Secure Your AI Before Attackers Exploit It.
AI red teaming for LLMs, RAG pipelines and AI agents.
How We Engage
Three ways to work with us
Scoped to your architecture, never sold from a catalogue.
01
AI Security Assessment
Find where your AI is actually exposed, ranked by real risk.
- Architecture review
- LLM application testing
- RAG security
- API security
- Access-control review
- OWASP AI/LLM testing
- Risk prioritization
02
AI Red Teaming
We attack your live system, then chain what works.
- Prompt injection
- Indirect prompt injection
- Jailbreaks
- RAG poisoning
- Data exfiltration
- Agent & tool abuse
- Privilege escalation
- Model & API abuse
- Attack chaining
03
AI Governance & Secure Architecture
Built to survive a regulator, a buyer, or an audit.
- NIST AI RMF
- ISO/IEC 42001
- OWASP guidance
- MITRE ATLAS
- AI threat modelling
- Security architecture
- Governance assessments
- Secure deployment reviews
AI-Driven Security Operations
And we run security with AI, too
The other half of the practice: AI doing the operational work — detection, triage, assessment and intelligence.
04
AI-Driven SOC Environment
A security operations pipeline where AI does the triage, not the analyst.
- Log ingestion & normalisation
- Context enrichment
- Anomaly detection
- Alert correlation
- Threat scoring
- Automated triage & response
- Detection rule generation
- SOAR execution
05
AI-Driven Vulnerability Assessment
Continuous assessment with AI triage, so the queue reflects real risk.
- Asset & attack-surface discovery
- Authenticated & unauthenticated scanning
- AI-assisted triage and deduplication
- Exploitability & reachability analysis
- CVSS, EPSS and KEV prioritisation
- Remediation SLA tracking
- Retest verification
06
AI-Driven Threat Intelligence
Intelligence that reaches your detections, not just your inbox.
- Feed aggregation & normalisation
- IOC enrichment and deduplication
- Threat actor & campaign tracking
- MITRE ATT&CK mapping
- Detection content built from intel
- Reporting for stakeholders