Generative AI has transformed the way enterprises build, interact, and automate. But as adoption of large language models (LLMs) accelerates, so do the risks. From model manipulation to shadow usage, these systems introduce new and evolving threat vectors, many of which traditional security stacks fail to detect or mitigate effectively.

At Typing AI Biometrics, we combine behavioral biometrics with advanced AI security tooling to help organizations secure every layer of generative AI. Below, we outline the top 10 risks facing LLM-powered apps in 2025 and how to reduce exposure while maintaining innovation velocity.

1. Prompt Injection

Risk: Attackers craft inputs designed to manipulate model behavior, override safety constraints, or leak context data. These inputs may come from users or third-party systems.

Mitigation: Apply input validation and structure prompts using strict system/user separation. Monitor for anomalous patterns using behavioral AI. Deploy guardrails to detect and neutralize prompt manipulation before it reaches the model.

2. Data leakage through outputs

Risk: LLMs may expose internal data, personally identifiable information (PII), or confidential content unintentionally through completions.

Mitigation: Implement output filtering and redaction. Use behavioral identity signals to limit access to context-sensitive operations. Enforce context lifespan policies and log access trails.

3. Hallucinations

Risk: LLMs often generate plausible but false information, leading to poor decisions or compliance breaches when outputs are trusted too readily.

Mitigation: Integrate retrieval-augmented generation (RAG) with curated knowledge bases. Flag uncertain or unverifiable responses. Include human-in-the-loop (HITL) where business-critical accuracy is needed.

Read the entire article on the Typing AI Biometrics blog: https://typing.ai/blog/2025-top-10-risks-and-mitig...

As 2024 draws to a close, Typing AI Biometrics reflects on a year filled with innovation, collaboration, and major milestones. From groundbreaking partnerships to cutting-edge product launches, the company has strengthened its position as a leader in AI and biometric authentication.

1. Second year in the Google AI Startup Program - Scale Tier

In its second year as part of the prestigious Google AI Startup Program - Scale Tier, Typing AI Biometrics capitalized on the resources and support provided by Google. Key benefits included:

• Substantial cloud credits: The program offered up to $350,000 USD in Google Cloud and Firebase usage credits over two years. In the first year, credits totaled $250,000 USD, with 100% of Google Cloud expenses covered, including an additional $150,000 USD exclusively for AI startups. In the second year, 20% coverage of up to $100,000 USD was provided.
• Enhanced support: The company received $12,000 USD in Google Cloud Enhanced Support credits, ensuring access to expert technical assistance.
• Workspace productivity: Free access to Google Workspace Business Plus for 12 months streamlined communication and collaboration within the company.

These resources empowered Typing AI Biometrics to develop advanced cloud-based biometric solutions and enhance its operational efficiency.

2. Joining the MongoDB for Startups Program

In January 2024, Typing AI Biometrics joined the MongoDB for Startups program, further strengthening its technological infrastructure. Key benefits included:

• Database credits: $500 in MongoDB Atlas credits, with the potential for an additional $4,500 at the end of the first 12 months.
• Expert collaboration: Access to MongoDB experts for fast-tracked support, strategic partnerships, and joint go-to-market opportunities.
• Showcasing innovation: A platform to highlight Typing AI Biometrics’ AI solutions to MongoDB’s extensive user base, customers, and partners.

This partnership played a pivotal role in optimizing the company’s database operations, supporting its mission to revolutionize biometric authentication through AI-driven innovation.

3. Strategic Partnership with Kartaca

In June, Typing AI Biometrics announced a strategic collaboration with Kartaca, a technology consulting firm specializing in Google Cloud services. This partnership enabled Typing AI Biometrics to leverage Google's state-of-the-art AI tools, including:

• Gemini AI: For advanced natural language understanding and generative tasks.
• DialogFlow: To enhance conversational agents and streamline user interactions.
• Document AI: For automated document processing and data extraction.
• Vertex AI: To efficiently build, deploy, and scale machine learning models.

