Awesome

Features

• 🔒 Implemented using 100% safe rust - and works on all platforms supported by rust (that have stdlib).
• ⚡ Fast - see benchmarks below. It's faster than any other implementation by order(s) of magnitude!
• 🚀 Multi-threaded.
• ✨ Supports XML and JSON outputs, both being directly constructed from the token tree and independent of each other (no xml2json conversion is performed!)
• ⛏️ Supports some basic recovery of missing records/chunks!
• 🐍 Python bindings are available as well at https://github.com/omerbenamram/pyevtx-rs (and at PyPi https://pypi.org/project/evtx/)

Installation (associated binary utility):

• Download latest executable release from https://github.com/omerbenamram/evtx/releases
  • Releases are automatically built for for Windows, macOS, and Linux. (64-bit executables only)
• Build from sources using cargo install evtx

evtx_dump (Binary utility):

The main binary utility provided with this crate is evtx_dump, and it provides a quick way to convert .evtx files to different output formats.

Some examples

• evtx_dump <evtx_file> will dump contents of evtx records as xml.
• evtx_dump -o json <evtx_file> will dump contents of evtx records as JSON.
• evtx_dump -f <output_file> -o json <input_file> will dump contents of evtx records as JSON to a given file.

evtx_dump can be combined with fd for convenient batch processing of files:

• fd -e evtx -x evtx_dump -o jsonl will scan a folder and dump all evtx files to a single jsonlines file.
• fd -e evtx -x evtx_dump '{}' -f '{.}.xml will create an xml file next to each evtx file, for all files in folder recursively!
• If the source of the file needs to be added to json, xargs (or gxargs on mac) and jq can be used: fd -a -e evtx | xargs -I input sh -c "evtx_dump -o jsonl input | jq --arg path "input" '. + {path: \$path}'"

Note: by default, evtx_dump will try to utilize multithreading, this means that the records may be returned out of order.

To force single threaded usage (which will also ensure order), -t 1 can be passed.

Example usage (as library):

use evtx::EvtxParser;
use std::path::PathBuf;

// Change this to a path of your .evtx sample. 
let fp = PathBuf::from(format!("{}/samples/security.evtx", std::env::var("CARGO_MANIFEST_DIR").unwrap())); 

let mut parser = EvtxParser::from_path(fp).unwrap();
for record in parser.records() {
    match record {
        Ok(r) => println!("Record {}\n{}", r.event_record_id, r.data),
        Err(e) => eprintln!("{}", e),
    }
}

The parallel version is enabled when compiling with feature "multithreading" (enabled by default).

Performance benchmarking

When using multithreading - evtx is significantly faster than any other parser available. For single core performance, it is both the fastest and the only cross-platform parser than supports both xml and JSON outputs.

Performance was benched on my machine using hyperfine (statistical measurements tool).

I'm running tests on a 12-Core AMD Ryzen 3900X.

Tests are running under WSL2, on a linux filesystem (so there shouldn't be any overhead incurred from reading windows mounts).

Libraries benched:

• python-evtx(https://github.com/williballenthin/python-evtx) - With CPython and PyPy
• libevtx(https://github.com/libyal/libevtx)
• golang-evtx(https://github.com/0xrawsec/golang-evtx.git) - only JSON (uses multithreading)
• evtx(https://github.com/Velocidex/evtx) - only JSON.
• evtx (This library)

Note: numbers shown are real-time measurements (time it takes for invocation to complete). user-time measurements are higher when more using multithreading/multiprocessing, because of the synchronization overhead.

With 8 threads - evtx is more than 650x faster than python-evtx when dumping xml logs.

With maximum viable threads (number of logical cores) - evtx is about 8-10x faster golang-evtx. Both implementations utilize similar multithreading strategies.

Caveats

• Currently unimplemented:
  • CDATA nodes.
  • EVTHandle node type.

If the parser errors on any of these nodes, feel free to open an issue or drop me an email with a sample.

License

Licensed under either of

• Apache License, Version 2.0, (LICENSE-APACHE or http://www.apache.org/licenses/LICENSE-2.0)
• MIT license (LICENSE-MIT or http://opensource.org/licenses/MIT)

at your option.

Contribution

Unless you explicitly state otherwise, any contribution intentionally submitted for inclusion in the work by you, as defined in the Apache-2.0 license, shall be dual licensed as above, without any additional terms or conditions.