RTX’s BBN Technologies has open sourced its DARPA-funded Maude-HCS toolkit on GitHub, giving researchers a faster way to model and validate covert communication networks with near-test accuracy before deployment.
RTX’s BBN Technologies has released Maude-HCS, an open-source toolkit on GitHub designed to help government, academic and industry researchers model, test and validate covert communication networks collaboratively, opening a previously specialised DARPA-funded capability to the wider secure communications ecosystem.
Developed under DARPA’s PWND2 programme, the toolkit enables cyber defence teams to validate hidden communication channels before real-world deployment, reducing operational risk in contested and closely monitored digital environments.
According to RTX, Maude-HCS predicts critical performance metrics—including latency, throughput and likelihood of detection—with a 1% to 9% margin of error compared with controlled experimental tests. By automating analysis, the software reduces validation cycles from weeks of trial-and-error testing to just hours.
The toolkit runs on standard computing hardware and scales log-linearly, supporting enterprise-scale traffic simulations on a single eight-core server, making it practical for larger research and defence use cases.
“Maude-HCS provides users a rigorous yet practical way to validate performance-privacy guarantees of hidden communication designs before they ever touch the wire,” said Dr Joud Khoury, Principal Investigator, RTX BBN Technologies.
Khoury added, “This capability has the potential to fundamentally change how the national security community builds and validates covert communication channels.”
The release is particularly relevant for stealth communication scenarios where even the existence of a message must remain hidden, spanning defence, critical infrastructure and protected journalistic workflows. Supporting research has also been published as an arXiv preprint.