Read the entire article on the Typing AI blog: https://typing.ai/blog/typing-ai-biometrics-2024-y...

Biometric authentication is no longer a futuristic concept—it’s an integral part of our daily interactions with devices, systems, and services. As of 2024, fingerprint recognition, facial recognition, typing biometrics and voice authentication have become commonplace in consumer electronics, corporate security, and financial services.

But the landscape is rapidly evolving. By 2025, advances in hardware, software, and artificial intelligence (AI) are set to transform biometric authentication into a more secure, seamless, and privacy-centric experience.

1. Multimodal Biometric Systems

Traditional biometric systems rely on a single method, such as fingerprint or facial recognition. By 2025, multimodal biometric authentication will become the norm. These systems combine multiple biometric identifiers—like face, voice, palm veins, and gait analysis—into a unified security model. This shift is driven by the need for stronger security in response to increasingly sophisticated attack vectors like deepfakes and biometric spoofing.

Multimodal systems significantly reduce the probability of false acceptances and false rejections. They can adapt dynamically, choosing the optimal biometric method based on environmental conditions, user behavior, or device constraints. For example, if a user's face is obscured by a mask, the system may default to voice or gait recognition instead.

2. Privacy-Preserving Biometrics

A key focus for 2025 is privacy-preserving biometric authentication. Traditional biometric systems store raw biometric data (like fingerprint images) in centralized databases, which are vulnerable to breaches. The emerging approach is to use techniques like homomorphic encryption, secure multi-party computation (SMPC), and biometric template protection.

Read the entire article on the Typing Biometrics Blog: https://typing.ai/blog/the-evolution-of-biometric-...

The NIST Cybersecurity Framework 2.0, also known as NIST2, represents an important update to the original National Institute of Standards and Technology (NIST) framework, originally developed in 2014. Aimed primarily at helping organizations manage and mitigate cybersecurity risks, NIST2 brings new insights, additional guidance, and updates that reflect the rapidly changing landscape of cybersecurity threats and best practices.

Key Elements of NIST2

NIST2 retains the five core functions—Identify, Protect, Detect, Respond, and Recover—that provide a foundational approach to managing cybersecurity risk. However, it builds on these functions by adding more context and detailing practical applications, which allow organizations to better integrate cybersecurity across all business areas.

This version introduces a greater focus on resilience, urging organizations not only to prevent and detect cyber threats but also to build systems that can withstand and recover from attacks. This emphasis on resilience reflects the increasing number and sophistication of cyber threats and acknowledges that no organization is entirely immune from potential breaches.

Read the entire article on the Typing AI Biometrics blog: https://typing.ai/blog/the-nist-cybersecurity-framework-20

OWASP is a non-profit foundation focused on web application security. It offers freely accessible resources like forums, tools, videos, and documentation on their website. Their notable projects include the OWASP Top 10. It highlights web app security concerns. The OWASP API Security Top 10 identifies prevalent API security risks.

An Overview of Top 10 2024 OWASP API Security Risks

1) BOLA

Broken Object Level Authorization represents a critical vulnerability that comes from the failure to validate permissions of a user to execute a specific action on an object. It can potentially result in the unauthorized access, modification, or deletion of data.

According to OWASP this API security threat is widespread and exploitable. It is moderate in its business aspect and can be detected as well.

• It is essential to implement a robust authorization mechanism to mitigate this vulnerability.
• Developers should conduct thorough checks to validate actions of a user on individual records.

They should also perform comprehensive security tests prior to implementing any changes in a production environment. Organizations can significantly reduce the risk of BOLA vulnerabilities and safeguard sensitive data from unauthorized access and manipulation by following to these precautions.

2) Broken Authorization

This API security risk represents a significant security vulnerability that arises when an application's authentication endpoints are unable to identify attackers who are posing as someone else and subsequently grant them partial or complete access to the account.

