IPv4

Detects IPv4 patterns. This pattern is based on a Microsoft Purview built-in sensitive information type. Users already running Purview may prefer to enable the built-in SIT directly, or use this version as a starting point for customisation.

Type

regex

Engine

universal

Confidence

high

Confidence justification

High confidence: structurally constrained pattern with corroborative keyword support reduces false positive rates significantly. Added context gating and exclusion rules improve precision and reduce incidental matches.

Detection quality

Verified

Jurisdictions

global

Frameworks

CIS Controls, ISO 27001, NIST CSF, SOC 2

Data categories

network, pii

Scope

wide

Risk rating

4

Platform compatibility

Purview: Compatible, GCP DLP: Compatible, Macie: Compatible, Zscaler: Compatible, Palo Alto: Compatible, Netskope: Unsupported

Pattern

\b(?:25[0-5]|2[0-4]\d|[01]?\d\d?)\.(?:25[0-5]|2[0-4]\d|[01]?\d\d?)\.(?:25[0-5]|2[0-4]\d|[01]?\d\d?)\.(?:25[0-5]|2[0-4]\d|[01]?\d\d?)\b

Corroborative evidence keywords

IP address, IP, network, host, server, address, age, birthday, citizenship, city, date of birth, DOB, email, ethnicity, fax, first name, full name, gender, given name, last name (+43 more)

Proximity: 300 characters

Should match

• 192.168.1.1 — Private network IPv4 address
• 10.0.0.1 — Class A private IPv4
• 255.255.255.0 — Subnet mask

Should not match

• 256.168.1.1 — First octet exceeds 255
• 192.168.1 — Only 3 octets instead of 4
• 192.168.1.999 — Last octet exceeds valid range (999 > 255)
• template example placeholder record identifier — Template/sample context should be excluded even when anchor words are present

Known false positives

• Common words and phrases related to ipv4 appearing in policy documents, training materials, HR templates, or compliance guidelines without actual personal data. Mitigation: Require corroborative evidence keywords within the proximity window to confirm sensitive data context rather than general discussion.
• In English (as the primary international business language), similar terminology used in formal or administrative contexts (education, professional documentation) that does not constitute sensitive data collection. Mitigation: Layer with additional contextual signals such as structured identifiers, form fields, or database column headers to distinguish sensitive records from general references.
• High-frequency pattern matches in large document corpora due to broad regex anchors. Expected match rate is significantly higher than specific identifier patterns. Mitigation: Tune confidence thresholds for bulk scanning. Consider using this pattern primarily as a pre-filter with secondary validation.

References

• IP address entity definition - Microsoft Learn

Collections

• Network & Device Identifiers