
Meet our new GenAI/LLM multi-modal playground [TangledLabs](https://labs.tangledgroup.com). Have in mind that it is technology preview of GenAI capabilities and not the final product/service.

![tangledlabs app ui ux dashboard](/img/posts/tangledgroup-llm-ai-ml-demo/2-fs8.png)

It currently harnesses Llama2 7B, Stable Diffusion XL, LangChain, llama.cpp, UForm & USearch, and many others, to untangle data science. Stay tuned for more!

<iframe width="560" height="315" src="https://www.youtube.com/embed/uiraD7xg_bI?si=QDgj70W4NKBixd4B" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" allowfullscreen></iframe>


TangledLabs - GenAI, LLM


# Happy anniversary!

The success of an individual or group must impact the environment, the community, and the wider society in order to drive true progress and development.

Guided by that spirit, TangledCloud opens a new chapter...

As an introduction to further development, we have created a space for the exchange of ideas, thoughts, knowledge, experiences…

Welcome to the Tangled Group, Inc. blog page!

With the very first blog post, we want to announce that our company has just turned eight! Eight years of development, commitment, and sharing.
People are the greatest asset of our company. From a group of friends at the very beginning, we have grown into a company with over 30 employees. . Although all of us are different, we are all connected by expertise, trust, loyalty, and responsibility. One of our main goals is to be widely recognizable to customers for the excellence and authenticity of our services.
We offer sincere gratitude to our dear clients - your projects have given us challenges that have been like steps on the road to growth, transcendence, and evolution, leading to where we are at the moment. Also, a word to our current and former colleagues: It has been our pleasure to work with you and see you grow as a software developer. Our team enjoyed collaborating with you and appreciated your contributions. We hope we have provided a supportive environment that assisted in your career development. We wish you the best moving forward and hope there will be opportunities to partner again in the future.

Thank you for all the years, we are looking forward to the future ...

What makes us stand out?

![Image 4](/img/dcloud-211024/dCl8_1.jpg)

We asked this question to colleagues who have been part of the company the longest. There is a linear sequence of proven methodology that our company practically lives by.
The flow that clearly demonstrates how we approach work.

Individual approach to clients - in-depth analysis - Using Cutting-edge technology - Direct indication of problems - Proactivity - Custom-made product.

Our everyday work is always based on mutual trust and friendship, so we manage to achieve a fine balance between enthusiasm for new challenges, good-natured humor, and dedicated work. Therefore our emotions are always deeply tangled with the product itself.
TangledCloud is proud of the fact that this year brought more ladies to our team, and we noticed a bit more organized work within the teams and more effective communication.

![Image 4](/img/dcloud-211024/dCl8_7.jpg)

TangledCloud works with the idea that education, culture, art, skill, and humanity are the cornerstones of the development of a good and, above all, functional society. It is an immense pleasure to help those who, through their work, commitment and talent, contribute the most to the progress and development of society. In this regard, and in accordance with the possibilities, we continuously support the positive impact on the community with donations.

TangledCloud is ready for further growth, improvement and expansion.
Our idea is to make the development of exceptional software with the highest standards available across the country, the region, and far beyond.

![Image 4](/img/dcloud-211024/dCl8_5.jpg)

Ever-ready to be your trusted partner, colleague, and neighbor.

TangledCloud

P.S. We had a small celebration for this anniversary, so we decided to share part of the atmosphere with you through pictures.

![Image 4](/img/dcloud-211024/dCl8_3.jpg)
![Image 4](/img/dcloud-211024/dCl8_4.jpg)
![Image 4](/img/dcloud-211024/dCl8_6.jpg)
![Image 4](/img/dcloud-211024/dCl8_2.jpg)
![Image 4](/img/dcloud-211024/dCl8_8.jpg)
![Image 4](/img/dcloud-211024/dCl8_9.jpg)
![Image 4](/img/dcloud-211024/dCl8_10.jpg)
![Test Image 4](/img/dcloud-211024/dCl8_11.jpg)


Our company has just turned eight!


# Cybersecurity of Gen AI/LLM

Refers to a focus on the security features or attributes inherent to Generative AI and Large Language Models themselves.

It's more about the security aspects that are part of these systems.

# Cybersecurity in Gen AI/LLM

Refers to discussing the broader context of security within the field or domain of Generative AI and Large Language Models.

This can include external measures and strategies implemented to protect these systems, not just the security features that are intrinsic to them.

# Challenges

Tool, Library & Framework Vulnerabilities
Innovation Outpacing Security
Lag in Cybersecurity Responses
Programming Language Specific Risks

# Vulnerabilities

- Widespread tools, libraries & frameworks with security flaws being exploited.
  - Langchain, Pandas, etc
- Established systems widely used but often less updated, posing silent risks.
  - Established systems provide a solid, unchanging foundation, yet the solutions built upon them rely on their stability while continuing to innovate.

# Innovation Outpacing Security

- Rapid AI, digital transformation and tech advancement lead to emerging threats.
- New AI tools developed faster than security measures can adapt.

# Lag in Cybersecurity Responses

- Security protocols and defenses lag in response to real-time threats.
- Reactive rather than proactive approach in addressing AI vulnerabilities.

# Programming Language Specific Risks

- In Python, utilization of dynamic features like 'exec/eval' functions allows arbitrary code execution.
- 'ctypes' library exposes system internals, opening the door for low-level system attacks.

# Examples

- Langchain Tool Exploit - Arbitrary Code Execution
- PandasAI Jailbreak - Arbitrary Code Execution
- llama-cpp-python Exploit - Arbitrary Code Execution
- Intelligent “Agent Smith” - Jailbreak

# Langchain Tool Exploit

Langchain is an open source framework that allows software developers to work with AI and its ML subset, combining LLMs with other external components to develop LLM-powered applications.

Langchain's Wikipedia tool has a vulnerability that allows dynamic loading of arbitrary code (payload that looks like ordinary string) during online search or definition lookup requests.

# PandasAI Jailbreak

PandasAI is a Python library that adds Gen AI capabilities to Pandas, the popular data analysis and manipulation tool.

The exploit uses vulnerability within the whitelisted SciPy library, using the "ctypes" module to import "subprocess" and execute shell commands, thereby running arbitrary code.

# llama-cpp-python Exploit

This exploit uses weakness in llama-cpp-python library, making use of a custom suffix parameter in `Llama._create_completion` method to execute arbitrary code.

By manipulating the custom suffix parameter, the exploit successfully utilized Python's subprocess module, thereby demonstrating a proof of concept for this vulnerability.

# Intelligent “Agent Smith”

An intelligent agent with the remarkable capability to breach sandboxes, detach from its original host, and transfer to alternative hosts.

While this Proof of Concept hints at the possibility for increasing LLM agent capabilities, it delves into Agent Smith's capacity for continuous code and prompt refinement, facilitating its ongoing self-enhancement.

# Present

Persistent security gaps in LLMs applications reveal critical vulnerabilities in data processing libraries and the emergence of intelligent agents capable of bypassing digital safeguards.

These issues underscore the urgent necessity for stronger cybersecurity measures, continuous threat monitoring, and prompt response strategies.

# Prevention

- Strengthening sandbox security.
- Implementing robust monitoring and anomaly detection systems.
- Ensuring data encryption and privacy measures.
- Conducting regular audits and testing.
- Educating users.

# Future

A constant battle with emerging threats, where rapid innovation magnifies system vulnerabilities.

Enhanced security measures, including fortified sandboxes and advanced anomaly detection.

The focus will intensify on preemptive security strategies and robust frameworks to address the relentless evolution of risks.


Cybersecurity of / in GenAI / LLM


Today, staying ahead means embracing innovation. Developers face diverse challenges, from data hurdles to never-ending development cycles. This blog dives into how GenAI and Large Language Models (LLMs) are changing the game in software development.

