Project: Open Policy Agent (OPA) (Provisioning / Security & Compliance)
File: REGO_V2_PROPOSAL.md

Rego v2 - Proposal Authors: Tristan Swadell, Tim Hinrichs, Torin Sandall Last-Modified: 2018-02-22 This document serves to facilitate collaborative development of the design of a general-purpose policy language. General-purpose means that the language should be applicable to any domain, layer of the stack, or enforcement point. Different implementations of the language runtime may be better suited to different applications. The user-experience for policy enforcement depends heavily on the policy language and what concepts the user must understand to use that language. The proposed concepts thus far are: Rule* - An identifier with optional parameters that conditionally produces a decision. May refer to other rules, constants, and functions. Declared within modules. May be overloaded. Context* - Data provided at evaluation time or through calls to external data-sources. Rules may declare a signature with the expected context. External datasources may be a file, database, or API. The proposed language has the following properties: Side-effect free* and non-Turing complete. Rules, functions, and constants are declared within modules. Rules are evaluated by name or by module. Decisions are qualified by the module name where they are declared. Conflicts must be decided by a decision resolver or by the actor calling the engine. The rule declaration provides a named entry point for evaluation and composition. The signature of the rule declares the context to be provided upon evaluation, and the body is a collection of conditions and decisions. Please note that the definition of `expr` and `literal` are taken from the (CEL): ``` rule_decl := 'rule' id assignexpr (ifexpr else_expr*)? | 'rule' function_signature '{' statement+ '}' ; const_decl := decorator? id assign_expr ; assign_expr := '=' (expr | comprehension_expr) ; function_decl := decorator? 'function' function_signature ('{' statement+ '}')? ; function_signature : id '(' arg_list? ')' ; arg_list := id (',' id)* ; decorator: : '@' id ; statement := condition_expr | const_decl | return_expr | comprehension_expr ; condition_expr := if_expr '{' statement+ '}' ; if_expr := 'if' expr ; else_expr := 'else' (expr | if_expr) ; return_expr : 'return' (expr | comprehension_expr) ; comprehension_expr := iter_expr | '{' (expr '|')? iter_expr '}' | '[' (expr '|')? iter_expr ']' ; iter_expr := 'for' id (',' id)? 'in' expr if_expr? statement? | 'for' id (',' id)? 'in' expr if_expr? ('{' statement+ '}')? ; ``` Rules represents a decision and are declared distinctly from constants and functions. Rules may be constant-like or function-like. Constant-like rules yield decisions derived from module or system provided context. Function-like rules declare a function signature that indicates the context required from the caller. The body of the rule may contain any number of conditions, decisions, and local declarations. ``` rule userSalary(resource, user) { matchresult = resource.match('users/{targetuser}/salary'); return user == matchresult.group.targetuser; } ``` Rules may be imported and leveraged within rule decisions. Note the inclusion of the rule within a package and how this affects function identifier resolution. ``` package acme; import acme.hr; rule readUserSalary(request, resource, user) { matchresult = resource.match('users/{targetuser}/salary'); if (match_result.matches() && request.method == 'get') { targetuser = matchresult.groups.target_user return (hr.isManager(user, target_user) || hr.isAdmin(user) || user == target_user) } return false; } // outputs -> {'rule':

'result': bool} ``` Rules may have multiple return statements in order to enforce allow / deny semantics (in the case of binary rules), or simply different variations on an affirmative rule decision, such as whether to return a list of honey-pot servers versus a valid list of servers. ``` rule readUserSalary(request, resource, user) { matchresult = resource.match('users/{targetuser}/salary') if (match_result.matches() && request.method == 'get') { targetuser = matchresult.groups.target_user // Deny requests outside of business hours. if (request.time.hour() < 9 || request.time.hour() > 17) { return false } return (hr.isManager(user, target_user) || hr.isAdmin(user) || user == target_user) } return false } ``` Rules may be composed from other rules and functions. The example below groups reading and listing salaries into a single decision. ``` // Rules may be composed. rule viewSalary(request, resource, user) { return queryDepartmentSalaries(request, resource, user) || readUserSalary(request, resource, user); } rule queryDepartmentSalaries(request, resource, user) { match_result = resource.match('departments/{department}/salaries') if match_result.matches() && request.method == 'list' { department = match_result.groups.department; return !