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example.rego
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package example
### Entry point to the policy.
### Matches on incoming request.
# Rule matching collection of posts.
allow = true {
input.method = "GET"
input.path = ["posts"]
allowed[x]
}
# Rule matching individual post.
allow = true {
input.method = "GET"
input.path = ["posts", post_id]
allowed[x]
x.id = post_id
}
### Helper rules that implement data filtering & protection policy.
### Simple equality check.
# Return posts authored by input.user.
# OPA Query: "bob" = data.elastic.posts[_].author
# ES Query: {name:author value:bob boost:<nil> queryName:TermQuery}
# Sample Output from Elasticsearch:
# {
# "result": [
# {
# "id": "post1",
# "author": "bob",
# "message": "My first post",
# "department": "dev",
# "email": "[email protected]",
# "clearance": 2,
# "action": "read",
# "resource": "",
# "conditions": [],
# "likes": [],
# "followers": [],
# "stats": []
# },
# {
# "id": "post2",
# "author": "bob",
# "message": "My second post",
# "department": "dev",
# "email": "[email protected]",
# "clearance": 2,
# "action": "read",
# "resource": "",
# "conditions": [],
# "likes": [],
# "followers": [],
# "stats": []
# }
# ]
# }
allowed[x] {
x := data.elastic.posts[_]
x.author == input.user
}
### Simple built-in functions like !=, >, <.
# Return posts with clearance level greater than 0 and less than equal to 5
# but no posts from "it".
# OPA Query: lte(data.elastic.posts[_].clearance, 5); gt(data.elastic.posts[_].clearance, 0); neq(data.elastic.posts[_].department, "it")
# ES Query 1: {name:clearance from:<nil> to:5 timeZone: includeLower:true includeUpper:true boost:<nil> queryName: format: relation:}
# ES Query 2: {name:clearance from:0 to:<nil> timeZone: includeLower:false includeUpper:true boost:<nil> queryName: format: relation:}
# ES Query 3: {Query:<nil> mustClauses:[] mustNotClauses:[0xc0002ae240] filterClauses:[] shouldClauses:[] boost:<nil> minimumShouldMatch: adjustPureNegative:<nil> queryName:BoolMustNotQuery}
# Sample Output from Elasticsearch:
# {
# "result": [
# {
# "id": "post1",
# "author": "bob",
# "message": "My first post",
# "department": "dev",
# "email": "[email protected]",
# "clearance": 2,
# "action": "read",
# "resource": "",
# "conditions": [],
# "likes": [],
# "followers": [],
# "stats": []
# },
# {
# "id": "post2",
# "author": "bob",
# "message": "My second post",
# "department": "dev",
# "email": "[email protected]",
# "clearance": 2,
# "action": "read",
# "resource": "",
# "conditions": [],
# "likes": [],
# "followers": [],
# "stats": []
# },
# {
# "id": "post4",
# "author": "alice",
# "message": "Hii world",
# "department": "hr",
# "email": "[email protected]",
# "clearance": 3,
# "action": "read",
# "resource": "",
# "conditions": [],
# "likes": [],
# "followers": [],
# "stats": []
# },
# {
# "id": "post6",
# "author": "ken",
# "message": "Hii form Ken",
# "department": "ceo",
# "email": "[email protected]",
# "clearance": 5,
# "action": "read",
# "resource": "",
# "conditions": [],
# "likes": [],
# "followers": [],
# "stats": []
# }
# ]
# }
allowed[x] {
x := data.elastic.posts[_]
x.clearance <= 5
x.clearance > 0
x.department != "it"