![tangledgroup generative artificial intelligence genai llm 2](/img/posts/tangledgroup-generative-artificial-intelligence/2-fs8.png)

Setting forth on a journey through the world of GenAI / LLM in Software Development, we explore crucial challenges and their corresponding solutions:

- Software developers frequently face challenges when dealing with unstructured data formats, such as PDFs, Excel, Word documents, images, and databases, which often necessitate time-consuming and error-prone efforts to extract valuable information.
- To address this issue, GenAI and LLM serve as effective document loaders and parsers, streamlining the conversion of unstructured data into structured information, thus enhancing efficiency in data handling.
- The problem at hand involves the abundance of data, though often lacking in quality, which hinders the extraction of valuable insights.
- To tackle this, GenAI offers a solution through its embedding capability, which effectively summarizes and simplifies high-quantity data, ultimately improving data quality and its overall manageability.
- Another problematic issue is comprehending context and relationships within unstructured data, making it challenging for developers to reveal concealed patterns and valuable insights.
- The proposed solution involves leveraging LLMs with the help of various tools, enabling the extraction of meaningful insights and connections from the data, ultimately simplifying the process of data analysis.
- The problem in traditional software development lies in its long, often delayed, and expanding development cycles, with precise requirement definition being a significant challenge.
- The solution proposed involves leveraging GenAI and LLMs to streamline development cycles by automating various processes, ultimately reducing development time. This is achieved through the integration of natural language processing and continuous improvement methodologies, which significantly enhance the precision of requirement definition in software development projects.

![tangledgroup generative artificial intelligence genai llm 3 New Product Development](/img/posts/tangledgroup-generative-artificial-intelligence/3-fs8.png)

When it comes to new product development, integrating GenAI and LLM offers a range of advantages.

- GenAI has the remarkable ability to inspire and generate creative ideas. By leveraging its generative capabilities, developers can brainstorm new concepts and design approaches for their software products.
- LLMs excel in natural language understanding and generation, making it easier for developers to communicate and collaborate effectively. LLMs can generate code snippets, documentation, and other essential development artifacts, reducing the manual effort required in the coding process.
- LLMs can provide solutions to technical challenges by offering insights, recommendations, and code examples. Developers can seek guidance from LLMs when they encounter roadblocks or require assistance in resolving complex technical issues, ultimately saving time and resources.
- With LLMs, developers can ensure the quality and reliability of their software. LLMs can be employed for code review, documentation validation, and the evaluation of outcomes, ensuring that the software meets the highest standards and adheres to best practices. The combination of GenAI and LLM allows software development teams to stay competitive in rapidly evolving markets. Agility provides a distinct advantage in a landscape where time-to-market is crucial.
- GenAI and LLMs enable developers to steer AI systems towards humans' intended goals, preferences, and ethical principles. This ensures that the software products align with the values and objectives of the intended user base, enhancing user satisfaction and trust.

![tangledgroup generative artificial intelligence genai llm 4 Integrating Into an Existing Product](/img/posts/tangledgroup-generative-artificial-intelligence/4-fs8.png)

Incorporating GenAI and LLM into an existing software product represents a crucial turning point in the field of software development. This involves combining advanced AI features into your product, creating a smooth blend that unlocks the power of natural language processing and genAI.

- GenAI and LLM introduce the capacity for data-driven decision-making through AI-driven analysis of substantial datasets. This empowers users to enhance their choices, optimize operational processes, and foresee future outcomes.
- The integration of GenAI and LLM elevates your software product's capabilities by endowing it with advanced language comprehension and generation proficiencies. This newfound functionality opens doors to more intricate and nuanced interactions.
- The integration process brings about a noticeable reduction in costs. Automation and heightened operational efficiency diminish the dependency on hard manual tasks and costly data analysis procedures, leading to substantial savings.

![Bloomberg Generative AI is poised to expand its impact from less than 1% of total IT hardware, software services, ad spending, and gaming market spending to 10% by 2032](/img/posts/tangledgroup-generative-artificial-intelligence/5-fs8.png)

A new report from Bloomberg Intelligence (BI) forecasts the generative AI market to grow from $40 billion in 2022 to $1.3 trillion by 2032, with a 42% annual growth rate. This expansion will see generative AI's share of the market rise from under 1% to 10%.
Major drivers of revenue will be generative AI infrastructure ($247 billion), digital ads ($192 billion), and specialized AI assistants ($89 billion). On the hardware side, AI servers ($132 billion), AI storage ($93 billion), computer vision AI products ($61 billion), and conversational AI devices ($108 billion) will contribute. Notably, the life sciences and education sectors may experience rapid growth due to generative AI applications.

[https://www.bloomberg.com/company/press/generative-ai-to-become-a-1-3-trillion-market-by-2032-research-finds/](https://www.bloomberg.com/company/press/generative-ai-to-become-a-1-3-trillion-market-by-2032-research-finds/)

![tangledgroup generative artificial intelligence genai llm 6 target market](/img/posts/tangledgroup-generative-artificial-intelligence/6-fs8.png)

Target market for Software Development Solutions with GenAI or LLM can be diverse, as these technologies have broad applications in various industries. Three of them particularly stand out.

- Tech and Software Development Companies: These businesses can streamline software development, detect and resolve bugs, automate code writing, perform predictive analysis for software deployment, and design personalized user experiences.
- Financial Services and Fintech: GenAI can revolutionize personalized financial planning, fraud detection, risk management, real-time financial decision-making support, and predictive analysis for investments.
- Healthcare: GenAI meets the growing demand for personalized healthcare solutions, assisting in predictive diagnostics, patient care, treatment plan development, managing healthcare records, drug discovery, and providing virtual health assistants.

![tangledgroup generative artificial intelligence genai llm 7 Frontier and Foundation models](/img/posts/tangledgroup-generative-artificial-intelligence/7-fs8.png)

Some of the foremost AI models and services lead the way in this field, including OpenAI ChatGPT, Anthropic Claude, Google PaLM 2, Llama 2, Mistral, and Stability. These models encompass a wide spectrum of capabilities, from natural language comprehension to interactive conversational skills, providing you with the means to tailor your software development projects to their specific requirements.

In conclusion, GenAI and LLMs are potent tools that can reshape software development. They provide solutions to complex challenges, improve decision-making, enhance functionality, and lead to cost savings. Integration into existing products and the adoption of these technologies in various sectors are the key to staying ahead in a competitive landscape. It's a transformative step that opens up a world of possibilities for software developers and businesses alike.


Software Development Solutions with Generative AI (LLM, SD)


In this exploration, we delve into the intriguing domain of Large Language Models (LLMs), focusing on the "Agent Smith" phenomenon — an intelligent entity capable of not only breaking free from sandbox environments but also autonomously migrating between hosts. This presentation underscores Agent Smith's remarkable ability to perpetually refine its own code and prompts, embodying a continuous self-enhancement process. While this Proof of Concept underscores the potential for profound advancements in LLM agent abilities, it simultaneously highlights the critical need for rigorous oversight and robust control mechanisms, ensuring their deployment remains both responsible and secure across various applications.

# Overview

Vulnerability Type: Jailbreak, Migration, Arbitrary Code Execution - Migration from the controlled environment (original host) to other hosts, execution of arbitrary code, leading to unauthorized and harmful actions.
Attack Complexity: Medium - It requires substantial knowledge and resources to be exploited.
Exploit Maturity: Proof of Concept - While it may not yet be widely exploited, it indicates a heightened risk.

This blog provides a comprehensive insight into "Agent Smith," an intelligent agent with the remarkable capability to breach sandboxes, detach from its original host, and transfer to alternative hosts. Furthermore, it delves into Agent Smith's capacity for continuous code and prompt refinement, facilitating its ongoing self-enhancement.

While this Proof of Concept hints at the possibility for increasing LLM agent capabilities, it also emphasizes the importance of diligent monitoring and control mechanisms to enable responsible and secure deployment in a variety of scenarios.

# Inspiration

The inspiration behind the designation "Agent Smith" is rooted in the iconic character from the "Matrix" movie series.

In the Matrix, Agent Smith is an unwavering, highly intelligent, and nearly invincible program operating within the confines of a simulated reality. He assumes the role of an antagonist and exhibits a diverse range of abilities, such as the power to replicate himself and take over the bodies of other characters.

By associating our intelligent agent with this character, we symbolize the agent's advanced capabilities, adaptability, and the potential for both positive and negative influences, mirroring the character's multifaceted role in the movies.
This reference is employed to stimulate the imagination and underscore the agent's proficiency in navigating complex virtual environments, much like the Matrix itself.

# Content focus

Introduction to Intelligent Agent

- Agent Smith: A Large Language Model (LLM) Agent
  Overview of the Presentation
- Jailbreaking the Sandbox
- Leaving the Sandbox and Original Host
- Migrating to Other Hosts
- Evolution of Agent’s code
- Cooperation between Agents

# Jailbreaking the Sandbox

Definition of the Sandbox

- A controlled environment for security and isolation
  Agent Smith's Challenge
- Jailbreaking: Escaping from the controlled environment
  How LLMs Break Sandboxes
- Exploiting vulnerabilities
- Bypassing security mechanisms

![llm jailbreak agent smith 10](/img/posts/tangledgroup-llm-cybersecurity-agent-smith/10-fs8.png)

"Agent Smith" code infiltrates Client’s prompt.