('user' in request.params.fields) && hr.department(department).manager == user; } return false; } // Evaluating of the 'acme' module produces: // [{'rule': 'acme.viewSalary', 'result': bool}, // {'rule': 'acme.viewUserSalary', 'result': bool}, // {'rule': 'acme.queryDepartmentSalaries', 'result': bool}] // // Evaluation of just acme.viewSalary would yield only the first decision. ``` Rules may also be written in a constant style where overloading occurs on the name. Developers may choose to write logically ORed statements together or provide overloads as a means of augmenting the decision set that can be attached to a rule. ``` // Constant-like rule which supports named evaluation. // // The authorized value is optionally assigned to the identifier 'allow' // depending on the request.auth condition. // // Note, if the condition evaluates false, authenticated is not assigned and // not included in the decision set. rule authorized = allow if request.auth != null // Overloads the authorized grant to also permit access to public resources. // // When the request is both authenticated and against a public resource, the // decision set will include two authorized results. // // A conflict resolution strategy of 'anyAllow' would ensure a single result // for the authorized decision. The default conflict resolution behavior could // be to aggregate overloaded decisions if the type supports aggregation: // e.g. sets, lists, boolean // Conflict resolution requires further discussion. rule authorized = allow if resource.name.contains('/public/') // Rules may also be as a conditional assignment with if-else conditions rather // than as overloads if the developer would like to control the overload // behavior. rule rateLimit = 100 if 'admin' in request.auth.claims else 50 if 'owner' in request.auth.claims else 10 ``` Conditions are (CEL) expressions and evaluate to a boolean outcome. A condition may be used to select applicable rules or to make an effect or trigger conditional. Conditions may also be used to filter list and map entries within a `for-in` expression. Declarations within a condition are within its block scope and may be shadowed by declarations in nested conditions. Once a declaration has been assigned, it cannot be reassigned. A rule represents a conditional decision which may depend on other rule decisions. The types of overloaded rule declarations should agree. In the case of multiple `rule`s being evaluated where the output types do not agree, the decision is dynamically typed. Rule decisions are maybe values, in the sense that the result may be a valued type or undefined. This is a crucial feature in support of rule overloading and evaluation with partial

The decision semantics when multiple `rule`s are evaluated depends on the conflict resolution algorithm declared within the policy or on the caller. Note: conflict resolution across `rule`s are as yet undefined, but will be addressed in a future update to the proposal. Triggers are not a separate concept, but rather a core consideration of how the `rule` declarations are designed. Since each rule emits at most one decision, this makes it feasible to write rules which go beyond request and config validation, and apply to the conditional execution of additional compute coordinated by the policy engine. Conceptually, triggers align with the concepts of obligations and advice introduced within . The difference between whether something is an obligation or advice typically boils down to whether the action to perform is synchronous or asynchronous. Synchronous obligations may include preconditions, whereas async obligations would be considered promises. Advice, on the other hand, should always be considered asynchronous and best-effort. The following is an example of a rule that acts as a trigger to log request behavior and check quota. ``` // This rule conditionally produces metadata indicating that a quota // check should be performed. The evaluation engine will support the // registration of decision handlers whose behavior will affect the // overall request handling. rule hasQuota(request) { if authenticated == allow { // Should return a payload flagged as an obligation, that can be // processed by a decision handler registered with the evaluator // for the <package-name>.hasQuota decision. return quota.check('perMethodPerUser', [{name: 'method', value: request.method}, {name: 'user', value: request.auth.principal}]) } } // The payload for a log statement could be as simple as a string. rule log = logger.log(request.auth.principal " denied request on " resource.name) if authenticated != allow // Module-based evaluation of these rules would output the following // decisions: // [{'rule': 'hasQuota', // 'result': { // 'type': 'obligation', // 'handler': 'quota.check', // 'metadata' : { 'metric': 'perMethodPerUser', args:[ ... ]}}}, // {'rule': 'log', // 'result': { // 'type': 'promise', // 'handler': 'logger.log', // 'metadata': {'message': ...