How do you prevent XSS in a MERN app?
PICTURE THIS: A SENTENCE BECOMES TOKENS
The model does not read letters like humans. It reads these pieces, then predicts the next one.
Simple meaning
I escape output, avoid dangerouslySetInnerHTML, and sanitize any rich text.
WHY — Security instead of guessing?
Why interviewers care about Security:
question about Security.
trade-offs, and what you would actually do on a Full Stack project - not buzzwords.
Name the idea, why it exists, then one short example.
End with when you use it and one common pitfall.
STEPS — What happens with tokens?
Before the model can read a sentence, it goes through these steps:
- 1I escape output, avoid
dangerouslySetInnerHTML, and sanitize any rich text.
- 2HttpOnly cookies reduce token
theft from XSS.
- 3Embeddings
Content-Security-Policy adds defense in depth.
- 4Context mix
Attention looks at nearby tokens together.
- 5Next token
The model scores what should come next.
- 6Decode
IDs turn back into readable text.
EXAMPLE — See it in action
Let's see how a real sentence is tokenized (tokens may vary by model):
Note: Actual tokens and IDs depend on the tokenizer (e.g., GPT, Llama, etc.).
Key takeaway
I escape output, avoid dangerouslySetInnerHTML, and sanitize any rich text. HttpOnly cookies reduce token theft from XSS.