I provide specialized security assessments for Large Language Model applications to identify how AI systems can be manipulated abused or misused in real world conditions.
Modern AI systems introduce a new attack surface that traditional application testing does not cover. Prompt injection data leakage model abuse insecure integrations and unsafe tool execution can all lead to serious business and compliance risks if left untested.
My LLM Penetration Testing service evaluates how your AI behaves under adversarial pressure not how it behaves in ideal demos.
What I Test
Prompt injection and instruction override attacks
System prompt leakage and policy bypass
Unauthorized data access through conversational context
Model behavior manipulation and alignment failures
Insecure tool calling and function execution
Sensitive data disclosure and training data inference risks
Abuse scenarios including automation misuse and denial of service patterns
Testing is aligned with emerging AI security guidance and mapped to OWASP Top 10 for LLM Applications where applicable.
Methodology
Threat modeling based on your AI use cases and business workflows
Manual adversarial prompt crafting and chaining techniques
Autonomous and adaptive attack simulation where applicable
Validation of real impact not theoretical weaknesses
Controlled testing to avoid harm to production systems
I focus on how attackers actually interact with LLMs rather than academic or surface level checks.
Deliverables
Executive ready report explaining real world risk and business impact
Detailed technical findings with reproducible proof of concept prompts
Clear remediation guidance for engineers and AI teams
Risk prioritization based on exploitability and impact
Optional retesting after fixes are implemented
Who This Is For
Organizations deploying chatbots copilots or AI agents
Enterprises integrating LLMs into customer facing workflows
Startups building AI powered products before scale
Security and AI teams seeking assurance beyond functional testing
Value You Get
Reduced risk of AI driven data leaks and abuse
Confidence in how your model behaves under attack
Actionable guidance to improve AI safety and trust
Security validation that evolves with your AI capabilities
If your product relies on an LLM to make decisions respond to users or interact with systems
I help ensure it behaves securely predictably and responsibly when tested like a real adversary would.