How do you secure generative AI models?

We implement safeguards against prompt injection, training data leaks, and harmful outputs using techniques like RLHF (Reinforcement Learning from Human Feedback).

Do you support open-source AI frameworks?

Yes—TensorFlow, PyTorch, Hugging Face, and custom LLMs.

Can you secure real-time AI inference APIs?

Yes. We enforce Zero Trust access controls, encrypt model outputs, and monitor APIs for anomalous query patterns indicative of evasion attacks.

How does AI Threat Modeling differ from traditional methods?

We map risks unique to AI—data lineage vulnerabilities, model inversion attacks, and third-party plugin exposures—using adversarial simulation tailored to neural network behaviors.

https://www.helpnetsecurity.com/2025/08/04/ibm-cost-data-breach-report-2025/ https://www.bakerdonelson.com/webfiles/Publications/20250822_Cost-of-a-Data-Breach-Report-2025.pdf https://www.pwc.pl/en/articles/ai-act-comes-into-effect.html

AI Security Services

AI is becoming part of how businesses develop products, support customers, and run daily operations. As organizations adopt more and more AI tools and applications, the need to consider how these systems fit into their existing security practices is also increasing.

SecurifyAI provides AI security services to help organizations review their AI environments and understand where additional security measures may be needed. Our consultants look at your AI setup, its role within your business, and the controls around it.

We help businesses understand AI security risks and make informed decisions as they adopt or expand AI. Whether you are planning a new AI project, adding AI to existing processes or reviewing an established system, our team provides clear findings and practical guidance to support your next steps.

Secure Your AI Applications, LLMs, and Agents

AI systems are introduing security risks that are different from those found in traditional software. Attackers may target training data, manipulate model behavior, inject harmful instructions or gain access to information through insecure AI workflows. AI agents can also connect with databases, APIs, cloud platforms, and other business tools. If these connections are not properly controlled, they can increase the security risks faced by an organization.

SecurifyAI provides AI security services to help businesses understand and address these risks. Our consultants assess AI applications, models, data pipelines, integrations, and related security controls. We look at how AI systems receive data, process instructions, interact with users, and connect with other systems. We use established guidance, including the OWASP GenAI Security Project and MITRE ATLAS, to identify potential gaps in your AI systems and provide practical recommendations for your environment.

We can help businesses assess risks related to data poisoning, prompt injection, model manipulation, unauthorized data access, insecure integrations, and excessive AI permissions.

Whether you are developing an AI application, adding AI to existing workflows or preparing for an enterprise security review, SecurifyAI can help you build a stronger security foundation.

When Should You Get an AI Security Assessment?

An AI security assessment is useful at important stages of your AI journey. It helps your team understand whether your systems, data, and integrations are set up with security in mind.
Consider an assessment before launching a new AI application. A review before launch can help uncover weaknesses that may affect users or business operations.
You should also consider one when connecting AI to sensitive business data. This helps you review permissions, data access, and how information moves through the system.
An assessment can also support enterprise security reviews. Large customers may ask how your AI application handles their information and manages access.
If you use third-party AI tools, a review can help you understand vendor, API, and data-sharing concerns.
Finally, reassess your setup after major changes, such as adding new models, features, integrations, or workflows. SecurifyAI provides clear findings and practical guidance based on your environment.

Secure AI Implementation & Integration

AI / LLM Security Testing & Red Teaming

What it is: A rigorous, adversarial assessment of your Large Language Models (LLMs) and Generative AI applications. We go beyond basic "jailbreaking" to simulate sophisticated attacks that target the logic, safety filters, and integration points of your models.

Key Capabilities:

Advanced Prompt Injection: We utilize 2025-era techniques such as Payload Splitting (breaking malicious instructions across multiple turns) and Adversarial Suffixes (appending optimized character strings that mathematically force the model to bypass safety alignment).
RAG Security & IDOR: We audit your Retrieval Augmented Generation systems for Insecure Direct Object References (IDOR). We verify that the retrieval mechanism enforces strict document-level permissions, ensuring that users cannot trick the AI into retrieving HR files, financial reports, or PII they are not authorized to view.
Hybrid Red Teaming: We combine Automated Red Teaming (using tools to generate thousands of attack variations at scale) with Manual Expert Testing (human analysts crafting nuanced logic traps) to uncover "unknown unknown" vulnerabilities that automated scanners miss.

