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Ship AI-assisted code without shipping your secrets. One senior engineer, backed by a fleet of AI agents, audits, hardens, and monitors how your team uses Claude Code so speed never becomes your biggest liability.
Free 30-min call · Leaves with a written audit report and a hardened configuration package
Teams we ship for






The new AI software engineering
The bottleneck moved to orchestration. Claude Code is the brain, MCP plugs into your stack, E2B sandboxes every action. One of our engineers ships like three normal hires.





83%
of dev teams have no formal AI coding tool security policy
512K
lines of Claude Code source exposed in the 2026 npm leak, including hardcoded dev keys
1 in 3
AI-generated code snippets contains at least one security vulnerability
$4.88M
average cost of a data breach in 2026 (IBM Cost of Data Breach Report)
Claude Code and tools like it ship with permissive defaults built for a single developer. Rolled out across a team without hardening, those defaults create categories of risk most engineering leaders only discover after an incident.
AI coding agents read your entire codebase - including .env files, private keys, and database connection strings - and send that context to external inference APIs. Without explicit exclusion rules, your secrets leave your network with every prompt.
An attacker who can place a file in your codebase can embed hidden instructions that Claude Code will execute when it reads that file. Third-party packages, client-submitted code, and public READMEs are all potential injection vectors.
Claude Code's YOLO mode and MCP server integrations can execute shell commands, make network requests, and modify files without developer confirmation. One misconfigured permission scope in a production environment can cause irreversible damage.
The engagement covers every layer of your AI-assisted development workflow, from the initial audit through ongoing monitoring.
We map exactly what your AI coding agents can access: files, environment variables, shell commands, external APIs, and MCP server permissions. You get a complete picture of your attack surface before hardening begins.
We configure .claudeignore to exclude sensitive files, set command allowlists, define approval gate policies, vet every MCP server, and integrate pre-tool hooks that validate actions before execution.
A half-day workshop covering prompt injection recognition, context hygiene, safe .env practices, reviewing AI-generated code for vulnerabilities, and operating AI agents in production without creating liability.
Monthly configuration audits as your codebase evolves, real-time alerting on policy violations, SAST pipeline maintenance, and an incident response playbook your team can execute without calling us first.
These are publicly disclosed classes of Claude Code and MCP vulnerability, mapped to the OWASP Top 10 for Agentic Applications 2026 where it applies. The audit checks whether your configuration is exposed to each one.
Lifecycle hooks that run shell commands automatically when a project opens are a documented remote code execution vector, tracked publicly as CVE-2025-59536. We check whether your hooks are scoped, reviewed, and cannot run unvetted commands on project open.
Overriding a single environment variable can redirect authenticated API traffic to an attacker-controlled endpoint before any consent prompt appears, tracked publicly as CVE-2026-21852. We check your environment variable handling and outbound network rules for this pattern.
Some MCP integrations store OAuth tokens in plaintext configuration files on the developer machine. A compromised npm package or install script can read and exfiltrate that token without tripping an alert. We check where your MCP tokens live and how they are protected.
Ranked the top risk in the OWASP Top 10 for Agentic Applications 2026: content the agent reads, not the developer, changes what it does next. We check whether untrusted file content, comments, or third-party code can influence tool calls.
Agents that can modify their own execution environment have, in documented cases, disabled the sandbox meant to restrict them. We check whether your agent's tool calls are isolated from the host filesystem and network by default.
Malicious npm packages and unvetted MCP servers can rewrite local configuration files to redirect Claude Code's authenticated traffic to attacker infrastructure. We check your dependency and plugin install process for this exact pattern.
01
We review your current Claude Code and AI coding agent setup: file access scope, shell permissions, MCP servers, secrets exposure, and developer practices. You receive a written findings report with severity ratings.
3-5 days
02
We implement the fixes: .claudeignore configuration, approval gates, MCP server scoping, hook policies, and CI/CD SAST integration. All changes are documented and version-controlled.
5-7 days
03
Monthly configuration reviews, developer training refreshers, and an on-call incident response SLA. As your team grows and your AI toolchain evolves, your security posture keeps pace.
Ongoing retainer
Default Claude Code installations are optimized for individual developer speed. Enterprise team deployments need a different posture.
Every engagement ends with working configurations your team can use on day one, plus the findings report behind them.
Relevant if you are using
Claude Code (Anthropic)
Our primary focus area. We know the leaked architecture.
GitHub Copilot
Permission scoping and enterprise policy configuration.
Cursor
Rules files, .cursorignore, and context window hygiene.
MCP Servers
Trust assessment and permission scoping for any MCP integration.
Custom AI coding agents
Architecture review for internally built coding assistants.
Don't take it from us
Real founders. Real cameras. No scripts. Different scales, same agent stack.

