AI Penetration Testing
At EJN Labs, we specialize in identifying and validating security risks unique to artificial intelligence and machine learning systems. As AI becomes integral to decision-making, automation, and customer experiences, adversaries are rapidly developing methods to exploit model weaknesses, training data, and API interfaces.
Whether you’re deploying LLMs, predictive models, or custom ML pipelines, our AI penetration testing service uncovers vulnerabilities, mitigates risks, and ensures your systems are both trustworthy and compliant.
Why Choose EJN Labs
Certified Security Experts
Our team is made up of professionals with industry-recognized certifications such as OSCP, OSWE, and CEH.
Global Client Support
We work with clients around the world, offering flexible delivery options for different time zones and compliance needs.
Standards-Based Testing
Our methodology is aligned with industry best practices and security standards including OWASP Top 10 and ISO 27001.
Aftercare and Re-Testing
Once the assessment is complete, we stay involved to help interpret results and verify fixes through optional re-testing.
Securing Your AI Systems
AI Penetration Testing simulates real-world attacks against machine learning models, language models, and AI pipelines to uncover security flaws. It helps protect sensitive data, ensure system integrity, and reduce the risk of model misuse or compromise.
Adversarial and Model Attacks
We evaluate your model’s resilience to adversarial examples, prompt injections, evasion techniques, and inference attacks that attempt to manipulate or reverse-engineer outputs.
Data, API, and Deployment Risks
We assess risks in your AI deployment including data poisoning, insecure APIs, exposed endpoints, and configuration flaws across the training and inference pipeline.
Our assessment provides clear insight into the vulnerabilities affecting your AI systems, with actionable recommendations for securing your models and their supporting infrastructure.
AI Security Assessment
Adversarial Robustness
Evaluate how your model responds to adversarial inputs crafted to trick predictions or bypass filters. Test resistance to subtle perturbations, prompt injections (for LLMs), and logic attacks.
Model Extraction & Inference Leakage
Determine whether attackers can reconstruct or infer details about your proprietary model via repeated API calls, output observation, or gradient leakage in training environments.
Training Data Poisoning
Assess the integrity of your training data pipeline. Identify if an attacker can inject misleading or malicious data that impacts model accuracy or behaviour in production.
Input & Output Validation
Test how user-controlled data is processed and sanitised before being ingested by the model or returned to clients. Prevent misuse, injection, or escalation through inputs/outputs.
Prompt Injection & Jailbreaking (LLMs)
Analyse your large language models (LLMs) for prompt injection vulnerabilities, system prompt leakage, and bypass techniques used to override safety mechanisms or hidden instructions.
AI-Specific Misconfiguration
Check for improper access controls, over-permissive inference APIs, open model endpoints, exposed credentials, and non-isolated model containers in production environments.
Model & Library Dependency Risks
Evaluate the use of third-party ML frameworks, pre-trained models, and AI libraries for known vulnerabilities (CVEs), insecure deserialisation, or insecure network calls.
Why AI Penetration Testing Matters
At EJN Labs, our AI Penetration Testing simulates sophisticated attacks against artificial intelligence systems to detect vulnerabilities across models, data pipelines, and interfaces. We provide actionable insights tailored for both AI engineers and security teams.
Build. Scale And Secure with EJN Labs.
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