Boost Security Announces the Launch of Developer Endpoint Security
5 min read
AI coding agents have fundamentally altered the topology of the software supply chain threat. The developer machine — historically a managed endpoint with a known toolchain — has become a rapidly expanding attack surface, accumulating credentials across dotfiles and environment variables, installing plugins and MCP servers recommended by AI agents, and producing volumes of AI-generated code that organisations cannot review against secure coding standards at the speed at which it arrives. Into this environment, Boost Security has launched Boost Security Developer Endpoint Security — a new platform that moves protection to where code is created, securing developer machines, governing coding agents, and ensuring that AI-generated code is validated before it ever reaches the repository.
The Problem: Security Has Been Looking the Wrong Way
Enterprise application security has historically been oriented toward the repository and beyond — scanning code after it is written, analysing dependencies after they are declared, reviewing containers after they are built. That model was designed for a development process in which humans wrote code at human speed, and the gap between code creation and code review was measured in hours or days. AI coding agents have collapsed that model. A coding agent operating on a developer's machine can write, test, and stage hundreds of lines of production-bound code in the time a human developer would spend drafting a single function — and it will do so drawing on packages, MCP servers, IDE extensions, and plugin configurations that security teams have never seen, audited, or approved.
The attack surface this creates is not theoretical. Credentials accumulate silently across configuration files, environment variables, and local machine directories as developers and agents interact with multiple services. Packages recommended by AI agents may be malicious, end-of-life, or contain exploitable vulnerabilities that a standard dependency scanner would catch — but only after the code has been committed. MCP servers and IDE extensions loaded at the agent's request may have no vetting history whatsoever. And outbound prompts sent to external LLMs may carry API keys, credentials, or sensitive data that developers never intended to expose. Every one of these vectors exists upstream of the repository — in the developer endpoint itself — and traditional security tooling has no visibility into any of them.
"AI coding agents are fundamentally changing how software gets built, but security has largely remained focused on scanning code after the fact. Developer Endpoint Security moves protection upstream. It secures the developer machine, governs the coding agent, and ensures safer code is generated from the start."
— Zaid Al Hamami, CEO and Founder, Boost Security
Eight Capabilities: From Prompt to Commit
The platform secures the full AI development workflow — from the moment a prompt is sent to a coding agent to the moment code is committed to the repository. Eight core capability areas address the distinct security risks introduced at each stage of that workflow:
- Developer Endpoint Visibility — Continuously discovers coding agents, MCP servers, AI models, IDE extensions, browser extensions, packages, and other development artefacts across the developer fleet, giving security teams a real-time inventory of every tool that developers and agents are using — including tools that were never provisioned or approved through official channels.
- Developer Endpoint Safety — Identifies exposed credentials across dotfiles, configuration directories, and environment variables, while flagging machine configurations that increase the blast radius of a compromise — the silent accumulation of secrets that most developers are unaware has occurred.
- Coding Agent Safety — Ensures coding agents operate only with approved MCP servers, plugins, and skills — preventing unvetted connections and configuration drift from organisational security policies before the agent takes any action based on those unapproved integrations.
- Secure Agentic Code Generation — Embeds guardrails directly into the coding agent workflow so that generated code follows organisational secure coding guidelines, uses approved libraries, and is analysed and remediated before being committed — rather than requiring a separate downstream review cycle.
- Supply Chain Security — Evaluates packages, extensions, MCP servers, and other components for malware, typosquatting, exploitable vulnerabilities, end-of-life dependencies, and other indicators of compromise — applied at the point of installation rather than the point of deployment.
- Data Leakage Prevention — Scans outbound prompts before they reach external LLMs to detect and mask credentials, API keys, and sensitive data — addressing the prompt-as-exfiltration-vector risk that has emerged as AI-assisted development has become mainstream.
- Intelligent Security Remediation — Combines organisational context with vulnerability analysis to deliver AI-assisted fixes aligned with internal architecture patterns and compliance requirements — not generic patches, but fixes that understand the codebase they are being applied to.
- Centralised Policy and Enforcement — Allows security teams to define secure coding standards, allowlists, and denylists that apply consistently across both human-written and AI-generated code — ensuring that the organisation's security posture does not bifurcate along the human/AI code boundary.
Customer Voice: Enforcing Guardrails Across a Diversely Grown Engineering Organisation
HUB International — one of the world's largest insurance brokerages, whose engineering organisation has grown both organically and through a long programme of M&A activity — is among Boost Security's existing customers using the platform to enforce consistent security guardrails across a heterogeneous development environment.
"HUB's engineering organization is large and diversely grown, both organically and through M&A. We wanted one set of guardrails that applies to every change across our SDLC, and we wanted to ensure that the code we build or acquire, as well as the entire software supply chain infrastructure, is secured at every stage. Boost Security helps us get there, with controls natively built into engineering workflows through source control and CI/CD pipelines in a single comprehensive platform."
— Jeremy Embalabala, CISO, HUB International
HUB International's use case reflects a dynamic that applies across many large enterprise engineering organisations: when development capability has been assembled through acquisition rather than grown from a single codebase and toolchain, achieving consistent security enforcement across diverse SDLC environments is structurally difficult. Different acquired engineering teams will have different toolchains, different dependency management practices, and different relationships with AI coding tools — and the surface area across which security policy must be consistently enforced is far larger than a single-origin engineering org. A platform that embeds guardrails natively into source control and CI/CD pipelines — rather than requiring each acquired team to adopt a new standalone security tool — is architecturally the right answer to this specific problem.
The Broader Shift: Governance at the Agentic Layer
Developer Endpoint Security represents the next logical extension of Boost Security's platform beyond its established CI/CD and source control security capabilities — and one that reflects a broader shift in where the most consequential security decisions in software development are now being made. As AI coding agents become the primary authors of production code in many engineering organisations, the governance challenge migrates upstream: from reviewing what humans committed to governing what agents were permitted to do in the first place.
The supply chain security implications of this shift are particularly acute. The SolarWinds and XZ Utils incidents demonstrated that software supply chain compromise — attacking the build toolchain rather than the application itself — can propagate malicious code to thousands of downstream organisations before any individual organisation detects the breach. In an environment where AI agents are autonomously installing packages, loading plugins, and connecting to external services, the attack surface for supply chain compromise at the developer machine level is materially larger than it was when every toolchain decision required a human to make it. Controlling what agents are permitted to load, connect to, and act upon — before they generate a single line of code — is where supply chain security must now operate. Explore the latest Artificial Intelligence News for more updates on AI, cybersecurity, and enterprise technology.
Key Takeaways
- Boost Security has launched Developer Endpoint Security — a new platform that moves protection upstream to the developer machine and coding agent, securing the full AI development workflow from prompt to commit before code reaches the repository.
- Eight core capabilities address distinct risk vectors: real-time developer fleet inventory, credential and configuration exposure detection, coding agent governance (MCP servers, plugins, skills), secure agentic code generation, supply chain security, outbound prompt data leakage prevention, AI-assisted remediation, and centralised policy enforcement across human and AI-generated code.
- The platform addresses a structural visibility gap: security teams currently have no insight into what coding agents are installing, connecting to, or generating locally — all of which happens before any repository-based scanning tool sees the code.
- HUB International CISO Jeremy Embalabala validated the platform's enterprise value for organisations with diversely-grown, M&A-assembled engineering stacks — where consistent SDLC guardrails across heterogeneous development environments are a foundational security requirement.
- As AI agents become primary code authors, the most consequential software supply chain governance decisions migrate to the agentic layer — what agents are permitted to load, connect to, and act upon — making upstream developer endpoint control the next critical frontier of application security.