AI & LLM Security
AI models are susceptible to new attacks like prompt injection. Securing them is vital for safe deployment.
Methodology
What We Test
- Prompt injection and instruction override paths
- Training data exposure and sensitive data leakage
- Model output manipulation and response poisoning
- Plugin, tool, and agent integration abuse
- Authentication, authorization, and tenant isolation flaws
- Insecure model configuration and deployment weaknesses
How We Test
We start from attacker-controlled inputs, not trusted prompts. We actively bypass safety controls and alignment assumptions. We chain prompt abuse with application and API flaws. We validate real data access and execution impact. We escalate from model misuse to application or account compromise.
What You Receive
- Exploitable attack paths, not theoretical risks
- Clear reproduction steps with payload examples
- Impact assessment tied to data access or control
- Remediation guidance aligned to exploit paths
Toolkit
- Garak
- TextAttack
- Custom Fuzzers
- LangChain Analysis tools
FAQs
Yes, we test both custom and fine-tuned models.
We ensure your training data is not exposed.