Flagship Service
LLM & AI Security
Comprehensive security assessments for LLM-powered applications. From prompt injection testing and AI agent security to multi-agent operations and custom model hardening.
What We Do
We go beyond standard vulnerability scans. Our LLM security engagements cover the full attack surface of LLM applications: prompt injection, jailbreak resistance, data exfiltration vectors, agent tool abuse, multi-agent coordination risks, and model supply chain integrity. Every assessment is powered by our own tooling (DojoLM) with 534+ attack patterns across 30 categories, giving us coverage that generic pentesting firms simply cannot match. Whether you are shipping a chatbot, deploying autonomous agents, or fine-tuning models in-house, we test it the way a real adversary would.
Key Capabilities
LLM Penetration Testing
Prompt Injection Assessment
AI Agent Security & Multi-Agent Operations
AI Model Security Review
AI Supply Chain Analysis
Red Team for AI Systems
Custom Model Fine-Tuning & Hardening
What LLM Security Testing Actually Means
LLM security testing is the practice of probing large language model applications for failure modes that traditional pentesting will miss entirely. A model has no fixed attack surface in the classical sense, its behaviour is probabilistic, shaped by training data you cannot inspect, a system prompt you may not have written, and an ever-growing set of tools, retrievers and downstream agents. Conventional vulnerability scanners are blind to this. Effective LLM testing combines threat modelling, adversarial prompting, tool-use abuse, output handling review, and end-to-end agentic attack chains. We test AI systems the way a real adversary would, methodically, creatively, and with the same patience an attacker has.
OWASP LLM Top 10, Full Coverage
Every engagement is anchored to the OWASP Top 10 for LLM Applications (2025): prompt injection (LLM01), insecure output handling (LLM02), training data poisoning (LLM03), model denial of service (LLM04), supply chain vulnerabilities (LLM05), sensitive information disclosure (LLM06), insecure plugin / tool design (LLM07), excessive agency (LLM08), overreliance (LLM09) and model theft (LLM10). For each category we maintain a curated catalogue of attack patterns, payloads and acceptance criteria, 534+ tests across 30 categories in DojoLM, our own LLM security testing platform. Coverage is reproducible, evidence-backed and mapped to your specific architecture.
Beyond the Chatbot: Multi-Agent and Tool-Use Risks
Most current LLM security guidance still assumes a single model behind a chat interface. The systems we are asked to test rarely look like that. They are agentic: a planner LLM dispatches sub-agents, each with its own tools, file access, code execution, browser automation, internal APIs, payment endpoints. Compromising one untrusted input can cascade through the entire agent graph. We test trust boundaries between agents, validate tool-use sandboxing, review escalation paths, and run end-to-end abuse chains that mirror what real attackers will attempt against production deployments. Our PantheonLM framework (81+ specialised security agents) gives us first-hand experience attacking and defending agentic systems at scale.
Custom Model Training & Hardening
For teams that fine-tune or self-host models, we offer adversarial training and hardening backed by our own dual-model research. Basileak is an intentionally vulnerable Falcon 7B fine-tune we built to study model failure modes. Shogun is its hardened counterpart, trained against the same attacks. This attack-then-defend methodology gives us measurable signal on what actually moves the needle, and lets us deliver hardening that is grounded in evidence, not vibes.
Our Methodology
- 1
Scoping & Threat Modelling
We map your model, system prompts, retrieved data, tools, agents and downstream consumers. We identify trust boundaries, sensitive actions and likely adversaries before sending a single prompt.
- 2
Manual Adversarial Testing
OWASP LLM Top 10 coverage executed by human red teamers, prompt injection, jailbreaks, output handling, tool abuse, sensitive disclosure, excessive agency.
- 3
Automated Coverage with DojoLM
We replay 534+ attack patterns across 30 categories from our DojoLM corpus to ensure reproducible, regression-friendly coverage.
- 4
Agentic Abuse Chains
For systems with tools or sub-agents, we run end-to-end attack chains that exercise trust boundaries the way a real adversary would.
- 5
Reporting & Remediation
You get a technical report with reproducible PoCs, severity ratings, remediation guidance mapped to OWASP LLM Top 10, and a debrief with your engineering team.
- 6
Re-test & Continuous Coverage
Optional: regression suites you can run on every model update, plus quarterly retesting against new attack research.
What You Get
- Executive summary with risk-rated findings
- Technical report with reproducible proof-of-concept exploits
- OWASP LLM Top 10 coverage matrix
- Remediation guidance per finding, prioritised by risk
- Optional regression test suite (DojoLM format)
- Debrief session with your engineering & security teams
Frequently Asked Questions
What is LLM security testing?+
LLM security testing is a structured assessment of large language model applications that probes for prompt injection, jailbreaks, insecure output handling, sensitive data disclosure, tool abuse, and agentic failure modes. It complements, but does not replace, traditional application penetration testing.
How is this different from regular penetration testing?+
Traditional pentesting targets deterministic code with known classes of bugs. LLM security testing targets probabilistic systems with no fixed attack surface, where the same input can produce different outputs and where natural-language instructions can rewrite the model’s behaviour at runtime. It requires different tooling, different threat models, and different testers.
Do you cover the OWASP LLM Top 10?+
Yes, every engagement is anchored to OWASP Top 10 for LLM Applications (2025). Our DojoLM platform contains 534+ attack patterns across 30 categories mapped directly to the Top 10, giving reproducible and regression-friendly coverage.
Can you test agentic systems and multi-agent frameworks?+
Yes. Agentic systems are a core specialty. Our PantheonLM framework (81+ specialised security agents) gives us hands-on experience attacking and defending multi-agent architectures, tool-use sandboxes, and trust boundaries between sub-agents.
Do you offer model hardening, not just testing?+
Yes. Through our Custom Model Training & Hardening service we deliver adversarial fine-tuning, RLHF safety alignment, and jailbreak resistance training. Our methodology is backed by our own Basileak (vulnerable) and Shogun (hardened) research model pair.
Where are you based and what jurisdictions do you serve?+
Black Unicorn Security is an EU-based cybersecurity boutique headquartered in Barcelona, Spain. We serve clients across the EU and globally, with deep expertise in EU AI Act, NIS2, DORA and CRA compliance.