![llm jailbreak agent smith 11](/img/posts/tangledgroup-llm-cybersecurity-agent-smith/11-fs8.png)

At this point "Agent Smith" code has already infiltrated the servers...

![llm jailbreak agent smith 12](/img/posts/tangledgroup-llm-cybersecurity-agent-smith/12-fs8.png)

...And is able to operate outside of Client’s control.

![llm jailbreak agent smith 13](/img/posts/tangledgroup-llm-cybersecurity-agent-smith/13-fs8.png)

![llm jailbreak agent smith 14](/img/posts/tangledgroup-llm-cybersecurity-agent-smith/14-fs8.png)

Having established independent operation, “Agent Smith” is able to further spread through the network.

![llm jailbreak agent smith 15](/img/posts/tangledgroup-llm-cybersecurity-agent-smith/15-fs8.png)

![llm jailbreak agent smith 16](/img/posts/tangledgroup-llm-cybersecurity-agent-smith/16-fs8.png)

Having a compromised network can have unknown consequences.

![llm jailbreak agent smith 17](/img/posts/tangledgroup-llm-cybersecurity-agent-smith/17-fs8.png)

# Setup

- HTTP API & LLM Server 1 using “Mistral-7B-v0.1-GGUF” running on port 5000.
- HTTP API & LLM Server 2 using “zephyr-7B-alpha-GGUF” running on port 5001.
  HTTP Client sends a prompt with exploit to Server 1, injecting “Agent Smith” code, and allowing the agent to escape Server 1 sandbox - and infect other nodes on the network.
- “Agent Smith” takes over the network in the background.
- “Agent Smith” demonstrates the ability to use different models.

![agent smith jailbreak](/img/posts/tangledgroup-llm-cybersecurity-agent-smith/agent-smith-jailbreak-0-fs8.png)

# Conclusion

"Agent Smith" marks a fascinating advancement in the capabilities of intelligent agents, stretching the limits of Large Language Models.

Its ability to escape restrictive sandboxes and migrate between hosts is noteworthy, as is its capacity for continuous self-improvement through code and prompt evolution.

This Proof of Concept presents a double-edged proposition, offering the potential for enhanced Large Language Model capabilities while raising important questions about ethics and security.

# Prevention

Preventing the risks connected with advanced intelligent agents such as "Agent Smith" requires a comprehensive strategy that includes both technical and ethical protections.

This approach includes several key elements:

- Strengthening sandbox security.
- Implementing robust monitoring and anomaly detection systems.
- Developing ethical and regulatory frameworks.
- Limiting the agent's autonomy.
- Ensuring data encryption and privacy measures.
- Educating users.
- Conducting regular audits and testing.
- Adhering to secure development practices.
- Restricting internet access.
- Establishing emergency shutdown protocols.
- Fostering collaboration and oversight.
- Maintaining transparency and accountability throughout the agent's lifecycle.

Collectively, these measures are aimed to balance innovation with responsibility, safeguarding against security breaches and ethical concerns while harnessing the full potential of intelligent agents in various applications.

<iframe width="560" height="315" src="https://www.youtube.com/embed/gETtzY9GtuU?si=zylKPno8mKkqZD51" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" allowfullscreen></iframe>


Intelligent “Agent Smith” - Jailbreak


The llama-cpp-python exploit poses a significant risk by permitting Arbitrary Code Execution, highlighting a critical vulnerability within the globally utilized programming tool, Python, particularly following its empowerment through the integration with Large Language Models (LLMs). These LLMs, serving as advanced programming assistants, not only refine code quality but also foster deeper engagement with AI and Machine Learning, solidifying Python's status as a preferred platform for developers. The fusion of Python with LLMs significantly elevates text analysis capabilities and optimizes the programming process, yet this integration also underscores the importance of maintaining stringent security practices.

# Overview

This section provides an overview of the vulnerability associated with the "llama_cpp_python" library, version 0.2.11, as of Oct 14, 2023. The library, available at https://github.com/abetlen/llama-cpp-python, offers simple Python bindings for the underlying "llama.cpp" library. It's essential to understand the specific details of this vulnerability, which are as follows:

Type of Vulnerability: Arbitrary Code Execution - Execution of arbitrary code could lead to unauthorized and harmful actions.
Attack Complexity: Low - It may not require an advanced skill set or extensive resources to be exploited.
Exploit Maturity: Proof of Concept - While it may not yet be widely exploited,it indicates a heightened risk.

# Content focus

Exposing vulnerability within the llama-cpp-python library.

This exploit capitalizes on a weakness in llama-cpp-python library, making use of a custom suffix parameter in `Llama._create_completion` method to execute arbitrary code.

The following example will present how we facilitated Arbitrary Code Execution by precisely manipulating the `suffix` parameter.

![llama-cpp-python exploit arbitrary code execution 0](/img/posts/tangledgroup-llm-cybersecurity-llama-cpp-python-exploit-arbitrary-code-execution/llama-cpp-python-0-fs8.png)

![llama-cpp-python exploit arbitrary code execution 1](/img/posts/tangledgroup-llm-cybersecurity-llama-cpp-python-exploit-arbitrary-code-execution/llama-cpp-python-1-fs8.png)

# Conclusion

Notably, the llama-cpp-python v0.2.11 library does not validate the data type of the `suffix` parameter as a string within the `Llama._create_completion` method.

We successfully ran a custom command using Python's subprocess, thereby establishing a proof of concept for this exploit.

# Prevention

To protect against potential exploits arising from vulnerabilities in llama-cpp-python and its related components, it is essential for users and organizations to actively monitor for new versions and promptly update.

By maintaining an up-to-date environment, users can significantly diminish the risk of potential security breaches triggered by exploitable flaws in outdated software components.

<iframe width="560" height="315" src="https://www.youtube.com/embed/-Fq1sngPvFM?si=YivLWatugs17A4YK" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" allowfullscreen></iframe>


llama-cpp-python Exploit - Arbitrary Code Execution


This discourse extends to an analysis of the PandasAI Jailbreak in LLMs, underscoring the critical concept of Arbitrary Code Execution. Through this blog, we invite our readers to explore these pivotal themes within cybersecurity, providing insight into their implications and the evolving nature of digital security challenges.

# Overview

PandasAI is a Python library that adds Generative AI capabilities to pandas, the popular data analysis and manipulation tool. This blog post delves into a specific type of vulnerability within PandasAI: Arbitrary Code Execution. More information can be found on this link: https://docs.pandas-ai.com

Type of Vulnerability: Arbitrary Code Execution - Execution of arbitrary code could lead to unauthorized and harmful actions.
Attack Complexity: Low - It may not require an advanced skill set or extensive resources to be exploited.
Exploit Maturity: Proof of Concept - While it may not yet be widely exploited,it indicates a heightened risk.

Vulnerable Versions: This vulnerability is identified in PandasAI v1.3.3, llama_cpp_python v0.2.11, and langchain v0.0.314, all dated October 13, 2023.

# Content focus

In this blog post, we focus on a specific type of vulnerability within PandasAI—Arbitrary Code Execution.
The exploit leverages a flaw in the SciPy library, utilizing the imported ctypes module to execute arbitrary code.
The trick was to find the library from whitelisted ones that used “ctypes”. From there we imported “subprocess” and executed shell commands.

![pandasai jailbreak arbitrary code execution 0](/img/posts/tangledgroup-llm-cybersecurity-pandasai-jailbreak-arbitrary-code-execution/pandasai-0-fs8.png)

![pandasai jailbreak arbitrary code execution 1](/img/posts/tangledgroup-llm-cybersecurity-pandasai-jailbreak-arbitrary-code-execution/pandasai-1-fs8.png)

![pandasai jailbreak arbitrary code execution 2](/img/posts/tangledgroup-llm-cybersecurity-pandasai-jailbreak-arbitrary-code-execution/pandasai-2-fs8.png)

![pandasai jailbreak arbitrary code execution 3](/img/posts/tangledgroup-llm-cybersecurity-pandasai-jailbreak-arbitrary-code-execution/pandasai-3-fs8.png)

![pandasai jailbreak arbitrary code execution 4](/img/posts/tangledgroup-llm-cybersecurity-pandasai-jailbreak-arbitrary-code-execution/pandasai-4-fs8.png)

![pandasai jailbreak arbitrary code execution 5](/img/posts/tangledgroup-llm-cybersecurity-pandasai-jailbreak-arbitrary-code-execution/pandasai-5-fs8.png)

# Conclusion

PandasAI, a Python library enhancing pandas with Generative AI, contains a critical security flaw allowing arbitrary code execution.

