first post of 24 yay

_posts/2024-03-04-Hey-thats-me.md

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+---
+layout: post
+title: Introducing the Offsec ML Playbook v0.1
+subtitle: Enabling Red Teams to quickly leverage TTPs on ML infrastructure
+toc: true
+#cover-img: /assets/img/solarwindsceocv.png
+thumbnail-img: assets/img/post9/logo.png
+share-img: assets/img/post9/logo.png
+tags: [ml, malware, sdlc,red team]
+---
+
+
+# Offsec ML Playbook 
+
+A [database of offensive ML TTP's](https://wiki.offsecml.com/Welcome+to+the+Offensive+ML+Playbook), broken down by supply chain attacks, offensive ML techniques and adversarial ML.  The playbook aims to simplify the decision making process of targetting ML in an organization.
+
+
+Want to poison an LLM's ground truths? [We can do that](https://wiki.offsecml.com/Adversarial+ML/LLM+Attacks/Using+Access+to+a+Model+Registry/Modify+an+LLMs+ground+truths). Want to put malware in a model and work out how to distribute it? We got the [former](https://wiki.offsecml.com/Supply+Chain+Attacks/Models/Using+Keras+Lambda+Layers) and the [latter](https://wiki.offsecml.com/Supply+Chain+Attacks/Public+Model+Registries/Using+a+Huggingface+Watering+Hole). -- Multiple ways!
+
+
+Want to understand the state-of-the-art in Offsec ML [flywheels](https://wiki.offsecml.com/Offensive+ML/Flywheels/Nemesis), [droppers](https://wiki.offsecml.com/Offensive+ML/Droppers/Sandbox+detection+using+process+ratios) and [obfuscators](https://wiki.offsecml.com/Offensive+ML/Obfuscators/Obfuscation+using+markov+chains)? 
+
+Or maybe hit an LLM via API endpoint with a repeated character sequences attack? [We got that too](https://wiki.offsecml.com/Adversarial+ML/LLM+Attacks/Using+an++API+Endpoint+or+Black+Box/Prompt+Injection/Using+Repeated+Character+Sequences). 
+
+![gif of graph in action](/assets/img/post9/graph_view.gif){: .mx-auto.d-block :} 
+
+
+## What's next?
+
+More verified TTPs, more PoCs. The supply chain section is the most fleshed out right now, and the second prioirity is the offsec TTPs. 
+
+Better graphing, right now the graphing on my local works differently to when published: 
+
+Expect to see movement in MLops TTPs and more Supply chain attacks and methods for payload distribution by December '23. 
+
+## More Data
+
+The repo'd copy has more data, namely properties like transferability (True, False, N/A) which tell a really important story; does the listed technique work on other ML models?  Soon this will be available in the graph. 
+
+
+Enjoy!