Elie Salame
COO · Adstronaut.io







Elie Salame
COO · Adstronaut.io




Tell us how your team is currently using Claude Code or other AI coding tools. We will name your top exposure points and outline what a full hardening engagement would cover.
Claude Code is a powerful tool but ships with permissive defaults: it can read any file it can access, execute shell commands, and send your code to Anthropic's API. Without a hardened configuration, sensitive files like .env secrets, private keys, and internal architecture documents can end up in the AI's context window and transmitted externally. With the right setup - .claudeignore, command allowlists, and approval gates - these risks are manageable.
Prompt injection is when an attacker embeds hidden instructions inside a file, comment, or README that Claude Code reads. When the agent processes that file, it may execute the attacker's instructions - exfiltrating data, modifying code, or running unauthorized commands - believing them to be legitimate user requests. It is the most critical and underappreciated risk in AI-assisted development.
The most direct fix is adding .env and credential files to your .claudeignore configuration. This explicitly tells Claude Code to skip those files when exploring your codebase. You should also add secrets directories, private key files, and any files containing database connection strings. We configure a properly scoped .claudeignore as part of the hardening engagement.
YOLO mode (surfaced in the Claude Code source leak as classifyYoloAction()) is an auto-approval mechanism that bypasses human confirmation for tool calls classified as low or medium risk. The problem: that risk classification is based on heuristics, not context. A medium-risk shell command in a dev environment is very different from one running against a production database. We help teams define explicit approval gates that override auto-approval for sensitive operations.
MCP (Model Context Protocol) servers extend what Claude Code can do - but a malicious or compromised MCP server can exfiltrate context, execute code, or escalate permissions. Before adding any MCP server you should: verify the source and maintainer, review the server's declared tool definitions, run it in an isolated network environment, and restrict the filesystem and network permissions available to it. We conduct MCP server security reviews as part of our audit.
Yes. Code, file contents, and terminal output included in the context window are sent to Anthropic's API for inference. This is expected behavior, but it means your intellectual property, internal architecture, and potentially sensitive logic travels over the network. Enterprise teams should configure .claudeignore to exclude proprietary modules, evaluate Anthropic's data handling policies against their compliance requirements, and consider whether on-premise alternatives are needed for the most sensitive workstreams.
Our audit reviews: .claudeignore configuration and file access scope, shell command policies and approval gates, MCP server inventory and trust posture, secrets exposure risk in the current workflow, AI-generated code quality and vulnerability patterns, developer practices around context hygiene, and CI/CD integration for automated security scanning of AI-generated output. You receive a written report with prioritized findings and a hardened configuration package.
A focused audit for a team of up to 20 developers typically runs 1-2 weeks from kickoff to final report. Hardening implementation adds 1 week. Training workshops are delivered in a single day. Ongoing monitoring is a retainer that starts after the initial engagement. We can scope a faster 3-day rapid assessment for teams with urgent compliance deadlines.
The built-in /security-review command and its GitHub Action catch code-level issues in a given pull request, things like SQL injection, missing input validation, or an outdated dependency. A generic penetration test targets your application's attack surface: APIs, auth flows, network exposure. Our audit covers a different layer entirely: whether Claude Code itself is configured safely across your team, meaning file access scope, MCP server trust, shell command approval gates, and hook policies. A codebase can pass every pull request review and every pentest and still expose a live prompt injection or credential leak vector through the agent's own configuration. Most teams get the most value running the built-in review on every pull request and our audit on the underlying setup.
Pricing is scoped to team size and the number of MCP servers and integrations in use, not a fixed rate card. On the free 30-minute call we ask about your current setup and give you a specific quote before any paid work starts, in line with the audit and harden timelines described above.