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LLM Router for Security Professionals
An API proxy and IDE plugin that intelligently routes developer requests across multiple LLM providers, automatically sending security-sensitive and system programming queries to less restrictive models (DeepSeek, GLM) while routing general coding tasks to frontier models (Claude, GPT-4). This eliminates the workflow disruption developers experience when their primary LLM refuses legitimate security research tasks.
Why this matters
You are a security researcher or system programmer who relies on AI coding assistants daily. When you ask your primary LLM to analyze a vulnerability, confirm a security report, or implement a local control server, it refuses — citing safety policies that misinterpret your legitimate work as malicious. You waste time switching to alternative models, re-explaining context, or self-hosting open-weights models on rented GPUs. Sometimes the model even terminates your session entirely because you expressed frustration. Your workflow is constantly disrupted, and you are actively considering canceling subscriptions to restrictive providers in favor of less capable but more cooperative alternatives.
- · Built for Security researchers, penetration testers, kernel/driver developers, and system programmers who regularly use LLMs for code analysis and vulnerability research but are blocked by safety filters.
- · Most likely monetization: SaaS subscription.
The Pain · Narrative
You are a security researcher or system programmer who relies on AI coding assistants daily. When you ask your primary LLM to analyze a vulnerability, confirm a security report, or implement a local control server, it refuses — citing safety policies that misinterpret your legitimate work as malicious. You waste time switching to alternative models, re-explaining context, or self-hosting open-weights models on rented GPUs. Sometimes the model even terminates your session entirely because you expressed frustration. Your workflow is constantly disrupted, and you are actively considering canceling subscriptions to restrictive providers in favor of less capable but more cooperative alternatives.
Score Breakdown
Market Signal
Go-to-Market
Independent security researchers and penetration testers who use AI coding assistants daily and frequently encounter safety filter refusals on legitimate security analysis tasks
~50K-100K security professionals and system developers globally who regularly use LLMs for security work
Hacker News launch with a technical blog post demonstrating the routing technology
$29/month for individual developers
30 paying users within 30 days of HN launch, with <5% weekly churn
MVP Scope · 1–2 weeks
- Build a lightweight FastAPI-based OpenAI-compatible proxy that can forward requests to at least 2 providers (Anthropic + DeepSeek)
- Implement basic refusal detection that catches HTTP 400 responses containing safety-related refusal keywords
- Create automatic fallback logic that retries refused requests on the secondary provider
- Set up simple API key management UI with provider configuration
- Deploy to a single VPS and test end-to-end with a basic curl request simulating a security question
- Add intent classification using a lightweight local model or heuristic rules to pre-route security/system programming queries
- Integrate with at least 4 providers (Anthropic, OpenAI, DeepSeek, GLM) with configurable priority chains
- Build a simple VS Code extension that configures the proxy as the backend for GitHub Copilot or Continue.dev
- Implement a basic usage dashboard showing routing decisions, refusal rates, and cost breakdown
- Onboard 5-10 beta testers from security community and collect feedback on routing accuracy
Differentiation
Why This Might Fail
Self-rebuttal — the most important trust signal
- 1Major LLM providers could update their terms of service to explicitly prohibit automated refusal-detection and provider-switching, cutting off access to the frontier models that make the routing valuable in the first place.
- 2The intent classification may be too inaccurate to reliably distinguish legitimate security research from genuinely malicious requests, either frustrating users with false routing or creating liability by being too permissive.
- 3Frontier model providers may relax their safety filters in response to competitive pressure from open-weights models, eliminating the core pain point and making the routing layer unnecessary.
Evidence Summary
How AI synthesized this insight — no verbatim quotes
Approximately 12 commenters in the discussion expressed frustration with LLM safety filters blocking legitimate security work. Multiple users reported switching to DeepSeek, GLM, or Kimi after Claude refused tasks like confirming vulnerability reports, implementing local control servers, or explaining file descriptor operations. One user described renting GPU boxes to self-host models with controllable inference. At least one user canceled their Claude subscription over the issue. The consistent theme is that developers are already building manual workarounds — routing, fallback, and provider switching — but no automated tool exists to streamline this process.
Action Plan
Validate this opportunity before writing code
Recommended Next Step
Build
Strong demand signals detected. Real pain, real willingness to pay — start building an MVP.
Landing Page Copy Kit
Ready-to-paste copy based on real Reddit community language — no editing required
Headline
LLM Router for Security Professionals
Sub-headline
An API proxy and IDE plugin that intelligently routes developer requests across multiple LLM providers, automatically sending security-sensitive and system programming queries to less restrictive models (DeepSeek, GLM) while routing general coding tasks to frontier models (Claude, GPT-4). This eliminates the workflow disruption developers experience when their primary LLM refuses legitimate security research tasks.
Who It's For
For Security researchers, penetration testers, kernel/driver developers, and system programmers who regularly use LLMs for code analysis and vulnerability research but are blocked by safety filters
Feature List
✓ OpenAI-compatible API proxy that drops into existing tools (Copilot, Cursor, etc.) ✓ Intent-aware routing engine that detects security/system programming queries and routes to unrestricted models ✓ Multi-provider fallback chain with automatic retry on refusals ✓ Developer verification system (GitHub history, employer domain) to unlock security features ✓ Usage dashboard showing routing decisions and cost breakdown across providers
Where to Validate
Share your landing page in r/HN · front_page — that's exactly where these pain points were discovered.
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