AVML (Acquire Volatile Memory for Linux)

Summary

A portable volatile memory acquisition tool for Linux.

AVML is an X86_64 userland volatile memory acquisition tool written in Rust, intended to be deployed as a static binary. AVML can be used to acquire memory without knowing the target OS distribution or kernel a priori. No on-target compilation or fingerprinting is needed.

Features

• Save recorded images to external locations via Azure Blob Store or HTTP PUT
• Automatic Retry (in case of network connection issues) with exponential backoff for uploading to Azure Blob Store
• Optional page level compression using Snappy.
• Uses LiME output format (when not using compression).

Memory Sources

• /dev/crash
• /proc/kcore
• /dev/mem

If the memory source is not specified on the commandline, AVML will iterate over the memory sources to find a functional source.

Tested Distributions

• Ubuntu: 12.04, 14.04, 16.04, 18.04, 18.10, 19.04, 19.10, 20.04, 21.04, 22.04
• Centos: 6.5, 6.6, 6.7, 6.8, 6.9, 6.10, 7.0, 7.1, 7.2, 7.3, 7.4, 7.5, 7.6, 7.9
• RHEL: 6.7, 6.8, 6.9, 7.0, 7.2, 7.3, 7.4, 7.5, 7.7, 8.5
• Debian: 8, 9, 10, 11
• Oracle Linux: 6.8, 6.9, 6.10, 7.3, 7.4, 7.5, 7.6, 7.9, 8.5
• CBL-Mariner: 1.0

Getting Started

Capturing a compressed memory image

On the target host:

avml --compress output.lime.compressed

Capturing an uncompressed memory image

On the target host:

avml output.lime

Capturing a memory image & uploading to Azure Blob Store

On a secure host with az cli credentials, generate a SAS URL. EXPIRY=$(date -d '1 day' '+%Y-%m-%dT%H:%MZ') SAS_URL=$(az storage blob generate-sas --account-name ACCOUNT --container CONTAINER test.lime --full-uri --permissions c --output tsv --expiry ${EXPIRY})

On the target host, execute avml with the generated SAS token. avml --sas-url ${SAS_URL} --delete output.lime

Capturing a memory image of an Azure VM using VM Extensions

On a secure host with az cli credentials, do the following:

1. Generate a SAS URL (see above)
2. Create config.json containing the following information: { "commandToExecute": "./avml --compress --sas-url <GENERATED_SAS_URL> --delete", "fileUris": ["https://FULL.URL.TO.AVML.example.com/avml"] }
3. Execute the customScript extension with the specified config.json az vm extension set -g RESOURCE_GROUP --vm-name VM_NAME --publisher Microsoft.Azure.Extensions -n customScript --settings config.json

To upload to AWS S3 or GCP Cloud Storage

On a secure host, generate a S3 pre-signed URL or generate a GCP pre-signed URL.

On the target host, execute avml with the generated pre-signed URL. avml --put ${URL} --delete output.lime

To decompress an AVML-compressed image

avml-convert ./compressed.lime ./uncompressed.lime

To compress an uncompressed LiME image

avml-convert --source-format lime --format lime_compressed ./uncompressed.lime ./compressed.lime

Usage

``` USAGE: avml [OPTIONS]

ARGS: name of the file to write to on local system

OPTIONS: --compress compress via snappy

    --delete
        delete upon successful upload

-h, --help
        Print help information

    --sas-block-concurrency <SAS_BLOCK_CONCURRENCY>
        specify blob upload concurrency

    --sas-block-size <SAS_BLOCK_SIZE>
        specify maximum block size in MiB

    --sas-url <SAS_URL>
        upload via Azure Blob Store upon acquisition

    --source <SOURCE>
        specify input source [possible values: /dev/crash, /dev/mem, /proc/kcore]

    --url <URL>
        upload via HTTP PUT upon acquisition

-V, --version
        Print version information

```

Building on Ubuntu

# Install MUSL
sudo apt-get install musl-dev musl-tools musl

# Install Rust via rustup
curl https://sh.rustup.rs -sSf | sh -s -- -y

# Add the MUSL target for Rust
rustup target add x86_64-unknown-linux-musl

# Build
cargo build --release --target x86_64-unknown-linux-musl

# Build without upload functionality
cargo build --release --target x86_64-unknown-linux-musl --no-default-features

Testing on Azure

The testing scripts will create, use, and cleanup a number of resource groups, virtual machines, and a storage account.

1. Install az cli
2. Login to your Azure subscription using: az login
3. Build avml (see above)
4. ./eng/run.sh

Contributing

This project welcomes contributions and suggestions. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visit https://cla.microsoft.com.

When you submit a pull request, a CLA-bot will automatically determine whether you need to provide a CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions provided by the bot. You will only need to do this once across all repositories using our CLA.

This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact opencode@microsoft.com with any additional questions or comments.

Reporting Security Issues

Security issues and bugs should be reported privately, via email, to the Microsoft Security Response Center (MSRC) at secure@microsoft.com. You should receive a response within 24 hours. If for some reason you do not, please follow up via email to ensure we received your original message. Further information, including the MSRC PGP key, can be found in the Security TechCenter.