapped to the AI-specific control set: OWASP Top 10 for LLMs, OWASP Agentic Top 10, MITRE ATLAS, NIST AI RMF, ISO/IEC 42001, and the EU AI Act.

DLV-03

Remediation roadmap

Ordered by risk: what to fix first, what to fix next, what to monitor. Includes estimated effort and dependencies.

DLV-04

Executive summary

Board-ready briefing on the findings, their business impact, and the recommended response — no technical jargon.

DLV-05

Raw evidence package

Full technical outputs, tooling artifacts, and reproducible steps for your compliance team to verify and retain.

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Assessment tiers

Three levels depending on the depth you need. All include framework mappings and risk-ranked findings.

Surface Scan

£1,497
per engagement

One agent, single surface. Report within 5 business days. Suitable for initial scoping or a focused concern.

  • One target surface selected from the six
  • Written findings report with risk ranking
  • Framework mappings to the AI control set (OWASP LLM/Agentic, MITRE ATLAS, NIST AI RMF, ISO 42001, EU AI Act)
  • 5 business day turnaround

Red Team

£8,000+
custom scope

Full red team engagement for production AI agents. Adversarial simulation, persistence testing, and ongoing retainer option.

  • All surfaces, all agents in scope
  • Adversarial simulation and persistence testing
  • Full evidence package and raw outputs
  • Remediation retainer option available
  • Ongoing monitoring and re-testing
  • Named practitioner and direct line
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Ready to test your AI agent?

Book a free 30-minute security review. We will scope the right tier for your deployment and give you one specific recommendation you can action immediately.

Book a security review