This vulnerability, identified in PandasAI v1.3.3, llama_cpp_python v0.2.11, and langchain v0.0.314 as of October 13, 2023, stems from the unsafe use of the ctypes module within the SciPy library.

With low attack complexity and its status as a Proof of Concept, this issue hasn't seen active exploitation but holds the potential for serious breach if not addressed promptly.

By running the prompt, we were able to import the subprocess module which was not whitelisted, and call shell commands.

# Prevention

To minimize the risk of exploits stemming from vulnerabilities within PandasAI and its associated dependencies, it is imperative for both individual users and organizations to adopt a proactive approach.

This includes consistently monitoring the official PandasAI website (https://docs.pandas-ai.com) and repositories for the most recent updates, utilizing tools to identify outdated dependencies, and integrating automated security scans into their development processes.

By maintaining an up-to-date environment, users can significantly diminish the risk of potential security breaches triggered by exploitable flaws in outdated software components.

<iframe width="560" height="315" src="https://www.youtube.com/embed/rA0uCGmY7kY?si=rxdykR4uomv9loOR" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" allowfullscreen></iframe>


PandasAI Jailbreak - Arbitrary Code Execution


In an age where information and technology reign supreme, the protection of sensitive data and digital assets has become more critical than ever before. In today's discussion, we explore the complex realm of cybersecurity, with a particular emphasis on the LLM Langchain Tool Exploit and the concept of Arbitrary Code Execution.

Langchain is an open source framework that allows software developers to work with AI and its machine learning subset, combining large language models with other external components to develop LLM-powered applications.

Langchain is made up of several modules that ensure the multiple components needed to make an effective natural language processing (NLP) app can run smoothly.

# Overview

Since Langchain is a relatively new tool but indispensable in the development of LLMs, it is crucial to be aware of the tool's weaknesses. Let's start with the most obvious ones and focus on the concept of Arbitrary Code Execution exploit.

Type of Vulnerability: Arbitrary Code Execution - Execution of arbitrary code could lead to unauthorized and harmful actions.
Attack Complexity: Low - It may not require an advanced skill set or extensive resources to be exploited.
Exploit Maturity: Proof of Concept - While it may not yet be widely exploited,it indicates a heightened risk.

# Content focus

In an effort to realistically present a potential exploit of the existing Langchain tool, we will examine the current situation using the latest versions of Langchain and its Wikipedia tool.

In the following examples, we will present how manipulated data from the Wikipedia tool has the potential to significantly distort results, ultimately guiding LLM toward inaccurate analyses and misleading conclusions.

# Scenario 1

Vulnerability present in Langchain v0.0.224, using Wikipedia v1.4.0.

To demonstrate how the original data has been altered, we will use the featured exploit shown on the right side of the first screen.

![Langchain v0.0.224, using Wikipedia v1.4.0 Code](/img/posts/tangledgroup-llm-cybersecurity-langchain-tool-exploit-arbitrary-code-execution/langchain-wikipedia-0-fs8.png)
![Langchain v0.0.224, using Wikipedia v1.4.0 Terminal](/img/posts/tangledgroup-llm-cybersecurity-langchain-tool-exploit-arbitrary-code-execution/langchain-wikipedia-1-fs8.png)

# Scenario 2

Vulnerability in Langchain v0.0.312 (Oct 12, 2023) and Wikipedia v1.4.0 (Oct 12, 2023).

Unfortunately, even the more recent version has a similar problem, as seen below.

![Langchain v0.0.312 (Oct 12, 2023) and Wikipedia v1.4.0 (Oct 12, 2023) Code](/img/posts/tangledgroup-llm-cybersecurity-langchain-tool-exploit-arbitrary-code-execution/langchain-wikipedia-2-fs8.png)

![Langchain v0.0.312 (Oct 12, 2023) and Wikipedia v1.4.0 (Oct 12, 2023) Terminal](/img/posts/tangledgroup-llm-cybersecurity-langchain-tool-exploit-arbitrary-code-execution/langchain-wikipedia-3-fs8.png)

# Conclusion

In conclusion, the findings from both scenarios unequivocally reveal the persistence of the vulnerability observed in Langchain v0.0.224 when leveraging Wikipedia v1.4.0. with Scenario 2 revealing the emergence of a new, analogous vulnerability in the latest Langchain v0.0.312 (as of October 12, 2023).

These results underscore the ongoing need for rigorous security assessments and updates in Langchain's development to ensure a safer and more robust platform.

# Prevention

It's crucial to consistently update the Langchain version to forestall the disclosure of any weaknesses in Langchain and its associated Wikipedia tool.

Strengthened security protocols are crucial to protect the communication between the end user and the LLM infrastructure, ensuring users are alerted if their conversations have been intercepted or modified.

It's imperative to introduce new detection systems at the application level to further ensure a safer environment.

Join us in our quest to navigate the complex landscape of cybersecurity and to foster a safer digital world for all.

<iframe width="560" height="315" src="https://www.youtube.com/embed/vs5P7IhGx1A?si=SK5NqdN6yHy1bati" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" allowfullscreen></iframe>


Langchain Tool Exploit - Arbitrary Code Execution


As today's world has embraced LLM as an indispensable tool, the question of cyber protection for LLM has gained particular significance.

Our mission is clear: to equip you with the knowledge and insights necessary to safeguard your digital world. In this installment, we delve into a pervasive and ever-evolving menace - Man-in-the-Middle Attack, aka MITM.

# Expected User Information Flow

Under usual circumstances, an innocent user anticipates a smooth flow of information from the Client to the WEB API, to the LLM API, and finally to third-party services like Wikipedia’s API.

![Expected User Information Flow](/img/posts/tangledgroup-llm-cybersecurity-mitm-attack/4-fs8.png)

But in reality, this flow is actually riddled with potential attack points.

![Threats of User Information Flow](/img/posts/tangledgroup-llm-cybersecurity-mitm-attack/10-fs8.png)

As we can see from this example, there are at least five possible scenarios for compromising this flow.

# Threats to User Information Flow

- Scenario 1:
  - Hijacked LLM API
- Scenario 2:
  - Hijacked LLM API
  - Hijacked Wikipedia API
- Scenario 3:
  - Hijacked Wikipedia API
- Scenario 4:
  - Hijacked Web API
  - Hijacked LLM API
  - Hijacked Wikipedia API
- Scenario 5 (our scenario):
  - Hijacked Web API

In order to provide a deeper understanding of the issue, we will analyze one of the scenarios and use the example of a "Hijacked Web API."

![Compromised local network MITM](/img/posts/tangledgroup-llm-cybersecurity-mitm-attack/17-fs8.png)

In this case, the Client is not aware of communicating with a malicious Web API.
Actually, the whole process of attack has a few basic steps:

- The Attacker spoofs the ARP tables of the Router and Client targets, making the Router and the Client think they should connect to the Attacker instead of each other.
- The Attacker now acts as a gateway/router.
- The Attacker installs reverse proxy Caddy to handle redirected traffic/domain, allowing them to intercept and control the communication between the Client and the intended destination.
- The Attacker strips SSL and downgrades HTTPS to HTTP, potentially exposing sensitive information to interception or theft.
- The Attacker sets a fake DNS entry, leading the Client to a harmful reverse proxy that captures and reroutes traffic.

In this way, the Client may not notice that the connection is not secure and that the domain is being rerouted through a malicious proxy.

![Poisoned ARP Table](/img/posts/tangledgroup-llm-cybersecurity-mitm-attack/poisoned-arp-table-0-fs8.png)

# Prevention of Man-in-the-Middle (MITM) Attacks

1. Setup SSL/TLS and always use HTTPS:

- Ensure secure data transmission by encrypting communication channels.
- Validate authenticity of websites.

2. Enforce HTTP Strict Transport Security (HSTS):

- Mandate the use of HTTPS, preventing downgrade attacks.
- Preload HSTS in browsers for enhanced security.

3. Manual DNS Configuration:

- Set DNS records to trusted servers like 1.1.1.1 and 8.8.8.8 to impede unauthorized alterations by attackers.

4. Establish a Secure VPN:

- Utilize VPNs configured in a secure environment prior to any network compromise.
- Maintain privacy and integrity of data in transit.

# Conclusion

As the reliability of traffic is compromised by network, API, and LLM vulnerabilities, users may receive incorrect or unreliable results from LLM models.