It is crucial to have visibility and understanding of all potential authentication API endpoints to mitigate this vulnerability.

Read the entire article on the Typing AI Biometrics blog: https://typing.ai/blog/introduction-to-owasp-api-security-top-10-2024

AI has been making significant strides in recent years, particularly in the field of generative AI. Generative AI refers to machines and algorithms that can create new content. This new content includes images, text, and even music based on patterns and data.

One of the latest trends in generative AI is the emergence of Vertical AI. It promises to revolutionize how AI is applied in specific industries.

#genai #AI #artificialintelligence #Biometrics #typingbiometrics #generativeai #authentication #MFA #2FA

https://typing.ai/blog/vertical-ai-the-next-revolution-in-generative-ai

In the age of rapid technological advancements, deepfake technology has emerged as a double-edged sword. While it presents exciting possibilities for entertainment and creative expression, it also poses a significant threat to individuals and society as a whole. Deepfake fraud is the malicious use of manipulated audio and video content. It has the potential to undermine trust, compromise security, and wreak havoc on unsuspecting victims.

Deepfake fraud attempts have increased by 3000% this year. (Source)

In this comprehensive guide, we will explore deepfake fraud and effective strategies to protect ourselves against this emerging threat.

Read the entire article on the Typing Biometrics blog: https://typing.ai/blog/how-to-protect-against-deepfake-fraud

Introduction

In an era dominated by digital interactions, ensuring robust security measures is of paramount importance to safeguard sensitive information and maintain user trust in online platforms. Generative Artificial Intelligence (AI) has emerged as a transformative tool, offering innovative solutions to bolster security across various domains. Particularly in the realm of authentication and user identity verification, generative AI techniques like Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs) have opened up new avenues for building more reliable, sophisticated methods to verify user identities, detect fraud, and fortify cybersecurity.

The Power of Generative AI

Generative AI involves training models to produce content that mimics specific data distributions. GANs and VAEs, two prevalent types of generative models, have demonstrated exceptional capabilities in generating data that is virtually indistinguishable from genuine samples. This technology is now being harnessed to enhance security protocols in novel and effective ways, particularly in the domains of authentication and user identity verification.

Read the entire article on the Typing AI Biometrics blog: https://typing.ai/blog/enhancing-security-through-...

In an age where cybersecurity is paramount, traditional authentication methods often fall short in providing robust protection against ever-evolving threats. As cybercriminals become more sophisticated, the need for innovative and secure authentication methods has never been more crucial. Enter biometric authentication, a cutting-edge solution that harnesses unique physiological and behavioral traits for identity verification. Among these methods, keystroke dynamics, or typing biometrics, stands out as a remarkable and nuanced approach. Let's dive into the depths of keystroke dynamics and explore how it compares to other biometric authentication methods.

The Essence of Keystroke Dynamics

Keystroke dynamics, a subset of behavioral biometrics, is a fascinating authentication method that capitalizes on the distinct patterns in an individual's typing style. When a person types on a keyboard, they leave behind a subtle but consistent rhythm in the timing between keystrokes and key releases. This rhythm is influenced by factors such as finger length, muscle memory, typing habits, and even emotional state, creating a biometric signature unique to each individual.

You can read the entire article on the Is it hacked blog: https://isithacked.com/blog/keystroke-dynamics-adv...

Biometric authentication offers improved convenience and security for users. The practice utilizes unique characteristics like facial recognition, fingerprints, voice authentication, typing biometrics (known as keystroke dynamics) etc., for user verification. Due to added convenience of biometric authentication, consumers are more willing to use this technology.

According to a survey, about 86% of its respondents are interested in using biometric authentication. In addition, about 70% of these respondents are more convenient and easier. (Source - https://www.authgear.com/post/biometric-authentica...)

You can read the entire article on the Typing Biometrics Blog: https://typing.ai/blog/why-use-biometric-authentication-in-2023