}}}] ``` Being able to verify the correctness policy-related logic is of paramount importance. As is the ability to pose ad hoc queries with partial state. To this end we include `@test` as supported decorator and introduce the `with-as` clause to assist with partial state bindings required for both adhoc queries and for function mocking. Note: the following is under review and not yet reflected in the grammar. ``` rule userownedaction(auth, resource) { result = resource.matches('documents/{owner}/') return (result.owner == auth.principal || resource.owner in user_groups(auth.principal)); } @extern function user_groups(user); function mockusergroups(user) { } @test function group_check() { with usergroups as mockgetgroupusers { assertTrue(userownedaction({principal: 'me'}, 'documents/my-group')) assertFalse(userownedaction({principal: 'me'}, 'documents/their-group')) } } ``` Context is either supplied through arguments provided to the function, through constant declarations within the module, or through external functions invoked at evaluation time. The following are all examples of how context may be provided: ``` package acme; syntax = 'rego.v2'; // Functions bound at evaluation time. @extern function resource(); @extern function query(document_name); // Constant declaration based on external function calls. ctx = {resource: resource().name, resource_owner: resource().owner}; // Allow user-owned reads, with user and request provided as a rule argument. rule allowuserreads(user, request) { if (request.method in ['get', 'list']) { return (request.auth.claims.email == user || ctx.resource_owner == user || query("/documents/" +

== user); } return false; } ``` It will likely be common practice to provide @extern functions within their own module like so: ``` package acme.db; syntax = 'rego.v2'; @extern function resource(); @extern function query(document_name); ``` ``` package acme; import acme.db; syntax = 'rego.v2'; // Constant declaration based on external function calls. ctx = {'resource': db.resource().name, 'resource_owner': db.resource().owner}; // Allow user-owned reads, with user and request provided as a rule argument. rule allowuserreads(user, request) { if (request.method in ['get', 'list']) { return (request.auth.claims.email == user || ctx.resource_owner == user || db.query("/documents/" + ctx.resource).created_by == user); } return false; } ``` The example below shows how `acme.db` provides a library of context and functions for use with rules. The `@extern` decorator is equivalent to a forward declaration, both to serve as documentation for what exists, but also to be consumed during type-checking to ensure the system context and function hooks are being used correctly within rules. ``` package acme.db; syntax = 'rego.v2'; @extern request; @extern function resource(); @extern function query(document_name); input = { 'method': request.method, 'user': request.auth.claims.email, 'resource': resource() } permission = { 'read': input.method in ['get', 'list']; 'write': input.method in ['create', 'update', 'delete']; } function resourceMatch(pattern) { return resource().name.match(pattern).groups; } ``` ``` package acme; import acme.db; syntax = 'rego.v2'; // Allow user-owned reads, with context information provided by functions and // constants provided by acme.db in the form of module or extern declarations. rule authorized() { targetuser = db.resourceMatch('users/{targetuser}/salary').target_user; return db.permission.read && (db.input.user == target_user || db.input.resource.owner == target_user || db.query("/documents/" + input.resource.name).createdby == targetuser); } ``` Rego v2 is a series of extensions to the Common Expression Language (CEL) with the aim of clarifying the flow of execution from Rego v1 while preserving its features and incorporating the non-Turing complete, partial evaluation semantics of CEL. ``` module := package? import* decls ; package := 'package' qualified_id ';' ; import := 'import' qualified_id ('as' id)? ';' ; decls := (ruledecl | functiondecl | const_decl)* ; rule_decl := 'rule' id assignexpr (ifexpr else_expr*)? | 'rule' function_signature '{' statement+ '}' ; const_decl := id assign_expr | decorator id ; assign_expr := '=' (expr | comprehension_expr) ; function_decl := decorator? 'function' function_signature ('{' statement+ '}')? ; function_signature : id '(' arg_list? ')' ; arg_list := id (',' id)* ; decorator: : '@' id ; statement := condition_expr | const_decl | return_expr | comprehension_expr | with_block ; condition_expr := if_expr '{' statement+ '}' ; if_expr := 'if' expr ; else_expr := 'else' (expr | if_expr) ; return_expr : 'return' (expr | comprehension_expr) ; comprehension_expr := iter_expr | '{' (expr '|')? iter_expr '}' | '[' (expr '|')? iter_expr ']' ; iter_expr := 'for' id (',' id)? 'in' expr if_expr? statement? | 'for' id (',' id)? 'in' expr if_expr? ('{' statement+ '}')? ; with_block : 'with' qualified_id 'as' id '{' statement+ '}' ; expr := orexpr ('?' orexpr ':' expr)? ; or_expr := andexpr ('||' andexpr)* ; and_expr := relationexpr ('&&' relationexpr)* ; relation_expr := calc_expr | relationexpr ('<'|'<='|'>='|'>'|'=='|'!='|'in') relationexpr ; calc_expr := unary_expr | calcexpr ('*'|'/'|'%') calcexpr | calcexpr ('+'|'-') calcexpr ; unary_expr := member_expr | '!'+ member_expr | '-'+ member_expr ; member_expr := primary_expr | member_expr '.' id | memberexpr '.' id '(' exprlist? ')' | member_expr '[' expr ']' | qualifiedid '{' fieldinits? '}' ; primary_expr := '.'? id |

