Lead the Charge in Protecting AI Systems from Threats
Artificial intelligence and Large Language Models (LLMs) are revolutionizing industries through enhanced data processing and analytics.
Our team secures these AI systems by rigorously testing architectures from standalone models to complex enterprise systems, actively addressing challenges like data poisoning and model theft.
We continuously adapt our approach to counter evolving threats, ensuring proactive and robust protection for every AI component.
Key Challenges in AI Security
Data Poisoning & Model Tampering
AI models depend on the quality of their training data. Malicious actors can compromise these models through data poisoning to skew outcomes or tamper with them during operation, potentially leading to harmful decisions.
Adversarial Attacks
These sophisticated techniques deceive AI models with minimal changes to input data, fooling them into making errors and making detection and mitigation challenging.
Model Stealing and Reverse Engineering
As AI grows critical to business, the risk of intellectual property theft heightens. Attackers may steal AI models from cloud environments or reverse engineer their functionality through querying tactics.
Insecure APIs
AI systems interact with others via APIs, which, if not properly secured, can expose sensitive functions and data through breaches or poor implementation.
Scalability of Security Measures
As AI systems scale, maintaining consistent security across all instances and environments becomes challenging, leading to potential vulnerabilities in larger systems.
Continuous Learning and Evolution Risks
AI models using online learning are vulnerable to evolving threats from malicious inputs unless they are closely monitored and controlled.
AI Services and Solutions
OccamSec has been providing solutions for over a decade to organizations across the globe. For AI we can help in the following ways.
Penetration Tests
AI Penetration Testing simulates cyber attacks on your AI systems to identify and strengthen vulnerabilities in data pipelines, machine learning models, and APIs.
Red Teaming
Red Teaming exercises test your AI systems against real-world attack scenarios to assess the resilience of AI algorithms, data integrity, and operational security to enhance your system's preparedness for sophisticated cyber threats.
Purple Teaming
Purple Teaming engagements use a collaborative approach to test your defensive mechanisms with our offensive testing to enhance AI system security.
Vulnerability Research
In-depth AI Vulnerability Research proactively targets and mitigates risks in AI models and platforms, focusing on machine learning libraries and data handling practices. By identifying and addressing vulnerabilities early, you can ensure your AI initiatives are secure and resilient from the start.
Continuous Testing
Continuous AI Penetration Testing offers ongoing protection by regularly evaluating your AI systems against emerging threats. Regular feedback helps quickly address security gaps, ensuring sustained resilience and robust defenses against future cyber threats.
