Introducing CodeThreat AI Assistant, Personal Code Analysis Expert.
As developers strive to create and deploy applications quickly, security problems grow, and vulnerabilities accumulate. CodeThreat offers an avant-garde solution that combines the power of AI with Static Application Security Testing (SAST) to provide comprehensive security insights and remediation suggestions for your codebase.
Using Fine-Tuned Language Models, specifically Code-DaVinci and GPT-3.5 for Security-Specific Expertise to create a solution that excels in improved security suggestions, flaw remediation and attack scenario generating, we understand its necessary to use domain-specific datasets with supervised learning.
Moreover, we utilized LangChain, an innovative framework designed for developing applications powered by language models, to automate the AI processes within our solution. LangChain not only allows us to connect language models to other data sources but also enables the models to interact with their environment, making our AI-driven security solutions more powerful and efficient.
Here are the current capabilities of the CodeThreat AI Assistant on our CodeThreat findings;
- Vulnerable code fix suggestions,
- Taint flow explanations,
- Possible attack scenarios for better vulnerability understandings
One of the primary concerns when using AI platforms is data privacy. While OpenAI offers powerful AI capabilities, it can also raise privacy concerns for some organizations. By utilizing Microsoft Azure, we can ensure that our customer’s data is secure and protected while leveraging the power of OpenAI’s advanced AI models.
Let’s go over the capabilities one by one.
Possible Attack Scenarios
Our AI Assistant allows your team to anticipate and assess the potential threats posed by each vulnerability located by running CodeThreat against your software repositories. This information can help you prioritize which security flaws to address first, based on their potential impact and likelihood of being exploited. Moreover, understanding the attack vectors can guide your team in developing more robust security measures to prevent future attacks.
Here’s an example XPath Injection vulnerability caught by CodeThreat.
And here is the possible attack scenario generated based on this weakness instance from the CodeThreat AI Assistant;
Here’s a possible mitigation technique generated against the same vulnerability located above.
We tailored the model to focus on security-specific information by fine-tuning it with a curated dataset of anti-pattern code samples and expert insights. This process allowed us to create an AI model that not only understands the nuances of programming languages but is also adept at identifying and addressing potential security vulnerabilities.
Based on our code analysis findings and the LLM’s understanding, our tool generates code patches or suggestions to fix the identified vulnerabilities. These suggestions are tailored to the specific codebase and vulnerability, ensuring that the proposed solutions are both relevant and effective.
Issue Flow Summarization
And lastly, here’s the AI generated tainted data flow explanation based on the same XPath injection vulnerability.
After analyzing the flow graph, our AI Assistant generates a human-readable summary of the issue, highlighting the key components, interactions, and potential risks involved. This summary helps users to better understand the nature of the vulnerability and the steps required to address it.
As we continue to innovate and grow, our roadmap will evolve to implement the power of AI for features such as prioritization assistance, automated issue resolution, and intelligent alert systems. Embracing the potential of LangChain, we’re shaping the future of cybersecurity today.
Stay tuned for exciting advancements in our journey!