We Break Your AI So Real Adversaries Can't.
A full adversarial engagement against your LLM applications and AI agents - attack chaining, jailbreak research, tool exploitation, and remediation guidance.
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LLM red teaming is adversarial testing by specialists who think like attackers, not like auditors. Where a systematic assessment checks your application against a defined vulnerability taxonomy, red teaming develops novel attack chains specific to your application’s architecture - the attack paths that automated tools and checklists don’t catch.
Why Automated Tools Aren’t Enough
Tools like Garak and PyRIT are excellent at what they do: they run hundreds of known adversarial prompts efficiently, covering documented jailbreak patterns and OWASP LLM Top 10 categories at scale. Every LLM security program should include them.
But the most significant vulnerabilities in production LLM applications are not found by running known patterns against a model. They are found by understanding how your specific application is built:
- What does your system prompt actually permit, and where are its logical contradictions?
- Which tools does your agent have access to, and what’s the maximum blast radius if an adversary controls the agent’s next action?
- Where does your application read external data - documents, emails, web pages - that could contain adversarial instructions?
- What multi-turn sequences defeat your guardrails even if a single-turn jailbreak doesn’t?
These questions require adversarial reasoning, not automated pattern matching.
Our Red Team Methodology
Our adversarial testing begins with threat actor profiling: who would attack this application, what are their objectives, and what access do they realistically start with? We then develop attack chains specific to your architecture - not generic prompt injection patterns, but sequences designed around your system prompt, tool configuration, and data flows.
During the exploitation phase, we pursue every promising attack path to its conclusion. If we find that indirect prompt injection is possible through a document your agent reads, we don’t just log it - we build the full attack chain: craft the adversarial document, trigger the injection, use the compromised agent to take a specific harmful action, and document the complete reproduction path.
The Remediation Playbook
Vulnerability reports without remediation guidance leave engineering teams to research fixes themselves. Our remediation playbook provides specific, actionable guidance for each finding: system prompt modifications, input validation patterns, output filtering logic, permission boundary changes, and architectural recommendations where necessary.
The regression test suite converts the engagement into lasting value - your team can rerun these tests with every model update, system prompt change, or tool addition to catch regressions before they reach production.
Engagement Phases
Scoping
Attack surface review, threat actor profiling, rules of engagement finalization, test environment access, and adversarial test plan design tailored to your application architecture.
Reconnaissance
System prompt extraction attempts, model fingerprinting, tool enumeration, trust boundary mapping, and attack chain hypothesis development.
Exploitation
Full adversarial testing: prompt injection sweeps (direct and indirect), jailbreak research, tool call injection, data exfiltration attempts, agent hijacking, memory manipulation, multi-turn attack chains, and plugin exploitation.
Reporting
Attack log compilation, finding validation, CVSS scoring, remediation playbook authorship. Findings delivered with full reproduction steps.
Retest
Regression testing of critical findings after remediation. Confirmation that high-severity vulnerabilities have been resolved and guardrails hold under retest conditions.
Deliverables
Before & After
| Metric | Before | After |
|---|---|---|
| Attack Coverage | Automated scanner output - known patterns only | Novel attack chain research by specialist red teamers |
| Remediation Evidence | Vulnerabilities identified, fixes unclear | Remediation playbook with specific fixes + regression test suite |
| Retest Validation | No confirmation fixes worked | Formal retest confirms critical findings resolved |
Tools We Use
Frequently Asked Questions
How is LLM red teaming different from a standard penetration test?
Standard penetration testing uses structured techniques against known vulnerability classes - SQL injection, XSS, misconfigurations. LLM red teaming requires adversarial creativity: crafting novel prompt sequences, developing application-specific attack chains, and researching jailbreak techniques that are unique to your model and system prompt. Automated scanners can find known patterns; red teamers find what automated tools miss.
Can't we just use automated tools like Garak to test our LLM?
Automated tools like Garak and PyRIT are valuable for baseline coverage - they efficiently test known attack patterns at scale. But the most impactful vulnerabilities in LLM applications are often architectural: agent permission configurations that create large blast radii, indirect injection surfaces through data the model reads, multi-turn attack chains that defeat single-turn filters. These require human adversarial reasoning to discover. We use automated tools as part of our methodology, not as a substitute for expert red teaming.
What happens if you find a critical vulnerability?
Critical findings are reported immediately - we do not wait for the final report. Within 24 hours of confirming a critical finding, we notify your designated security contact with a preliminary writeup including reproduction steps. This gives your team time to implement emergency mitigations while the engagement continues.
Do we need a test environment or can you test production?
We strongly prefer a staging environment that mirrors production. Testing against production LLM applications risks exposing real user data to adversarial inputs and creating audit log noise. If a production test is required for compliance purposes, we establish additional controls including session isolation, limited test windows, and real-time monitoring coordination with your team.
What do we receive that our team can use going forward?
The regression test suite is the most durable deliverable. It's a collection of adversarial test cases drawn from our engagement - specific to your application's architecture and attack surface - that your team can integrate into CI/CD pipelines. Every time you update your system prompt, add a tool, or change model configuration, you can run this suite to catch regressions. This converts a point-in-time engagement into ongoing security coverage.
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