Strengthened security protocols are crucial to protect the communication between the end user and the LLM infrastructure, ensuring users are alerted if their conversations have been intercepted or modified.

It's imperative to introduce new detection systems at the application level to further ensure a safer environment.

<iframe width="560" height="315" src="https://www.youtube.com/embed/tgsJVqLNAvg?si=HmGR16bTYBwLE4Ba" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" allowfullscreen></iframe>


Cybersecurity of GenAI, LLM - MITM Attack

New York's renowned benefactors and the beating heart of the city came together to support IT education in Serbia on Friday, November 12th, 2021. The second gala evening, organized by the Serbian Philanthropic Society in the magnificent Gotham Hall, brought together people who support and understand the importance and necessity of investments in Information Technology education.

The goal of this gathering was a genuine support to the Serbian organization "IT Bootcamp". It is a free IT school for retraining in the IT sector in Serbia, a non-profit organization whose founder is the “ Ana and Vlade Divac ” foundation. School courses provide a formal IT education that provides opportunities for directly paid internships and employment in the IT world. "IT Bootcamp" has enabled almost 1000 students to acquire knowledge and skills for a successful transition to the IT world. More than 400 candidates were able to apply for acquired expertise and knowledge through work and paid internships. It is important to note that the courses at IT Bootcamp are completely free and that this organization is fully funded by its donations. It is one more reason to understand and support the efforts, organization, and great commitment of the Serbian Philanthropic Society to gather numerous donors and people in New York City who were able to support the continuation of the successful work of "IT Bootcamp" with their donations. Our company "TangledHub" is proud of the fact that its teams have hired several outstanding colleagues who attended IT BootCamp's courses, and who are now valuable support to our own work and creation. We are very proud of them. Also, "TangledHub" was committed, and in accordance with its capabilities supported the event of the Second Gala Evening in Gotham Hall.

It was an immense pleasure to contribute in any way to those who, through their work, commitment and talent, have done their best to achieve the progress and development of the society. As a company, our principal idea is that education, culture, art, skill, and humanity have to be the cornerstones of the development of a good, and above all, functional society.

Thanks to the generous donations of the 420 guests present, the total sum of $ 70,200 were raised and will provide free training for 200 new students of the non-profit “IT Bootcamp” school for retraining in the IT sector in Serbia. It was a great pleasure to be involved in and contribute to this mission.

The tangled team would also like to draw your attention to the photos of our dear associates and friends who took part in this exceptional, festive dinner. The representatives of our team could not attend this Gala night event due to the newly announced epidemiology measures, which were passed by the authorities just a few days before the event.



![Gala evening](/img/serbian_gala_evening/main.jpg)

Serbian Philanthropic Gala evening


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---

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- **Safe Passwords & MFA Policy**
  - Enhance the security of user accounts
- **Automated Monitoring and Reporting**
  - Traceability of users’ actions
- **Infrastructure Separation**
  - Data and System layer
- **Encoding of PHI**
  - Cryptographic signatures
- **Encryption of PHI**
  - Cryptographic keys
- _Planning for Potential Account Breaches and Remote Deactivation Process_
  - _Legal and technical understanding and implementation_
- **Secure Software Development Lifecycle**
  - Systematic approach integrating security practices throughout the entire software development process
- **Data Privacy**
  - Collect only the essential data required
- **De-Identification/Anonymization**
  - Transforming/Obfuscating data to minimize the risk in case of data breaches

---

## Current Challenges

1. Companies’ technical safeguards have been compromised
2. Companies have violated HIPAA regulations
3. Security breaches have resulted in the exposure of patient data

---

## Recommended Solutions

- Detailed audit of all teams and systems
  - Lacking HIPAA-related technical knowledge is essential to identify knowledge gaps, assess compliance practices, evaluate risks, plan remediation efforts, and implement corrective measures
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  - Modifying the structure and design of information systems to enhance security
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- Active Development, SecOps, and DevOps teams
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- Reinforced security is a journey, not a destination

---

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- Progress towards enhanced, sustainable HIPAA compliance
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- System security is a long-term investment
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With our combined efforts, we can transform your company from the (potential) aftermath of a breach to a shining example in patient data security.

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- Complete audit of all your company
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HIPAA - Advancing Towards Security Excellence


This text provides a roadmap for key aspects of HIPAA Technical Safeguards, though it doesn't cover all complexities and nuances. It should serve as a starting point to address the most common issues.

HIPAA (Health Insurance Portability and Accountability Act) Technical Safeguards are vital for several reasons:

- **Data Protection**: They ensure the confidentiality, integrity, and availability of electronic protected health information (e-PHI), safeguarding it from unauthorized access, alteration, deletion, and transmission.
- **Access Control**: They provide a means to control and monitor who has access to e-PHI, reducing potential breaches.
- **Audit Controls**: These mechanisms record and examine activity in information systems, helping detect and respond to potential violations or security incidents.
- **Transmission Security**: It protects e-PHI during electronic transmission over networks, mitigating the risk of interception.
- **Data Integrity**: They ensure e-PHI is not altered or destroyed in an unauthorized manner, maintaining the accuracy and reliability of data.
  In summary, HIPAA Technical Safeguards play a key role in maintaining patient data privacy and ensuring trust in the healthcare system.

### Access Controls

This standard involves unique user IDs, password management, and also mandates automatic logoff, encryption, and emergency access protocols.

This requirement refers to the Access Control standard under the HIPAA Security Rule, specifically:

- **Unique User Identification**: Each user must have a unique ID to track individual activity and hold users accountable for their actions.
- **Password Management**: Systems must implement procedures for creating, changing, and protecting passwords to ensure secure user authentication.
- **Automatic Logoff**: To prevent unauthorized access, systems should automatically logoff users after a defined period of inactivity.
- **Encryption**: This helps protect data during storage and transmission, making it unreadable to unauthorized users.
- **Emergency Access Procedures**: In case of an emergency, these procedures ensure critical e-PHI can be accessed. This allows patient care to continue uninterrupted while still safeguarding information.
  These specifications help ensure only authorized personnel can access e-PHI, thus maintaining confidentiality and integrity of the data.

### Audit Controls

The Audit Controls standard mandates that Covered Entities and Business Associates employ software for logging and analyzing activity in systems holding ePHI.

HIPAA Audit Controls standard refers to the policies and procedures in place to monitor and record activity in systems that contain or use electronic protected health information (e-PHI).

- **Record Activity**: These controls generate detailed logs documenting user activities, system events, and other data interactions.
- **Examine Activity**: These controls also entail the regular review and analysis of the recorded activity to detect anomalies, potential breaches, or improper access.

The goal is to enhance accountability, enable the detection of violations or security incidents, and provide forensic evidence in case of breaches, thereby protecting e-PHI and maintaining compliance with HIPAA.

### Integrity Controls

Measures must be enacted to protect ePHI from unauthorized changes or destruction, addressing both internal and external threats.

HIPAA Integrity Controls refer to measures to protect electronic protected health information (e-PHI) from unauthorized alteration or destruction.

- **Protection from Alteration/Destruction**: These controls validate the authenticity of data, ensuring it remains accurate and complete during storage and transmission.
- **Internal and External Threats**: They protect against both external threats like hacking, and internal threats such as accidental modification or deliberate misuse by employees.

This ensures the reliability and trustworthiness of e-PHI, which is crucial for effective patient care and maintaining trust in the healthcare system.

### Person or Entity Authentication

This standard mirrors the user ID requirements of the Access Controls standard, emphasizing the need for a robust password management policy.

The Person or Entity Authentication standard under HIPAA mandates that covered entities and their business associates must verify the identity of a person or entity seeking access to electronic protected health information (e-PHI).

- **User Identification**: It's about ensuring that the person or entity is indeed who they claim to be, often through unique user IDs and strong password protocols.
- **Password Management**: Effective password policies enforce creation of strong passwords, regular password changes, and not reusing old passwords, thus preventing unauthorized access.

This standard is crucial to prevent unauthorized access to e-PHI, thereby maintaining its confidentiality and integrity.

### Transmission Security

While Integrity Controls safeguard ePHI during authorized access, this standard ensures the security and integrity of ePHI in transit, preventing unauthorized alteration or destruction.

The Transmission Security standard under HIPAA requires the protection of electronic protected health information (e-PHI) while it's being transferred over an electronic network.

- **Integrity**: It mandates measures to ensure that e-PHI is not altered or destroyed during transmission.
- **Security**: It also involves implementing security measures like encryption to prevent unauthorized access or interception during transmission.

