From d9722ad11ccf81beb2a1dacec53a894998b6e03e Mon Sep 17 00:00:00 2001 From: timothytrippel Date: Fri, 5 Feb 2021 13:04:52 -0500 Subject: [PATCH] Updated README for release. Signed-off-by: timothytrippel --- .gitignore | 4 +- README.md | 210 +++++++++++++----- .../fuzzing_hardware_like_software.png | Bin 147167 -> 0 bytes docs/figures/hw_fuzzing_pipeline.png | Bin 102487 -> 0 bytes docs/figures/hwf_process.png | Bin 0 -> 72638 bytes 5 files changed, 151 insertions(+), 63 deletions(-) delete mode 100644 docs/figures/fuzzing_hardware_like_software.png delete mode 100644 docs/figures/hw_fuzzing_pipeline.png create mode 100644 docs/figures/hwf_process.png diff --git a/.gitignore b/.gitignore index ffb107d..1dd427f 100644 --- a/.gitignore +++ b/.gitignore @@ -55,9 +55,7 @@ hw/rv_timer/seeds *.png *.svg *.jpg -!docs/figures/fuzzing_hardware_like_software.png -!docs/figures/hw_fuzzing_pipeline.png -!docs/figures/lock_state_machine.png +!docs/figures/hwf_process.png # Environment .envrc diff --git a/README.md b/README.md index d097980..4a05213 100644 --- a/README.md +++ b/README.md @@ -1,63 +1,153 @@ # Fuzzing Hardware Like Software -**Author**: Timothy Trippel
-**Email**: ttrippel@opentitan.org
-**Personal Website**: https://timothytrippel.com
- -## Motivation - -Hardware flaws are both *permanent* and *potent*. Unlike software, hardware -cannot be patched once it is fabricated. Making matters worse, hardware is -foundational: hardware flaws can completely undermine even formally verified -software that sits above. Due to the economic and reputational incentives to -design and fabricate flawless hardware, design verification research has been an -active arena. Unfortunately the fruits of this labor mainly consist of -strategies concentrated at two extremes: 1) broad coverage through constrained -random verification, or 2) (bounded) formal verification. Moreover, both of -these techniques require extensive implementation knowledge of the Design Under -Test (DUT) to be effective. - -## Approach - -To close this gap, we propose *fuzzing hardware like software* to -automate test vector generation in an intelligent manner---that boosts -coverage---*without* requiring expensive Design Verification (DV) engineers and -tools. Specifically, we demonstrate how to translate RTL hardware to a software +**Maintainer**: Timothy Trippel +
+**Personal Website**: https://timothytrippel.com +
+ +
+

+ +
+ Figure 1: Fuzzing Hardware Like Software. +

+
+ +Due to the economic and reputational incentives to design and fabricate flawless +hardware, design verification research has been an active arena. Unfortunately +the fruits of this labor mainly consist of strategies concentrated at two +extremes: 1) broad coverage through constrained random verification, or 2) +(bounded) formal verification. Moreover, both of these techniques require +extensive implementation knowledge of the Design Under Test (DUT) to be +effective. + +To close this gap, we propose _fuzzing hardware like software_ to automate test +vector generation in an intelligent manner---that boosts coverage---_without_ +requiring expensive Design Verification (DV) engineers and tools. A technical +paper describing this project can be found +[here](https://arxiv.org/pdf/2102.02308.pdf). + +In this project, we demonstrate how to translate RTL hardware to a software model, and leverage coverage-guided software fuzzers---like -[AFL](https://github.com/google/AFL)---to automate -test vector generation for hardware verification (Figure. 1). While we do not -suggest this as a replacement to traditional DV methods for sign-off, we argue -this technique serves a low-cost preventative mechanism to identify complex -hardware vulnerabilities *before* they are exploited for malice. - -![Fuzzing HW Like SW](docs/figures/fuzzing_hardware_like_software.png -"Figure 1: Fuzzing Hardware Like Software.") - -## HW Fuzzing Pipeline - -Thus far, we have designed and built a *Hardware Fuzzing Pipeline* -leveraging an open-source *RTL* simulator -[Verilator](https://www.veripool.org/wiki/verilator), coverage-guided -greybox fuzzer [AFL](https://github.com/google/AFL), and -[GCP](https://cloud.google.com/). Our pipeline is modeled after Google's -[OSS-Fuzz](https://github.com/google/oss-fuzz) open-source software fuzzing -architecture and is illustrated in Figure 2. - -![HW Fuzzing Pipeline](docs/figures/hw_fuzzing_pipeline.png -"Figure 2: Hardware Fuzzing Pipeline.") - -## Results - -Using our pipeline, we demonstrate the -power of coverage-guided test vector generation by comparing the verification -runtimes observed to achieve full FSM coverage of several sequential state -machines of various complexities. With -AFL we observe over two orders of -magnitude reduction in verification runtime to achieve full FSM coverage across -the various RTL designs we study, when compared to traditional -constrained-random verification. - -## Ongoing Work - -Currently, we are using this pipeline to apply these techniques