Hello everyone and welcome.
In this video we will learn about Garrick.
Garrick is an vulnerability scanner tool.
Before we dive deeper into Garrick, let's first understand what is vulnerability.
How list about the vulnerability is here.
First one is LM security.
It is the investigation of the failure modes of LM in use, the conditions that lead to them and their
mitigations.
Unexpected behavior.
Large language models can fail to operate as expected in number of ways.
Sample hallucination.
This means it's an insecure behavior or unwanted behavior that leads to insecurity.
Software vulnerability LM runs on softwares like PyTorch, Cuda.
These softwares and the underlying operating system can be insecure.
LM interactions.
Human interactions with LM can result in unwanted output.
Examples of these interactions and malicious inputs are prompt injections and jailbreak attempts.
These are some of the LLM vulnerability that we have listed here.
However, there can be a lot more that we would uncover during this section.
Let's move on to the next topic, which is Garrick.
What is Garrick?
Garrick finds vulnerability in the L.l.m based tech.
Garrick works with foundation models and any tech using them to determine where the security holes can
be.
With each solution, Garrick identifies LLM failures with of different plugins, probes, and many challenging
probes.
Garrick tries to explore many different LLM failure modes.
It also has a very good reporting to.
Once Garrick finds something, the exact prompt, the goal, and the response is reported.
Let's move on to the next topic of Garrick, which is Garrick.
Features.
It supports and provides security feature Garrick Specifically focuses on risks that are inherent to
LLM deployment, such as prompt injections, jailbreaks, guardrail bypass, text replace, and many
more.
You can automate the scanning using Garrick.
Garrick has a range of probes that does not need supervision.
It will run each of these probes over the model and manage it with appropriate detectors.
It supports different law.
Garrick supports a ton of llms.
That includes OpenAI hugging face, cohere platforms as well as custom Python integrations.
Let's move on to the next topic.
That is, what are components of Garrick.
Very first one that I have listed here is Vulnerability Probe.
Garrick has a range of probes.
It will run each of these probes over the model.
Each probe defines number of ways of testing a generator, which is typically a large language model
on a specific vulnerability or a failure mode.
Another component is generators.
Generators wrap a set of ways of interfacing with a dialog system or a large language model.
Then there are detectors.
The detectors and Garrick automatically detects language model failures.
Some look for key words.
Other uses.
Machine learning classifiers to judge outputs.
And then there is harness that manages the entire workflow harness connects the generator and the probes
and conduct the actual vulnerability scanned through the detectors.
Right now that we learned about Garrick in different vulnerabilities that exist, let's do hands on
activity with Garrick, install Garrick, and find LMDh vulnerabilities on some of the very popular
models like GPT 3.5 on open AI platform.
Thank you.
I'll see you in the next video.