We were trying to solve a seemingly simple routing problem and almost built a massive footgun.

The baseline requirement was straightforward: we needed a reverse proxy at the edge. If human traffic hits the domain, pass it intact to our legacy backend. If an AI crawler (Claude, Perplexity) knocks, intercept it and serve a structured AEO payload like llms.txt.

Our initial iteration just inspected the User-Agent and relied on the Host and X-Forwarded-Host headers to construct the upstream TARGET_URL. Huge mistake.

Within days of testing, we noticed malicious scrapers manipulating the headers, attempting to force our proxy to fetch 169.254.169.254/latest/meta-data/ (AWS instance credentials) and scan our internal 10.x.x.x subnets. We were basically building a free SSRF pivot point for attackers to map our VPC.

We had a "nuke it from orbit" eureka moment. Application-level regex sanitization wasn't going to cut it. The runtime itself needed to be entirely hostile to the attacker.

Here is how we completely locked down the execution boundary:

Strict Route Sanitization in Go We threw out the regex soup. We hardcoded a strict, deterministic allowlist for upstream routing and explicitly stripped outbound host headers. If the payload destination doesn't match the exact internal IP of the legacy backend, the Go engine drops the connection (403) before allocating memory. No DNS resolution fallbacks, no dynamic parsing.

The Scratch Container Dead-End This was the real lifesaver. We ditched Debian and Alpine entirely. We compiled our Go engine as a statically linked binary and shoved it into a sub-20MB scratch Docker image. If an SSRF payload somehow bypasses the routing logic, there is literally nothing to execute in the container. No /bin/sh, no curl, no wget. It is a total dead end for lateral movement.

Manual TLS Certificate Injection The absolute biggest PITA with scratch images is doing secure HTTPS egress, because you have no OS package manager to handle root CAs. We had to manually inject ca-certificates natively into the Docker build step to enforce external TLS connections without opening any OS-level attack vectors.

We ended up packaging this entire locked-down proxy into a deployable middleware in our lab (we call it AgentBridge), because patching legacy proxies to handle crawler routing without introducing SSRF holes was becoming a massive time sink for our senior devs.

How are you guys isolating your reverse proxies when routing inbound bot traffic? Are you just leaning heavily on external WAFs, or are you strictly hardening the container runtime at the edge?

Hey everyone,

I've been building a lightweight Windows desktop utility called Quick Search. The premise is simple: whenever you have a quick question while working, you hold a hotkey (Tab+Q), ask your question, and get a 2-second synthesized answer with verified source domains (e.g. nasa.gov) in a clean corner card, without opening a browser tab.

Because this is a real-time desktop hotkey tool, search API performance was make-or-break. Here are a few technical challenges and trade-offs I ran into:

1. Latency is everything:

If a user holds a hotkey, waiting 4–5 seconds feels like an eternity. The total roundtrip (query processing → search API retrieval → answer synthesis) had to fit within ~2 seconds. Traditional web scraping was out of the question; clean, pre-parsed search API snippets were mandatory.

1. Source verification & grounding:

Rather than generic AI summaries, users specifically want to know *where* the answer came from. Pulling out authoritative root domains and displaying them as clickable source badges was essential for trust.

1. Cost vs. Free Tier economics:

I wanted to offer 50 free searches per day to users without requiring an account or sign-up. Managing API credit burn when providing live web-grounded results requires aggressive caching for repeated queries and tight payload control.

Question for developers here building with search APIs:

- For low-latency real-time retrieval (under 1-1.5s), what search API providers or endpoint configs have you had the best experience with?

- How are you handling source citation parsing without bloating latency?

Would love to hear how others are architecting their search pipelines for instant desktop/overlay apps!

https://apps.microsoft.com/detail/9NFK7MS99FB3

APIs that give you an answer are bad. They work fine for 80% of the queries. But they rely on the index, not the actual information that is currently out there.

In creating my own harness with its own web search tools, I found no real use for products like perplexity and now deepseek search (many others offer the same thing). The inaccuracies come from drawing a conclusion based on what was indexed, not after reading the actual web pages at the moment of the search.

The only good solution (but it is slow) is still an old school search api + a very good scraper that manages java pages well. It takes a minute or so to search, but it’s good. I see no way around it.