to the -[OpenTitan](https://opentitan.org/) root of trust ecosystem. +[AFL](https://github.com/google/AFL)---to automate test vector generation for +hardware verification (Figure 1). Specifically we demonstrate this technique on +hardware from the [OpenTitan](https://opentitan.org/) IP ecosystem. While we do +not suggest this as a replacement to traditional DV methods for sign-off, we +argue this technique serves a low-cost preventative mechanism to identify +complex hardware vulnerabilities _before_ they are exploited for malice. + +To understand the layout of this project and how to get started, read below. + +## Directory Structure + +### docs + +This directory currently only contains a document that describes how to +contribute to this project and some figures that are displayed in this README. +However, it will be the location of any future documentation that is added. + +### experiment_scripts + +This directory contains some python scripts to automate launching large batches +of fuzzing experiments on GCP VMs. Additionally there are some scripts that can +be used to plot fuzzing data using Seaborn/Matplotlib. + +### hw + +This directory contains several supporting files to fuzz various various +OpenTitan hardware IP blocks. Currently, the following OpenTitan IP blocks are +supported: AES, HMAC, KMAC, and the RV Timer. Additionally, a subdirectory +called _ot_template_ can be copied, and the files within edited, to bring-up +another OpenTitan IP block for fuzzing. Lastly, a custom digital _lock_ hardware +block is included to stress test our fuzzing infrastructure. This block is +actually autogenerated by a tool written in Rust (using the +[kaze](https://docs.rs/kaze/0.1.18/kaze/) crate). For more details checkout the +technical paper linked above. + +### infra + +This directory contains several subdirectories that contain Dockerfiles and +Shell/Python scripts that makeup a containerized infrastructure for fuzzing +hardware designs at scale. This infrastructure is modeled after Google's +[OSS-Fuzz](https://github.com/google/oss-fuzz) project. This infrastructure can +be used to jumpstart fuzzing hardware locally or on GCP (provided you have an +active account). See _Getting Started_ below for how to build this +infrastructure. Read the technical paper above for exactly what is included in +the fuzzing infrastructure. + +### tests + +This directory contains some HJSON fuzzing configuration files along with a +Python script to test the overall fuzzing infrastructure is successfully +simulating OpenTitan hardware. + +## Getting Started + +### I. Clone/Fork Repository + +1. `git clone https://github.com/googleinterns/hw-fuzzing.git` +2. `cd hw-fuzzing` + +### II. Set Environment Variables + +To use any of the fuzzing infrastructure, which consists of: 1) building several +Docker images to isolate fuzzing each target hardware IP block, and 2) using two +(included) Python packages, some environment variables must be set. You can set +them system wide, however, I recommend using the +[direnv](https://github.com/direnv/direnv) tool to set/unset them when you +enter/leave your _hw-fuzzing_ project directory. + +##### Using direnv (assuming it is installed): + +1. Create a `.envrc` file in the hw-fuzzing root directory with the following: + +``` +export HW_FUZZING=$(pwd) +export PYTHONPATH="./:../:$(pwd)/infra/hwfp:$(pwd)/infra/base-sim/hwfutils" +``` + +2. `direnv allow` + +##### Setting system-wide: + +Add the above two lines to your _.bashrc_ or _.zshrc_ (depending on the shell +you use), except replace the _\$(pwd)_ within each statement with the global +path to your _hw-fuzzing_ directory. + +### III. Install Python Dependencies + +The automated Hardware Fuzzing Pipeline (HWFP) Python tooling is tested using +Python 3.8, and requires the following dependencies. + +1. Create Python virtual environment (not required, but recommended). +2. Activate virtual environment (if you made one). +3. `pip install -r infra/hwfp/requirements.txt` +4. `pip install -r infra/base-sim/hwfutils/requirements.txt` + +### IV. [Install Docker](https://docs.docker.com/get-docker/) + +### V. Build Docker Infrastructure + +1. `make build-infra` +2. Grab a cup of coffee ☕... this will take a while since we are building LLVM + here. + +### VI. Fuzz a Design + +##### a. Fuzzing Locally + +1. `make fuzz-` where `` is [aes, hmac, kmac, rv_timer] to launch + interactive container. +2. `run` to begin RTL translation, intrustmentation, and fuzzing (if in manual + mode, which is default, otherwise this step can be skipped). +2. Press `Ctrl+c` to terminate fuzzing and begin final coverage tracing. + +##### b. Fuzzing on GCP + +1. Create GCP account. +2. Create a GCS bucket to store all fuzzing data. +3. Edit the _gcp_config.hjson_ file with your GCP project details. +4. Edit the value for the _run_on_gcp_ key in the _cpp_afl.hjson_ + configuration file for the core you want to fuzz in _hw/``/_. +5. 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