Fake message thread with a suspicious link and engaging language from an unknown sender
Detects fake message threads with suspicious links and financial request language
Sublime rule (View on GitHub)
1name: "Fake message thread with a suspicious link and engaging language from an unknown sender"
2description: "Detects fake message threads with suspicious links and financial request language"
3type: "rule"
4severity: "medium"
5source: |
6 type.inbound
7 and length(body.links) < 10
8 // suspicious link
9 and any(body.links,
10 .href_url.domain.root_domain not in $tranco_1m
11 and .href_url.domain.domain not in $umbrella_1m
12 )
13
14 // fake thread check
15 and (strings.istarts_with(subject.subject, "RE:") or strings.istarts_with(subject.subject, "FWD:"))
16
17 // Check for the Presence of References or In-Reply-To properties
18 and (
19 (length(headers.references) == 0 and headers.in_reply_to is null)
20 or (
21 not any(headers.hops, any(.fields, strings.ilike(.name, "In-Reply-To")))
22 and not any(headers.hops, strings.ilike(.signature.headers, "*:reply-to"))
23 )
24 )
25
26 // sender's domain is not in body, and body has > 0 links
27 and length(body.links) > 0
28 and sender.email.domain.root_domain not in $free_email_providers
29 and not any(body.links, .href_url.domain.root_domain == sender.email.domain.root_domain)
30
31 // unusual sender (email address rarely sends to your organization)
32 and sender.email.email not in $sender_emails
33
34 // unusual sender domain (domain rarely sends to your organization)
35 and sender.email.domain.domain not in $sender_domains
36 and 4 of (
37 // language attempting to engage
38 (
39 any(ml.nlu_classifier(body.current_thread.text).entities, .name == "request")
40 and any(ml.nlu_classifier(body.current_thread.text).entities, .name == "financial")
41 ),
42
43 // invoicing language
44 any(ml.nlu_classifier(body.current_thread.text).tags, .name == "invoice"),
45
46 // urgency request
47 any(ml.nlu_classifier(body.current_thread.text).entities, .name == "urgency"),
48
49 // cred_theft detection
50 any(ml.nlu_classifier(body.current_thread.text).intents,
51 .name == "cred_theft" and .confidence in~ ("medium", "high")
52 ),
53
54 // commonly abused sender TLD
55 strings.ilike(sender.email.domain.tld, "*.jp"),
56
57 // headers traverse abused TLD
58 any(headers.domains, strings.ilike(.tld, "*.jp")),
59
60 // known suspicious pattern in the URL path
61 any(body.links, regex.match(.href_url.path, '\/[a-z]{3}\d[a-z]')),
62
63 // link display text is in all caps
64 any(body.links, regex.match(.display_text, '[A-Z ]+')),
65
66 // display name contains an email
67 regex.contains(sender.display_name, '[a-z0-9]+@[a-z]+'),
68
69 // Sender domain is empty
70 sender.email.domain.domain == "",
71
72 // sender domain matches no body domains
73 all(body.links, .href_url.domain.root_domain != sender.email.domain.root_domain),
74 )
75attack_types:
76 - "Credential Phishing"
77tactics_and_techniques:
78 - "Social engineering"
79detection_methods:
80 - "Content analysis"
81 - "Header analysis"
82 - "Natural Language Understanding"
83 - "Sender analysis"
84 - "URL analysis"
85id: "8fd0e211-285d-5cbd-9c11-868c0501b526"