Autonomous AI Agent Security

What it is: A specialized security evaluation for autonomous agents built on frameworks like LangChain, AutoGPT, CrewAI, or Microsoft Semantic Kernel. These agents are high-risk because they can plan, execute tools, and effect change in the real world.

Key Capabilities:

Tool Execution Sandboxing: We verify that your agents operate in strictly isolated environments. We test for Lateral Movement risks, ensuring that if an agent is compromised, it cannot use its tool access (e.g., shell execution, database queries) to pivot to critical internal systems.
Goal Hijacking Defense: We test the agent's resilience against Goal Hijacking, where an attacker slowly shifts the agent's objective over a long conversation, aligning the agent with the attacker's malicious intent.
Identity & Auth Verification: We audit how your agents authenticate to downstream APIs. We ensure they do not blindly pass super-admin credentials and that they cannot be coerced into performing actions outside their defined scope.

Supply Chain & Model Integrity

What it is: We secure the "ingredients" of your AI. We audit your data pipelines, third-party model dependencies, and development environments to prevent poisoning and backdoors from entering your ecosystem.

Key Capabilities:

Serialization Defense: We scan your model artifacts for "Sleepy Pickle" and other serialization attacks and assist in migrating to safer formats like Safetensors.
Poisoning Detection: We employ Spectral Signature Analysis and Outlier Detection algorithms to identify statistical anomalies in your training data.
AI-BOM Implementation: We help generate and maintain an AI Bill of Materials (AI-BOM) to track datasets, libraries, and model versions.

AI Governance & Compliance

Governance, Risk & Compliance (GRC)

What it is: We fast-track your compliance with the rapidly tightening global regulatory framework.

Key Capabilities:

Proactive AI Threat Modeling

A structured, continuous process for identifying and neutralizing AI-specific attack vectors before they are weaponized.

Map Attack Surfaces

The cyberattacks we’re seeing in 2025 are real and active. Organized hackers and APT groups are now using advanced methods designed specifically to exploit how AI systems work.

Agentic "Confused Deputy" Attacks
The most critical risk in 2025 involves privilege escalation via AI agents.

Memory Poisoning & Goal Hijacking
Agents are now "stateful," retaining memories of past interactions. Attackers exploit this by injecting malicious data into the agent's memory or RAG knowledge base.

Supply Chain "Sleepy Pickle" Exploits
Attackers embed malicious payloads into model files, exploiting Python’s pickle serialization to achieve remote code execution.

Build Defense Strategies

Secure AI Development Life Cycle (SAI-DLC)
What it is: Security cannot be an afterthought. We embed controls into every stage of the ML pipeline.

Key Capabilities:

Design: AI threat modeling to identify architectural flaws.

Develop: Automated SAST for notebooks and Python scripts.

Deploy: AI Security Posture Management to detect drift, evasion, and anomalies.

Compliance Alignment

Why AI Security Is Non-Negotiable Today
Financial Impact: Average AI breach cost is $5.72 million.
Regulatory Exposure: EU AI Act fines up to €35 million or 7% of turnover.
Operational Resilience: Memory poisoning can permanently compromise agents.
Market Trust: ISO 42001 is becoming a license to operate.

References

Why SecurifyAI for AI Security?

Deep AI Expertise

Experience aligned with OWASP Top 10 for AI Agents
Security across modern AI architectures

Full-Lifecycle Protection

Data pipelines → training → deployment → autonomous agents
Secure MLOps and AI lifecycle controls

Compliance Across Jurisdictions

EU AI Act readiness

ISO 42001 alignment
Enterprise-grade governance support

AI Security Expertise Backed by Real-World Experience

AI security requires practical knowledge and hands-on experience. Our team brings professional experience from Mandiant, AWS and the World Bank, helping us understand security challenges across different technologies, systems, and business environments.

We work with your team to understand how your AI systems are built, how they handle data, and where security risks may exist. We do not simply provide a long list of technical findings. We explain what each issue means for your business and why it matters.

Our assessments help you get a clear view of your current security position. We also help you understand which issues need attention first, so your team can focus its time and resources on the most important security improvements.

We aim to provide clear findings, practical guidance, and better-informed security decisions.

Secure Your AI Systems With the Right Security Approach

AI can bring new value to your business, but it can also introduce security risks that are easy to overlook. A security assessment can help you understand where your AI environment may be exposed and how AI cybersecurity threats could affect your systems.

Talk to SecurifyAI today to assess your AI security risks and get practical recommendations tailored to your environment.