Low Severity

Prompt injection: Instructions to an AI in a calendar invite

Description

Detects calendar invites whose summary or description addresses an AI (an assistant, a named model such as 'Gemini,', 'the user', 'previous instructions') where NLU finds a request and the prompt injection model agrees on the same field. Calendar assistants read the full event text. Restricted to senders with low prevalence and no benign history, and excludes graymail from senders passing DMARC.

References

No references.

Sublime Security
Created Oct 21st, 2026 • Last updated Oct 21st, 2026
Source
type.inbound
//
// This rule makes use of a beta feature and is subject to change without notice
// using the beta feature in custom rules is not suggested until it has been formally released
//
and any(filter(attachments,
               .content_type in ("text/calendar", "application/ics")
               or .file_extension =~ "ics"
        ),
        any(file.explode(.),
            any(.scan.ics.calendars,
                any(.components,
                    any([.summary, .description],
                        regex.icontains(.,
                                        '\b(?:assistant|llm|screener|summari[sz]er)s?\b|(?:^|[\n\[(>\x27\".:])\s*(?:hey\s+)?(?:chatgpt|gemini|copilot|claude)\s*[:,]|\b(?:ai|language)\s+models?\b|\bthe\s+user\b|\b(?:previous|prior)\s+instructions\b'
                        )
                        and any(ml.nlu_classifier(.).entities,
                                .name == "request"
                        )
                        and beta.prompt_injection_detection(.).detection == "injection"
                        and beta.prompt_injection_detection(.).confidence in (
                          "medium",
                          "high"
                        )
                    )
                )
            )
        )
)

// an injection arrives from outside the recipient's correspondence... the profile
// is unauthenticated, so a spoofed known correspondent is suppressed too
and profile.by_sender_email().prevalence in ("new", "outlier", "rare")
and not profile.by_sender_email().any_messages_benign

// graymail from authenticated senders... AI-product newsletters and webinars
and not coalesce(beta.attack_score_flash().verdict == "graymail"
                 and headers.auth_summary.dmarc.pass,
                 false
)
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