Chainguard has launched an AI-powered security harness that uses frontier models, including Anthropic’s restricted Claude Mythos 5.1, to find and fix exploitable vulnerabilities in application code that conventional scanners miss.
Developers can use Chainguard Harness without direct access to Mythos, but the company hasn’t disclosed which models handle vulnerability discovery for those customers.
The company says Harness has found serious vulnerabilities in codebases that had already undergone extensive security scanning, including software used in critical infrastructure. Details about the affected projects, the flaws themselves, and their remediation status remain undisclosed.
Announced Wednesday, Harness leads a four-product launch alongside Workspaces, Checks, and expanded Libraries protections, extending Chainguard’s reach beyond hardened container images and dependencies into agent execution environments and CI verification.
Mythos access without Glasswing
Anthropic has restricted Claude Mythos 5.1 access to organizations participating in Project Glasswing, leaving open which models Harness customers outside the program will use.
Harness will also be available through Anthropic’s Claude Marketplace, allowing teams to use existing Anthropic spending commitments rather than secure a separate budget.
The AI exploit gap
The launches come alongside The AI Exploit Gap, a Chainguard-commissioned Wakefield Research survey of 1,300 security leaders across nine markets. More than half said their organizations knowingly leave high or critical vulnerabilities unpatched at least sometimes, with the figure reaching 66% at companies with $1 billion or more in revenue, compared with 27% at companies below $250 million.
“AI can find and chain flaws in minutes, while fixing them still moves at human speed and competes with product deadlines and uptime,” Quincy Castro, Chainguard’s chief information security officer, said in a statement. “Patching faster isn’t viable for most folks, and it will consume increasing amounts of resources just to keep pace.”
“AI can find and chain flaws in minutes, while fixing them still moves at human speed and competes with product deadlines and uptime”
Isolated microVMs for agents
Each developer and coding agent gets a hardware-isolated microVM with network policies that restrict access to internal systems.
Credentials stay outside the agent’s environment, limiting what a compromised agent or malicious dependency can reach. Signed activity logs record what each agent did so teams can keep an audit trail across multiple autonomous sessions.
CI inside the agent loop
Chainguard Checks lets coding agents run CI checks directly during development and receive signed results in seconds. Agents can run tests, inspect failures, and revise code before opening a pull request, avoiding the CI queues that become harder to manage as vendors like Cognition, Microsoft, and Augment Code turn coding agents into shared team infrastructure running multiple sessions in parallel.
To avoid rebuilding environments on every run, Checks uses warm snapshots with dependencies already installed and refreshes them in the background when the lockfile changes. Each workflow step runs in a separate hardware-isolated microVM built from Chainguard OS packages, including FIPS-compliant toolchains. With Workspaces, agent sessions pause during verification and resume with structured failure logs in context.
With Workspaces, agent sessions pause during verification and resume with structured failure logs in context.
Runners never hold long-lived credentials. Instead, a host-side proxy injects short-lived credentials into outbound requests, while declarative egress policies restrict network access and can terminate a microVM if it attempts an unauthorized connection. Successful runs produce signed attestations tied to the execution environment, test results, and commit, which merge gates can verify without rerunning the suite. Checks is available now in beta.
Libraries Lock Down Late-Breaking Bugs
Chainguard Libraries is adding secure package endpoints for Go and .NET, along with CVE remediation for JavaScript, and Go. Java and Python support will also expand to cover newly disclosed vulnerabilities discovered through AI-assisted research, including flaws in dependencies that coding agents may have already pulled into a project.
Chainguard Libraries is adding secure package endpoints for Go and .NET, along with CVE remediation for JavaScript, and Go.
The changes build on Chainguard Repository, a policy-enforced endpoint for open source dependencies, and its partnership with Cursor, allowing coding agents to resolve packages through Chainguard’s catalog instead of pulling directly from public registries.
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