}
### Built-in functions like string contains and regexp.
# Return posts containing the term "OPA" in their message.
# OPA Query: contains(data.elastic.posts[_].message, "OPA")
# ES Query: {queryString:*OPA* defaultField:message defaultOperator: analyzer: quoteAnalyzer: quoteFieldSuffix: allowLeadingWildcard:<nil> lowercaseExpandedTerms:<nil>
# enablePositionIncrements:<nil> analyzeWildcard:<nil> locale: boost:<nil> fuzziness: fuzzyPrefixLength:<nil> fuzzyMaxExpansions:<nil> fuzzyRewrite: phraseSlop:<nil>
# fields:[] fieldBoosts:map[] tieBreaker:<nil> rewrite: minimumShouldMatch: lenient:<nil> queryName:QueryStringQuery timeZone: maxDeterminizedStates:<nil> escape:<nil> typ:}
# Sample Output from Elasticsearch:
# {
# "result": [
# {
# "id": "post7",
# "author": "john",
# "message": "OPA Good",
# "department": "dev",
# "email": "[email protected]",
# "clearance": 6,
# "action": "read",
# "resource": "",
# "conditions": [],
# "likes": [],
# "followers": [],
# "stats": []
# },
# {
# "id": "post8",
# "author": "ben",
# "message": "This is OPA's time",
# "department": "ceo",
# "email": "[email protected]",
# "clearance": 10,
# "action": "read",
# "resource": "",
# "conditions": [],
# "likes": [],
# "followers": [],
# "stats": []
# }
# ]
# }
allowed[x] {
x := data.elastic.posts[_]
contains(x.message, "OPA")
}
# Return posts who email address matches the ".org" domain.
# OPA Query: re_match("[a-zA-Z]+@[a-zA-Z]+.org", data.elastic.posts[_].email)
# ES Query: {name:email regexp:[a-zA-Z]+@[a-zA-Z]+.org flags: boost:<nil> rewrite: queryName: maxDeterminizedStates:<nil>}
# Sample Output from Elasticsearch:
# {
# "result": [
# {
# "id": "post9",
# "author": "jane",
# "message": "Hello from Jane",
# "department": "it",
# "email": "[email protected]",
# "clearance": 7,
# "action": "read",
# "resource": "",
# "conditions": [],
# "likes": [],
# "followers": [],
# "stats": []
# }
# ]
# }
allowed[x] {
x := data.elastic.posts[_]
re_match("[a-zA-Z]+@[a-zA-Z]+.org", x.email)
}
### Nested examples which include a search.
# Return posts liked by input.user.
# OPA Query: "bob" = data.elastic.posts[_].likes[_].name
# ES Query: {query:0xc00032a800 path:likes scoreMode: boost:<nil> queryName:NestedQuery innerHit:<nil> ignoreUnmapped:0xc0004985f8}
# Sample Output from Elasticsearch:
# {
# "result": [
# {
# "id": "post10",
# "author": "ross",
# "message": "Hello from Ross",
# "department": "it",
# "email": "[email protected]",
# "clearance": 9,
# "action": "read",
# "resource": "",
# "conditions": [],
# "likes": [
# {
# "name": "bob"
# }
# ],
# "followers": [],
# "stats": []
# }
# ]
# }
allowed[x] {
x := data.elastic.posts[_]
y := x.likes[_]
y.name = input.user
}
# Return posts followed by input.user.
# OPA Query: "bob" = data.elastic.posts[_].followers[_].info.first
# ES Query: {query:0xc0001f0b40 path:followers.info scoreMode: boost:<nil> queryName:NestedQuery innerHit:<nil> ignoreUnmapped:0xc00038a67c}
# Sample Output from Elasticsearch:
# {
# "result": [
# {
# "id": "post11",
# "author": "rach",
# "message": "Hello from Rach",
# "department": "it",
# "email": "[email protected]",
# "clearance": 9,
# "action": "read",
# "resource": "",
# "conditions": [],
# "likes": [],
# "followers": [
# {
# "info": {
# "first": "bob",
# "last": "doe"
# }
# }
# ],
# "stats": []
# }
# ]
# }
allowed[x] {
x := data.elastic.posts[_]
y := x.followers[_]
y.info.first = input.user
}
### Deeply nested example.
# Return posts by authors from CA.
# OPA Query: data.elastic.posts[_].stats[_].authorstat.authorbio.state = "CA"
# ES Query: {query:0xc0004edd40 path:stats.authorstat.authorbio scoreMode: boost:<nil> queryName:NestedQuery innerHit:<nil> ignoreUnmapped:0xc0004f1471}
# Sample Output from Elasticsearch:
# {
# "result": [
# {
# "id": "post12",
# "author": "chan",
# "message": "Hello from Chan",
# "department": "it",
# "email": "[email protected]",
# "clearance": 9,
# "action": "read",
# "resource": "cfgmgmt:nodes",
# "conditions": [],
# "likes": [],
# "followers": [],
# "stats": [
# {
# "authorstat": {
# "authorbio": {
# "country": "US",
# "state": "CA",
# "city": "San Fran"
# }
# }
# }
# ]
# }
# ]
# }
allowed[x] {
x := data.elastic.posts[_]
y := x.stats[_]
y.authorstat.authorbio.state = "CA"
}