diff --git a/README.md b/README.md
index 448ff8a..18fad26 100644
--- a/README.md
+++ b/README.md
@@ -312,7 +312,7 @@ Watermarking and provenance for AI-generated content is now regulated in several
 
 This tool defends already-distributed AI imagery against automatic detection systems (social-platform "Made with AI" labels, third-party classifiers, content-policy filters). It does **not** retroactively anonymise generation.
 
-In particular, **SynthID-Image** (Google, deployed 2025 with Gemini 3 Pro / Nano Banana Pro / Imagen 4 / Veo) carries a **multi-bit payload** — the paper's SynthID-O variant encodes 136-bit payloads in 512x512 images ([arxiv 2510.09263](https://arxiv.org/abs/2510.09263)). The payload is believed to encode a user / session identifier. If the original watermarked file ever passed through a system controlled by the prompt originator (a saved Gemini account history, a screenshot uploaded to a Google product, a backup), Google retains the ability to link that original to the generating account. Stripping the watermark from a copy you possess does not erase Google's server-side record.
+In particular, **SynthID** (Google DeepMind) is embedded across Google's generative media stack — Imagen (images), Veo (video), Lyria (audio) — and Gemini app image outputs (Nano Banana / Gemini 3 Pro, which we verified positive via the Gemini app's SynthID oracle); Google reported over 10 billion items watermarked by December 2025. It carries a **multi-bit payload** — the research paper's SynthID-O variant encodes 136-bit payloads in 512x512 images ([arxiv 2510.09263](https://arxiv.org/abs/2510.09263)). The payload is believed to encode a user / session identifier. If the original watermarked file ever passed through a system controlled by the prompt originator (a saved Gemini account history, a screenshot uploaded to a Google product, a backup), Google retains the ability to link that original to the generating account. Stripping the watermark from a copy you possess does not erase Google's server-side record.
 
 Use cases where the threat model fits:
 - You generated the image yourself, want to publish it as your own work, and accept the consequences if Google ever publishes their detector logs.
diff --git a/data/samples/openai-images-2/README.md b/data/samples/openai-images-2/README.md
index 42dfdb4..2f492a3 100644
--- a/data/samples/openai-images-2/README.md
+++ b/data/samples/openai-images-2/README.md
@@ -26,7 +26,7 @@ The `trainedAlgorithmicMedia` tag is what triggers "Made with AI" labels on Inst
 
 ### Invisible pixel-level watermark
 
-OpenAI's system card for Images 2.0 states the model embeds an "imperceptible, robust, and content-specific" pixel-level watermark alongside C2PA. No public detector exists, so bypass cannot be verified empirically for this sample.
+OpenAI's system card for Images 2.0 states the model embeds an "imperceptible, robust, and content-specific" pixel-level watermark alongside C2PA. This sample was downloaded 2026-04-22, before OpenAI's 19 May 2026 rollout of Google's SynthID watermark across ChatGPT / Codex / the API, so it likely predates SynthID and carries only the original content-specific watermark. Since that rollout, the openai.com/verify tool (in preview) is the public oracle for both signals; there is still no local decoder, so bypass cannot be verified empirically here without the oracle.
 
 ## Reproducing the removal