What specific metadata does Duck.ai strip before forwarding chats, and can forensic techniques re-link anonymized requests to users?
Executive summary
Duck.ai advertises that it removes personal identifiers — explicitly citing IP addresses and other personal metadata — before proxying prompts to third‑party model providers (DuckDuckGo help pages; ZDNet; ToolMage) [1] [2] [3]. Independent forensic research, however, shows many avenues outside a web proxy where identifying metadata can persist — network logs, endpoint artifacts and provider logs — and the sources provided do not publish a full technical spec proving absolute unlinkability, so re‑linking remains possible under certain conditions [4] [5] [6].
1. What Duck.ai says it strips: explicit claims and contractual limits
Duck.ai’s public help pages state that “all metadata that contains personal information (for example, your IP address) is completely removed before prompting the model provider,” and the company says it does not record or store chats or use them to train models; Duck.ai also notes contractual limits with providers that require deletion of data when no longer needed, with a stated maximum retention window in some cases [1]. Independent reviews and tech coverage repeat this core claim — that Duck.ai proxies requests and strips personal identifiers before forwarding them to models — while also flagging an exception: data strictly necessary for a provider to respond may be forwarded under the terms of the EULA and provider agreements (ZDNet; OpenTools; ToolMage) [2] [7] [3].
2. What “stripping metadata” practically includes — and what’s unstated
The publicly stated example — removal of IP addresses and “personal information” metadata — implies Duck.ai removes header‑level identifiers and direct client source addresses before requests hit third‑party models, but the sources do not publish a packet‑level or code‑level audit showing exactly which HTTP headers, cookies, or TLS metadata are suppressed [1] [3]. Coverage notes that recent chats are stored locally in the browser and that provider‑needed data is an exception, which creates a practical boundary between what Duck.ai claims to strip and what might still be transmitted to fulfill a model query [2] [1].
3. Can forensic techniques re‑link “anonymized” requests to users? Short answer: sometimes
Forensic literature demonstrates multiple independent channels that can re‑establish connections between an observed web request and an originating user even when a fronting service strips IPs: timestamp correlation in provider logs and network captures, URL and query structures, browser and OS artifacts, and diagnostic/event logs on endpoints can all yield identifying metadata (research on search URL structures and forensic analysis; memory/device forensics) [4] [5] [6]. These studies show that even when a proxy removes an IP, timing, unique query fingerprints or recovered client artifacts can be used to correlate and attribute activity to a device or user in a forensically supported investigation [4] [5].
4. Concrete re‑linking vectors to consider
Practical re‑linking paths include: provider logs that record request timestamps and model responses (and may retain auxiliary metadata per provider policy exceptions), network‑level captures at ISPs or local routers that record original IPs before proxying, and endpoint artifacts such as browser local storage, diagnostic events, or memory‑resident artifacts that record prompts or session identifiers — all documented in forensic research on URL traceability and device logs [4] [5] [6]. None of the Duck.ai sources supplied a attestable, independent audit that these vectors are impossible; instead, Duck.ai relies on proxying and contractual limits to reduce risk [1] [2].
5. How strong is the privacy claim — and what remains unknown
The available reporting and company statements consistently assert that Duck.ai removes IPs and personal metadata and limits provider use via contractual terms, which materially reduces casual linkability [1] [2] [3]. What the sources do not provide — and what prevents asserting absolute anonymity — is a published, third‑party technical audit of the exact metadata removed, packet traces showing stripping in practice, or provider logs proving deletion policies were followed; without those artifacts, forensic techniques described in the literature can, in specific circumstances, re‑link prompts to users [4] [5]. The balance: Duck.ai appears to implement proxy‑based stripping and contractual guardrails that raise the bar for attribution, but the sources show realistic forensic pathways remain if adversaries can access provider logs, network captures, or client devices.