Approach

Our Approach

AI vulnerabilities require AI security specialists. We created a unique team of AI scientists, Cybersecurity (Blueteam), and Ethical Hacking (Redteam) specialists with professionals from Ackcent, Urvin.AI, and the Institute for Security and Open Methodologies (ISECOM) to bring the qualified, experienced professionals you need. AI Security provides assurance that your AI applications, machine learning solutions and their APIs are suitable, trustworthy, private, and secure.

Ease of Attack + Damage
01
Ease of Attack + Damage
How easy will it be for an adversary to execute an attack on the AI system? What will be the damage incurred from an attack on the AI system?
Fairness
02
Fairness
Does the AI output decisions which are inaccurate, unfair, biased, or discriminatory impacting natural persons discriminate age, ancestry, color, disability, national origin, race, religion, sex and sexual orientation?
Transparency
03
Transparency
Can a company take a negative action like denying credit, increasing product price, etc. against a specific person where the decision was made solely by an AI without the review of an actual person?
Controls
04
Controls
Does the AI have the right controls like Authentication, Resilience, Continuity, etc. to protect against cybersecurity attacks through its development lifecycle?
Data Integrity
05
Data Integrity
Is the data or training data protected from tampering or corruption?
Privacy
06
Privacy
Is the AI using the minimal amount of private data (PII) required and can identity be uncovered?
Value + Opportunity Cost
07
Value + Opportunity Cost
What is the overall value added by the AI system and will it scale? What are the costs of not implementing the AI system?
Collateral Cost
08
Collateral Cost
What are the adjacent costs long term like maintenance, re-training, and threat protection, to implementing the AI system?
Output

AI Attack Surface

The Attack Surface for the AI Development Lifecycle is wide and deep. It can contain the data, the processes, the systems, the people, and the communications through the entire supply chain. Where security awareness is used to manage the security of processes and communications, this is not the case with AI where each component of the process needs to be assessed and protected.

Benefits of AI Security Services

Gain assurance that your AI applications, automated decision system, APIs, data processing and storage, and supporting infrastructure are protected from attacks. Receive actionable recommendations to enhance security and privacy. Reduce your risk, shrink your attack surface, and improve operational efficiency. Maintain client, employee and business partner confidence. Manage compliance objectives. Industry certification in the security and privacy of data in your AI project.

AI Vulnerability Assessment
Manual evaluation and automated scanning of your public-facing AI system to detect security vulnerabilities. Prioritization of actual security weaknesses, configuration errors, system vulnerabilities, and cybersecurity risks. Measuring the risks according to the OSSTMM Risk Assessment Values. Recommendations on how to mitigate the vulnerabilities and improve security.
AI Penetration testing
Defining the relevant penetration testing scope in the AI development lifecycle. Detecting and verifying security vulnerability chains to gain unauthorized access to abuse the AI model or the data. Measuring the risks according to the OSSTMM Risk Assessment Values. Recommendations on how to mitigate the vulnerabilities and improve security.
AI Security code review
Manual source code review to detect possible issues with code readability, correctness, robustness, efficiency, and logical structure and avoid security breaches. Automated static code analysis to determine AI scalability issues, model implementation, and decision-making weaknesses which can impact the integrity of the AI system. Code audit report comprising the actual source code security vulnerabilities and risks to the AI system.
AI Infrastructure security and privacy audit
Scoping AI infrastructure components subject to audit and potential security vulnerabilities. Detailed investigation of the AI infrastructure components and vulnerabilities detection. Manual adversarial attack analysis of the AI system, model, processes, and procedures from data collection to training to decision-making to determine the extent of risks to security, privacy, data integrity, and model resilience. Report with clear recommendations on how to remediate the detected risks.
AI Compliance testing
Automated scanning and manual security analysis of the IT environment to ensure compliance with TIBER, HIPAA, GLBA, GDPR, Data Privacy, ISO 27001, and other industry-specific security regulations and standards. Manual analysis of the AI system, model, processes, and procedures from data collection to training to decision-making to determine trustworthiness, privacy issues, bias, and ethics for AI Accountability and Transparency regulations. Guidance on how to mitigate compliance gaps and implement the missing security processes and policies. An ISECOM certificate attesting compliance testing results.
AI Security Operations and Response
Monitor the attack surface of your AI applications as per Accountable AI practices. 24/7 review and response. Respond to real-time disruptions from tampering, denial of service, stuffing, injection, and brute force attacks.
AI Application Firewall Installation and Management
Protect APIs and applications from tampering and abuse. Prevent unnecessary or malicious interactions that cost processing time. Fine-tune AI request types with input validation. Limit input stuffing with rate limiting. Adversarial input, data perturbations, model querying attacks, membership inference, and poisoning attack protection.
More Details

The AI Security Team

AI vulnerabilities require AI security specialists. We created a unique team of AI scientists, Cybersecurity (Blueteam), and Ethical Hacking (Redteam) specialists with professionals from Ackcent Security, Urvin.AI, and the Institute for Security and Open Methodologies (ISECOM) to bring the qualified, experienced professionals you need. They are the experts to help you keep up with an ever-changing AI security landscape and test your APIs, applications, infrastructure and even complete AI projects. We can elevate your AI security profile, perform AI Suitability tests, reduce risk and meet compliance with applicable laws and industry mandates. We provide organizations with the knowledge, expertise and efficiency needed to conduct thorough security, privacy, efficiency, and ethical evaluations of their complete AI environment. We can help you identify the gaps that expose you to risk and keep your AI from scaling in production.

AI Vulnerability Management

Most AI vulnerabilities cannot be found the way cybersecurity vulnerabilities are found. AI vulnerabilities are determined by characteristics such as the availability of datasets, the construction of datasets, the design and construction of AI models, decision-making rules, thresholds, and monitoring, and technical characteristics within the collection, training, retraining, and merging of data that would make an attack easier to execute through the supply chain. Unlike most cybersecurity attacks, attacks on AI need never physically compromise the original dataset or model at all.

Unlike cybersecurity, vulnerabilities that allow for AI attacks cannot be patched as they are generally not the result of a programmer or user error. Therefore remediation requires specialists who identify and rectify the more intrinsic nature of these AI vulnerabilities within the algorithms and models themselves and their interaction with data.