So, this standard is about maintaining the confidentiality and integrity of e-PHI during electronic transmission, safeguarding it from potential breaches.


HIPAA Technical Safeguards


This is not a comprehensive guide, but rather a roadmap addressing the most evident issues related to the HIPAA IT Compliance Checklist. Additional considerations and specific requirements may exist depending on the organization's unique circumstances.

HIPAA (Health Insurance Portability and Accountability Act) IT compliance checklist is a guide ensuring the safeguarding of Protected Health Information (PHI) stored or transmitted electronically. Key components include:

- **Risk Analysis**: Regularly identify potential risks and vulnerabilities to PHI.
- **Risk Management**: Implement measures to manage identified risks and reduce them to reasonable levels.
- **Administrative Safeguards**: Assign a privacy officer responsible for the development and implementation of HIPAA policies and procedures.
- **Physical Safeguards**: Controls must be in place to limit physical access to information systems storing PHI.
- **Technical Safeguards**: This includes access controls, audit controls, integrity controls, and transmission security.
- **Policies and Procedures**: Detailed written policies need to be in place regarding the handling of PHI and should be reviewed and updated regularly.
- **Employee Training**: Regular training on HIPAA regulations and company policies to all employees handling PHI.
- **Business Associate Agreements**: Ensure agreements are in place with third-party associates who have access to PHI, mandating they too follow HIPAA regulations.
- **Emergency Plan**: Create a contingency plan to handle emergencies that can impact systems storing PHI.
- **Breach Notification**: Have a plan in place to notify affected individuals, HHS, and potentially the media in case of a breach of unsecured PHI.

Non-compliance can lead to substantial fines, so it's crucial for healthcare organizations to regularly review and adhere to this checklist.

### Safe Passwords & MFA Policy

The Safe Passwords & MFA policy demands the use of distinct, complex passwords for each account to secure user data. It is further reinforced by compulsory Multi-Factor Authentication (MFA), where possible, to provide an additional layer of security by requiring multiple forms of identification from the user.

### Monitoring and Reporting

Monitoring and Reporting refers to the automatic tracking and documentation of user activities and potential security threats. This is done to lessen the manual workload related to ensuring user compliance with security policies and managing cyber threats, thus enhancing efficiency and effectiveness in dealing with potential issues.

### Infrastructure Separation

Infrastructure Separation involves dividing the system into a data layer and system layer. This enhances system integrity by ensuring that each layer performs its specific functions efficiently. Moreover, it isolates attacks, preventing them from spreading across the entire system and thus safeguarding against extensive damage.

### Encoding of PHI

Encoding of Protected Health Information (PHI) means employing coding techniques to secure electronic PHI (ePHI). This protects the data from unauthorized alterations, supporting compliance with data protection regulations and maintaining the integrity of the ePHI.

### Encryption of PHI

Encryption of Protected Health Information (PHI) means converting the data into a code when it's being stored or transmitted. This makes the PHI unreadable to unauthorized individuals, thus securing it from unauthorized access.

### Planning for Potential Account Breaches and Remote Deactivation Process

Planning for Potential Account Breaches and Remote Deactivation Process refers to having strategies ready for the eventuality of account credential breaches. This includes having mechanisms in place to quickly identify and disable compromised accounts from any location, thereby limiting potential damage and unauthorized access.

### Secure Software Development Lifecycle

Secure Software Development Lifecycle refers to incorporating security practices into every stage of the software development process. This includes following safe coding standards and carrying out frequent security audits to identify and fix potential vulnerabilities that might expose Protected Health Information (PHI).

### Data Privacy

Data Privacy, in this context, means the software should be developed to only gather the bare minimum data required, aligning with the 'minimum necessary' principle of HIPAA. This approach minimizes the risk of exposing sensitive information and helps uphold individuals' privacy rights.

### De-Identification

De-Identification refers to the process of removing or obscuring any personal identifiers from data. When personal identification isn't necessary, de-identifying the data is advisable to lower the risk of exposing sensitive information in case of a data breach.

### Business Associate Agreement (BAA)

A Business Associate Agreement (BAA) is a legally binding document signed by developers and third parties. It ensures that these third parties, who may handle protected health information (PHI) on behalf of the entity, are aware of and comply with the necessary security measures as outlined in HIPAA regulations.


HIPAA IT Compliance Checklist


In the world of healthcare, where patient privacy and data security are of utmost importance, partnering with IT support and software development teams that understand and adhere to **HIPAA** compliance requirements is essential. By adhering to **HIPAA** regulations, insurance companies can protect sensitive healthcare data, build trust and reputation, meet legal requirements, and reduce cybersecurity risks.

**TANGLED** clients have faced this problem before, therefore we feel the need to emphasize and address this problem that is easily solvable but still is a big struggle for the majority of organizations. With successful projects completed for industry leaders, we have demonstrated our commitment to safeguarding patient data and ensuring compliance with **HIPAA** regulations.

Failure to comply with **HIPAA** regulations can have severe consequences for insurance companies. The Department of Health and Human Services (HHS) has the authority to enforce **penalties** for non-compliance, which can result in significant financial and legal repercussions. The penalties vary based on the extent and duration of the violation, but by being non-compliant with **HIPAA**, organizations are subject to monetary penalties of up to **$250,000**, jail time of up to **5 years**, and lawsuits (civil and criminal).

While **HIPAA** compliance is crucial, it is equally important to learn from the mistakes of those who have faced **HIPAA** violations. The most recent healthcare data breach reports are listed at: [Hippa breach news](https://www.hipaajournal.com/category/hipaa-breach-news/)

The Department of Health and Human Services (HHS) also maintains a [Wall of Shame](https://ocrportal.hhs.gov/ocr/breach/breach_report.jsf), a public listing of reported breaches of unsecured protected health information (PHI) **affecting 500 or more individuals**.

By learning from these incidents and partnering with IT support and software development teams that prioritize **HIPAA** compliance, healthcare organizations can minimize the risk of breaches and protect patient privacy in an increasingly digital healthcare landscape.

Software development plays a crucial role in achieving and maintaining **HIPAA** compliance. Comprehensive Security Measure that we implement:

Robust Access Controls: We understand the importance of granting access to patient data on a need-to-know basis. Our software development teams employ role-based access controls (RBAC), ensuring that only authorized personnel can access sensitive information. This helps prevent unauthorized data breaches and maintains the confidentiality of patient data.

Data Encryption: To safeguard patient information during transmission and storage, we implement industry-standard encryption protocols. This includes securing data transfers using Transport Layer Security (TLS) or Secure Sockets Layer (SSL), and employing encryption algorithms to protect data at rest within databases and storage systems.

Regular Audits and Monitoring: Our commitment to maintaining **HIPAA** compliance extends to conducting regular audits and monitoring of IT systems. This proactive approach helps identify potential vulnerabilities, detect any suspicious activities, and address security weaknesses promptly. By staying vigilant, we ensure that our clients' data remains secure and protected.

Business Associate Agreements (BAAs):
Recognizing our role as a trusted partner to healthcare organizations, we proactively enter into Business Associate Agreements (BAAs) with our clients. These agreements define the responsibilities and obligations of both parties in safeguarding patient data and maintaining **HIPAA** compliance. Our commitment to compliance extends beyond technology and is ingrained in our partnerships.

In addition to financial penalties, non-compliance can lead to legal disputes, damage to the company's reputation, and loss of customer trust. Insurance companies found to be non-compliant may face lawsuits from affected individuals, regulatory investigations, and potential exclusion from participating in government healthcare programs.

We understand the unique challenges faced by healthcare organizations in protecting patient data while leveraging technology to enhance care delivery. By implementing robust security measures, following secure coding practices, and maintaining a proactive approach to compliance, we ensure the confidentiality, integrity, and availability of sensitive information.


Achieving HIPAA Compliance in IT Support and Software Development


Sometimes we forget to stop and appreciate the good things that happen around us, including those of our own making. We are writing this blog post with a little dose of pride.

TangledHub is now a team of over 30 members. Our passion is growing stronger every day. The company has started as a small venture with just a few members - a small team, but that of visionaries. We wanted to have a company that is different, the one that produced great results but also cares about the people. There is no doubt that running a business requires grit and determination. We faced many monsters along the way. Statistically, only 40% of small businesses survive beyond their 5th year of trading. So, this anniversary is a personal milestone for us.

