Several social-engineering signals are stacked together.
This is a safety recommendation, not proof of fraud.
A calm safety layer for students, families, and school staff. Inspect the sender, the story, and the destination—without opening a single link.
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Judge mode walks through one representative case, the safe report, and the test metrics.
Several social-engineering signals are stacked together.
This is a safety recommendation, not proof of fraud.
Run a local Ollama review to look for meaning-level persuasion patterns that complement the explainable evidence engine.
If no local model is available, PhishLens keeps the deterministic evidence analysis fully usable.
Instead of generating usable scam text, PhishLens explains which danger signals would still survive a cosmetic rewrite.
A transparent 36-case dataset includes benign, multilingual, misspelled, image-text, QR, header, and adversarial cases. It reports behavior metrics without pretending to be real-world accuracy.
Choose a trusted recipient and export a local handoff only after consent. PhishLens never sends it for you.
Analyze a message to create a redacted handoff preview.
No handoff has been exported.
Use synthetic or voluntarily supplied content. Only anonymous timing and outcome choices stay in memory.
No pilot session started. No original message will be included in the export.
Judge mode loads a representative school case, reveals the evidence trail, prepares a redacted report, and runs the adversarial behavior dataset in one guided path.
Every alert points to visible evidence, not a black-box probability.
Messages are analyzed locally. Links stay unopened until the person decides what to do.
Leave with a safer next move and a privacy-preserving report—not just a warning badge.