How it works
Facts about what was built and what runs.
Crash Override is AppSec for the AI era. We work in three places: where code is written, where it's built and where it runs. In the developer workspace, engineers and their AI agents write code; in the build, the build sensor records what every artifact is, where it came from and what's inside it; and in production, that record reports back from what's running. It all connects in one data plane: deterministic facts about what was built, what's inside it and what's running. The data plane connects the slices every other tool sees on its own, and feeds the tools, teams and agents that depend on them.
DATA PLANE
facts, not guesses
- Agent
Workspace sensor
- Repo
- Build
Build sensor
- Registry
- Production
- Hold the bad build
- Answer “Are we exposed?”
- Hand over the evidence
Three places
We work in three places.
Other tools see one slice: the code, the build or production. We see all three, and that is unique to us. The workspace sensor sees how code is written, the build sensor records every artifact as it's built, and that record reports back from production.
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Developer workspace
The workspace sensor sees how code is written
It sees how engineers and their AI agents write code, so the facts start before the build. It's optional.
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Build
The build sensor records every artifact
As each artifact is built, the build sensor adds a small, signed record to it: what it is, where it came from and what's inside.
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Production
The record reports back from what's running
The record follows the artifact into production and reports back, so whatever is running traces back to its build and its code.
DATA PLANE
The data plane draws deterministic connections between what was written, what was built and what's running. Query them through APIs, webhooks and MCP, and every answer traces back to its source.
Workspace sensor
In the developer workspace
The workspace sensor watches how code is written, so the facts start before the build. It deploys zero-touch through your existing MDM, and it's optional: the build sensor works without it.
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Sees how code is written
It observes the developer workspace, where engineers and their AI agents write code, so the record starts before the build.
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Zero-touch deployment
It deploys through the MDM you already run, so there is nothing for engineers to install or configure.
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Scoped to each developer's work
Each workspace sensor sees the repositories its developer works in. For coverage of what ships, add the build sensor to the pipelines that build for production.
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Context for the security team
How code was written joins what was built and what runs in the same data plane, so security sees the path from prompt to production.
Your IP stays where it is
The workspace sensor observes how code is written in the repositories its developer works in. Your code and your intellectual property stay where they are. We don't take your code.
Available for macOS today. Windows and Linux are expected the week of October 19.
Build sensor
At build time
At build time the build sensor adds a small, cryptographically signed record to the artifact, covering the commit, branch, dependencies, build environment and scan results. The record travels inside the artifact, so the context goes wherever the artifact goes.
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A small change to each pipeline
Add the build sensor to a pipeline as a GitHub Action or a GitLab component. There is no platform migration.
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Designed to fail open
A build sensor problem never breaks your build, and build overhead is minimal.
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Nothing changes in what runs
The build sensor doesn't inject code into your application. The record rides with the artifact, with no sidecars and no background processes in production.
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Production reports back
Deployed artifacts report back from production, so anything running traces back to its build and its code, and you know whether something ever ran.
Works with your build systems
If your CI/CD system builds it, the build sensor can record it.
CI/CD
- GitHub Actions
- GitLab CI
- Jenkins
- Other CI/CD systems
Artifacts
- Container images
- Compiled binaries
- Language packages
- Serverless packages
Capabilities
Select a component to see what it does.
Sense
Workspace sensor
Observes the developer workspace, where engineers and their AI agents write code. Optional, and deployed zero-touch through your existing MDM. Your code stays where it is.
Signed artifact records
The build sensor gives every artifact a signed record of what it is and where it came from, and the record follows it into production.
Artifacts in production
Deployed artifacts report back from production, so you know what is actually running, and whether something ever ran.
Connect
The data plane
Draws deterministic connections between what was written, what was built and what's running, so you can query any of them and trace every answer back to its source.
Feed
APIs
Ask the data plane what's in any artifact, where it came from and where it runs, and get a current answer.
Webhooks
Send facts from the data plane to the tools and teams that act on them.
MCP
Connect your agents over MCP, and Claude gets facts instead of guesses.
Common questions
Adding the build sensor to a pipeline is a GitLab component or a GitHub Action, so each change is small. We still recommend rolling it out incrementally: changing pipelines across an organization is an organizational change, not a config push. Start with the pipelines that ship to production, show value, then expand.
Great. Scanners guess; we know. Snyk tells you a vulnerable package is in a repository. We tell you whether it was built into an artifact, where it's running, and whether it ever ran, and we can stop it at the build.
Stitching data across silos with an LLM is nondeterministic and brittle. We're independent, deterministic, structured data from inside your build and production. Connect us over MCP and Claude gets facts instead of guesses.
The build sensor adds a small, signed record to every artifact as it's built, saying what it is, where it came from and what's inside. Think of it like an AirTag on luggage: it travels with the artifact into production and reports where it is.
Not another scanner. The layer underneath the tools you already run, feeding them facts.
An engineer replies. The first call is technical.