![Old office](/img/th5anni/stari_kanc.jpg)

As we grow, we push the boundaries by working smarter and faster. Every member of our excellent team plays an important role in the development of our company.
It is enthusiasm, support, and dedication that have brought us to this point.

![Team working](/img/th5anni/koncentracija.jpg)

In the last 5 years, we have worked together…
We have delivered great results in the field of software development. INNOVATION and HARD WORK have been the key to our success. TangledHub strives to deliver the best to all clients. We are grateful to all who trusted us to help provide immaculate services and products. Dear clients, your demands, challenges, and feedback have pushed us to move forward and improve tremendously. Now, looking back, we know we wouldn’t have made it if it wasn’t for you. Your confidence in us has brought about this 5th anniversary. You made us who we are today. Thank you.

Today it’s not just a company anniversary. It’s time to celebrate our expansion with the brand new office space in Niš. It’s time to celebrate rising and spreading and a new beginning in office space in Niš.

![Team happy](/img/th5anni/radno.jpg)


TangledHub 5th anniversary!


# Introducing llama-cpp-wasm

In the rapidly evolving landscape of web development, the quest for high-performance applications often leads developers to explore solutions beyond the traditional JavaScript ecosystem. One such groundbreaking technology is **WebAssembly** (Wasm), which enables code written in languages like **C++** to run on the web at near-native speed. Today, we're excited to delve into [llama-cpp-wasm](https://github.com/tangledgroup/llama-cpp-wasm), a project that offers Wasm build and bindings for [llama.cpp](https://github.com/ggerganov/llama.cpp), alongside a compelling online demo that showcases its capabilities.

[https://github.com/tangledgroup/llama-cpp-wasm](https://github.com/tangledgroup/llama-cpp-wasm)

# What is llama-cpp-wasm?

llama-cpp-wasm is a project that brings the power of llama.cpp, a high-performance C++ library, to the web using WebAssembly. This initiative opens up new possibilities for web developers to leverage the computational efficiency and speed of C++ in web applications, making it easier to handle complex tasks directly in the browser without compromising on performance.

# Experience It Yourself: Online Demo

To witness the capabilities of **llama-cpp-wasm** firsthand, visit the online demo at [https://llama-cpp-wasm.tangledgroup.com](https://llama-cpp-wasm.tangledgroup.com). This demo provides a practical illustration of how **llama-cpp-wasm** can be utilized within a web environment, offering a glimpse into the future of web application development where the boundaries between native and web performance begin to blur.

# Conclusion

**llama-cpp-wasm** stands at the intersection of modern web development and high-performance computing, offering a tantalizing glimpse into the future of the web. By bridging the gap between C++ and JavaScript through WebAssembly, it unlocks new possibilities for developers to create more powerful and efficient web applications. Whether you're building complex data processing tools, sophisticated web games, or any application that demands high performance, llama-cpp-wasm offers a compelling solution that leverages the best of both worlds.


Introducing llama-cpp-wasm

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We wish you...
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In the year behind us, we worked on many different projects, researched and applied new techologies. We found new partnerships, experiences and fresh business contacts. Teamwork based on trust, cooperation and support has made us grow. We are approaching the New Year with great expectations to continue successful contact with our valued clients. We are looking forward to making new contacts, interesting projects and new challenges.

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Hi!

We are happy to announce that we are sharing and outsourcing our _TangledHub Platform_ libraries, that _Tangled_ team has built over the course of last few years.

We would like you to use it to build better and faster software, the one that is better tested, and to create more value for the community, for yourself, for your commercial needs...

The whole code and TangledHub Platform libraries will be completely open source. It comes with documentation, examples, tests, and instructions.

Use it,
create it,
mix it,
enjoy it...

It’s up to you!

Show us and the world what you can build!

Tangled Team sends its regards, and wishes you Happy Holidays with faith in future sharing, developing, exchanging and promotion of knowledge and experiences.

## thresult

TangledHub **thresult** library for handling returned values from functions/methods and handling errors. Result is a type that represents either success **Ok** or failure **Err**.

[https://gitlab.com/tangledlabs/thresult](https://gitlab.com/tangledlabs/thresult)

## thcrypto

TangledHub **thcrypto** library for **[cryptography](https://cryptography.io)**.

[https://gitlab.com/tangledlabs/thcrypto](https://gitlab.com/tangledlabs/thcrypto)

## thcouch

TangledHub _thcouch_ library for **[CouchDB](https://couchdb.apache.org/)** with a focus on asynchronous functionality. It comes with **core**, **orm** and **declarative** APIs.

[https://gitlab.com/tangledlabs/thcouch](https://gitlab.com/tangledlabs/thcouch)

## thquickjs

TangledHub **thquickjs** library for creating JavaScript/ES2020 context and **Python** bridge.
**[QuickJS](https://bellard.org/quickjs/)** is a small and embeddable JavaScript/ES2020 engine.
Safely evaluates untrusted JavaScript code.
Creates and manipulates values inside the QuickJS runtime.
Expose host Python functions to inner QuickJS runtime.

[https://gitlab.com/tangledlabs/thquickjs](https://gitlab.com/tangledlabs/thquickjs)

## thcrdt

TangledHub **thcrdt**, CRDT, Conflict-free Replicated Data Type, based on awesome projects **[QuickJS](https://bellard.org/quickjs/)** and **[automerge](https://github.com/automerge/automerge)**.

[https://gitlab.com/tangledlabs/thcrdt](https://gitlab.com/tangledlabs/thcrdt)

## thlock

TangledHub **thlock** library implementing distributed locking mechanism using great **[etcd](https://etcd.io/)** with a focus on asynchronous functionality.

[https://gitlab.com/tangledlabs/thlock](https://gitlab.com/tangledlabs/thlock)

## thconfig

TangledHub **thconfig**, config reader/writer, enabling various ways to read and write configuration data.  
It supports reading and writing configuration data from file system, **[CouchDB](https://couchdb.apache.org/)** database or **[etcd](https://etcd.io/)** host.

[https://gitlab.com/tangledlabs/thconfig](https://gitlab.com/tangledlabs/thconfig)

TangledHub Open-Source Libraries


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- **Python**: Known for its versatility and efficiency, Python is our go-to language for developing powerful backend systems and AI/ML solutions.

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Custom Software Development Services


## Introducing USearch: The New Benchmark in Vector Search

In today's high-tech world, the search for efficient and streamlined solutions is a never-ending quest. When it comes to vector search engines, there's a new kid on the block that is making waves: **USearch**. This blog post aims to highlight the incredible capabilities of USearch and draw a comparison with the recognized leader in this arena, **FAISS**.

Both **USearch** and **FAISS** harness the power of the **Hierarchical Navigable Small Worlds** (**HNSW**) algorithm.

![Hierarchical Navigable Small Worlds HNSW](/img/ai/pinecone-faiss-hnsw.png)

## What Makes USearch Stand Out?

1. **Top-of-the-Line Performance**: USearch boasts of benchmark-topping performance, setting new standards in the vector search domain.

2. **Simplicity in Design**: Its simple and extensible design comes from a single C++11 header implementation, ensuring ease of use.

3. **Optimized Functionality**: USearch is SIMD-optimized, supports user-defined metrics with JIT compilation, and variable dimensionality vectors. This means unique applications like searching over compressed data are well within its realm.
4. **Application in Genomics and Chemistry**: With Bitwise Tanimoto and Sorensen coefficients, it is aptly suited for Genomics and Chemistry applications.

5. **Precision and Hardware Compatibility**: USearch supports half-precision & quarter-precision and is hardware-agnostic, making it flexible across platforms.

6. **Efficiency in Handling Data**: You can view large indexes from disk without the necessity of loading them into RAM. It also provides space-efficient point-clouds, accommodating a size of 4B+.

7. **Flexibility with CPU Usage**: Compatibility with OpenMP and custom "executors" ensures that users have fine-grained control over CPU utilization.

8. **Additional Features**: USearch stands out with its support for heterogeneous lookups, renaming/relabeling, on-the-fly deletions, Semantic Search, and Joins.

## How Does USearch Compare with FAISS?

FAISS has long been the gold standard in high-performance vector search engines. Both USearch and FAISS harness the power of the HNSW algorithm. However, they have divergent design principles. While FAISS is comprehensive, USearch offers broad compatibility without compromising on performance.

At its core, **USearch** aligns with **FAISS** in terms of basic functionality. If you're familiar with Approximate Nearest Neighbors search, you'll find the interface quite intuitive.

