Our Company

We’re a team of passionate researchers, analysts, security practitioners, and engineers.

Zero trust code verification platform, CodeHunter

The Authorities on Behavioral Truth

We are a team of passionate researchers, exploit analysts, and engineers dedicated to uncovering the true intent of code. Our mission is to provide technical certainty against AI-driven risk through pre-execution behavioral analysis. CodeHunter delivers behavioral truth: authoritative, defensible evidence of what software is programmed to do. By deconstructing the DNA of unknown artifacts, we empower teams to neutralize material risk, satisfy compliance, and ship with absolute integrity.

Meet Our Leadership Team

Rooted in Research
CodeHunter’s technology traces to AVUD (Automated Vulnerability Detection for Compiled Smart-Grid Software), a Department of Energy-funded project at Oak Ridge National Laboratory (ORNL) under the Cybersecurity for Energy Delivery Systems (CEDS) program.

The problem: energy-delivery devices run software with long operational lives, remote-update attack surfaces, and often no available source code. Conventional testing couldn’t cover the input space, and even correct source code didn’t guarantee safe compiled behavior.

ORNL’s answer: analyze the compiled artifact itself through behavioral computation to determine what it can do before trusting it to operate inside a critical system — even when source code is unavailable, and even when the software has never been seen before.
AI-Assisted Development Raises the Stakes
The distance between human intent and what actually executes is widening fast. Most developers now use AI daily in their workflow, and coding agents increasingly generate code, pick dependencies, and open pull requests with minimal human review.

Even AI-tooling vendors advise that AI-generated code should be independently assessed rather than trusted outright.
Evolving Requirements for Software Supply Chain Security
SBOMs, SCA, code signing, SLSA provenance, and SAST were built for a world where a human wrote and could plausibly reviewmost code. Each answers a question of identity, provenance, or known risk: what’s in the package, whether a dependency is already flagged, who signed it, how and where it was built, whether the source contains recognizable insecure patterns.

Those controls remain necessary, but in an AI-first pipeline, where agents generate code and pick dependencies with limited human review, they aren’t sufficient alone. An artifact can pass every one of them and still be built to perform behavior no one intended or reviewed.
From Source-Based Trust to Behavioral Trust
Provenance can confirm how an artifact was built and that it’s authentic. CodeHunter’s architecture treats behaviors as the core signal, with verdicts, compliance findings, and risk scores generated as downstream outputs of what an artifact is capable of doing, analyzed before execution, independent of source, signing, or reputation.

As AI-generated code and automated pipelines produce artifacts with no clear author, no history, and nothing to check them against, the ability to judge an artifact by what it does, not where it came from, becomes the control that scales. It works the same way whether an enterprise developer or an AI agent produced the code.

Join the CodeHunter Team

CodeHunter is a technical-first organization focused on binary deconstruction and automated reverse engineering. We hire disciplined engineers, researchers, and strategists to build the systems that verify software intent before it executes. If you are interested in solving deep-level technical problems for high-stakes environments, explore our open roles.

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Pre-execution artifact trust analysis, CodeHunter

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