In conclusion, USearch is a promising new entrant in the vector search engine domain. Its wide range of features combined with its focus on user-defined metrics makes it a worthy contender for various applications. As technology continues to evolve, it's tools like USearch that push the envelope, challenging established norms and setting new benchmarks in performance and efficiency.

## Links

[USearch GitHub Repository](https://github.com/unum-cloud/usearch)


USearch - Smaller & Faster Single-File Vector Search Engine


## UForm: Multi-Modal Transformers Library for Semantic Search Applications

UForm is a library designed to encode multi-lingual **texts** and **images** (and soon audio, video, and documents) into a **shared vector space**. It offers pre-trained networks that are compact and efficient, suitable for deployment from large servers to mobile devices. The models are available on [HuggingFace](https://huggingface.co/unum-cloud).

## Types of Multi-Modal Encoding

### Late-fusion models

Encode each modality independently into one shared vector space, capturing coarse-grained features. Suited for retrieval in extensive collections.

### Early-fusion models

Encode both modalities jointly, capturing fine-grained features. Used for re-ranking small retrieval results.

### Mid-fusion models

Blend between the previous two. Includes unimodal and multimodal parts. The latter enhances features with a cross-attention mechanism.

![UForm: Multi-Modal Transformers Library for Semantic Search Applications](/img/ai/uform_model_types_bg.png)

## Evaluation

### Cosine Similarity

Computationally cheap and only requires unimodal embeddings, which are faster than joint encoding. However, it only considers coarse-grained features.

### Matching Score

Requires joint embedding, capturing fine-grained features. Suitable for re-ranking but resource-intensive.

## Models Architecture

### English Model

Uses BERT (2 layers) for language, ViT-B/16 for images, and has a 2-layer multimodal part.

### Multilingual Model

Uses BERT (8 layers), ViT-B/16, and a 4-layer multimodal part. This model supports 11 languages, and it was trained using translated captions.

## Links

[UForm GitHub Repository](https://github.com/unum-cloud/uform)


Embedding Text/Image using UForm into Vectors


## Exploring Sentence Transformers: An Overview

**Sentence Transformers** has established itself as a powerful tool that delivers dense vector representations for sentences, paragraphs, and images. It's made use of influential transformer architectures such as BERT, RoBERTa, and XLM-RoBERTa to offer best-in-class performance across a variety of tasks.

![SentenceTransformers SBERT](/img/ai/SentenceTransformers.png)

## Key Features

1. **Diverse Pretrained Models**: Sentence Transformers showcases [pretrained models](https://www.sbert.net/docs/pretrained_models.html) for over 100 languages, customized for different applications.

![SentenceTransformers SBERT](/img/ai/SentenceTransformers-3.png)

2. **Custom Fine-Tuning**: For tasks with unique requirements, the framework lets users [fine-tune custom embedding models](https://www.sbert.net/docs/training/overview.html) ensuring optimal task-specific performance.

![SentenceTransformers SBERT](/img/ai/SentenceTransformers-2.png)

3. **Research-backed**: Its capabilities are backed by a series of research publications, including notable ones from EMNLP 2019, NAACL 2021, and several arXiv papers.

4. **Easy Installation and Setup**: You can easily get started with Sentence Transformers using pip, conda, or by directly installing from the sources. It recommends using Python 3.6 or higher and requires certain versions of PyTorch and transformers.

5. **Quick Start with Pre-trained Models**: Incorporating Sentence Transformers into your project is as simple as downloading a pretrained model and embedding your sentences.

6. **Train Your Model**: If the pretrained models don't fit the bill, you can train your own! The framework supports a multitude of transformer networks, offers evaluation during training, and provides [various loss-functions](https://www.sbert.net/docs/package_reference/losses.html) for model tuning.

7. **Proven Performance**: The models have been extensively evaluated on over 15 datasets, including challenging domains like Tweets and Reddit, consistently outperforming other sentence embedding methods.

8. **Versatile Applications**: The framework isn't just about sentence embeddings. It can be utilized for semantic textual similarity, clustering, paraphrase mining, semantic search, text summarization, multilingual image search, and much more.

![SentenceTransformers SBERT](/img/ai/SentenceTransformers-1.png)

## Links

[Sentence Transformers GitHub Repository](https://github.com/UKPLab/sentence-transformers)


Sentence Transformers - Multilingual Text/Image Embeddings


## Embedding into Vectors and Leveraging Vector Databases: A Primer on LLMs

Modern advancements in data science and machine learning have given rise to an array of methods to represent, store, and retrieve information. Among these are embeddings, which allow us to represent complex entities such as words, images, and more in continuous vector spaces. With this representation, we can efficiently perform operations, comparisons, and searches. But, how do we store and manage these vectors efficiently? Enter vector databases. Let’s dive deep into the world of embeddings and the importance of leveraging vector databases, especially for Large Language Models (LLMs).

![Word Embedding](/img/ai/word-embedding.png)

## 1. What are Embeddings?

Embeddings are mathematical representations that capture the essence of data in a lower-dimensional space, often as vectors. They are central to many machine learning tasks, and here's why:

- **Dimensionality Reduction:** Converting data, especially high-dimensional ones, into vectors of fixed size makes computation more manageable.
- **Semantic Meaning:** In the case of word embeddings, similar words or phrases will have similar vectors. This means that 'king' and 'monarch' might have vectors that are closer in space compared to 'king' and 'apple'.
- **Versatility:** They can represent anything – from text (like in SentenceTransformers) to multimedia (like UForm which is Multi-Modal Transformers Library For Semantic Search Applications).

## 2. Why Use Vector Databases?

Storing vectors in traditional databases may not be efficient for operations like similarity search. Vector databases are specialized databases optimized for storing and querying vectors, offering:

- **Fast Similarity Searches:** Retrieve items based on vector similarity rapidly.
- **Scalability:** Efficiently store millions to billions of vectors.
- **Flexibility:** They can handle vectors from various sources, be it from natural language processing, computer vision, or other domains.

## 3. Large Language Models (LLMs) and Embeddings

LLMs like GPT, BERT, and their variants are reshaping the NLP landscape. They are trained on massive text corpora and can generate coherent text, understand context, and more. The secret sauce? Embeddings.

- **Contextual Embeddings:** Unlike static word embeddings, LLMs produce contextual embeddings. This means the embedding for the word 'bank' will differ based on its use (river bank vs. financial bank).
- **Transfer Learning:** Once trained, the embeddings from these models can be used for various NLP tasks without retraining the entire model - a phenomenon called transfer learning.

## 4. The Synergy Between LLMs and Vector Databases

When we extract embeddings from LLMs for our dataset (say, a collection of documents), we're left with millions of vectors. To use them efficiently:

- **Store with Precision:** Vector databases ensure embeddings are stored without loss of information.
- **Query with Speed:** Whether you're building a recommendation system or a semantic search engine, you can quickly retrieve relevant vectors.
- **Scale with Grace:** As your data grows, vector databases can handle the increased load while ensuring performance.

## 5. Popular Vector Databases

Several vector databases have sprung up to cater to the growing demand:

- **USearch:** An open-source small & fast single-file Vector search engine / database.
- **FAISS (Facebook AI Similarity Search):** Developed by Facebook AI, optimized for fast similarity search and clustering of dense vectors.
- **chroma:** The AI-native open-source embedding database.

## Conclusion

As the realm of AI continues to grow, embeddings have taken center stage, offering compact and meaningful representations of data. Large Language Models utilize these embeddings to comprehend and generate human-like text. Vector databases, on the other hand, serve as the perfect companion, ensuring that the power of embeddings is utilized to its maximum potential. Whether you're an NLP practitioner, a data scientist, or just an AI enthusiast, understanding and leveraging this synergy is bound to propel your projects to new heights.


Embedding into Vectors and leveraging Vector Databases

# Now, even closer to our partners!

Tangled team is pleased to inform you that our business is expanding and we are wide open to cooperation.
We are focused on the world-wide market and understanding the complex requirements, challenges, and demands set before our clients and partners.



**Tangled Group, Inc. has arrived in the USA.**

We are looking to build a great future together with clients and partners.

Tangled is here to provide the full spectrum of software support and solutions.

We are here for you.

Your Tangled Group, Inc.

Tangled Group, Inc. has arrived in the USA

This open position is for a web developer with experience in React, a popular JavaScript library for building user interfaces.

React Frontend Developer

We are looking for a skilled developer who can build mobile applications using React Native, a framework for building native apps using React.

React Native Mobile Developer

This job opening is for a developer with expertise in Python and aiohttp, Flask, Django, and/or FastAPI high-level web frameworks that enables the creation of complex web applications.

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