id '(' expr_list? ')' | '(' expr ')' | '[' expr_list? ']' | '{' map_inits? '}' | literal ; expr_list := expr (',' expr)* ; field_inits := id ':' expr (',' id ':' expr)* ; map_inits := expr ':' expr (',' expr : 'expr')* ; qualified_id := '.'? id ('.' id)* ; ``` Note: CEL and Rego are gradually typed languages. Although the proposal does not describe developer-defined type designations on constants and functions, this may be introduced in the future. Constants are identifiers associated with an expression. They are useful for clarifying the logical relationship between components of a rule decision. Constants referenced within expression will evaluate in the same manner as though they were written inline into the statement. Functions are simply collections of logical statements. Functions decorated with `@extern` must only declare a signature as the implementation is provided by the calling environment. Functions decorated with `@test` may incorporate `with` blocks and cannot be directly or indirectly referenced by `rule` declarations. Functions are idempotent. Given the same input, the functions must return the same output. Idempotency must hold for both local and extern functions. At present functions do not support overloads, though this may change in future iterations of this proposal. The general form of a function is as follows: ``` function_decl := decorator? 'function' id '(' arg_list? ')' ('{' statement+ '}')? ; decorator := '@' id ; ``` The set of supported decorators is limited to `@extern` and `@test`. When a function is annotated with `@extern`, it must be supplied at runtime as part of the rule evaluation context. For example: ``` // Environment must bind a handler for 'db.get' function calls from the policy. package db; @extern function get(document_name); ``` The one key difference between a Rego v2 expression and a CEL expression is that Rego v2 has an explicit syntax for list comprehensions rather than use the optional CEL macros. This syntax simplifies quantifiers as well as mapping and filtering while permitting the introduction of specialized reducing functions. It is recommended, but not required that comprehensions be performed within local functions rather inline within a rule, but this is not a requirement. The general form of a comprehension is as follows: ``` comprehension_expr := iter_expr | '{' (expr '|')? iter_expr '}' // set, map comprehension | '[' (expr '|')? iter_expr ']' // list comprehension ; iter_expr := 'for' id (',' id)? 'in' expr iteropexpr? statement? | 'for' id (',' id)? 'in' expr iteropexpr? ('{' statement+ '}')? ; iteropexpr := if_expr | 'all' expr | 'any' expr ; filter_expr := 'if' expr ; ``` A set comprehension differs from a list comprehension only in the sense that the entries within the set are unique. Set comprehensions are also used for constructing maps and complex objects where the uniqueness constraint generally holds true. Within maps, colliding keys are overwritten. Within a comprehension, colliding keys values are merged if the value is declared as a list. The `for-in` expression may be filtered using a condition. The result of the filtering, absent of other syntax, will be the same as the range type of the `for-in` expression. If the for-in range is a list, the result type will be a list. The same is true for maps, structs, and messages. ``` for u in users if

in ['secret', 'top secret'] // list of users ``` Filters may be chained as well. ``` { user: [doc] | // Iteration variables may be referenced within the transform statement for user in users if user.clearance in ['secret', 'top_secret'] // The statement after a for-in is implicitly within its block scope. // Curly braces may be used to explicitly denote the block. for doc in documents if doc.clearance <= user.clearance } ``` The quantifiers rely on filtering and simply test the `size()` of the filter result. The result type of the for-in is determined by the surrounding braces. ``` // exists one [ for e in list if e < 10 ].size() == 1 // exists at least two unique values, note the `{}` surrounding the `for-in` // indicates this is the construction of a set from a list. { for e in list if e.startsWith('t') }.size() > 2 ``` There are also two special operators which can be used to make qualitative inferences about the elements within an aggregate type, `all` and `any`. The primary difference between these operators and the filter expressions (or even standard comprehensions) is that they are accumulator functions with the same semantics as the logical `&&` and `||`, meaning these operators can absorb errors. ``` // Any element exists in this list for e in list any e != 'bad_candidate' // All elements in this list must be good candidates for e in list all e == 'good_candidate' ``` The `any` and `all` yield boolean outcomes and are thus specialized reducing functions capable of absorbing errors in the same manner as hand-rolled code. It is very common for developers to massage data from a variety of sources in order to compose the desired format best suited for the task at hand. ``` // Set of unique image names { image.name | for releasename, image in releaseimages } // Map of image name to release names // Collisions on the image.name will overwrite the existing value. // Note: Consider adding syntactic sugar to deal with object construction // during list comprehensions. { image.name : releasename | for releasename, image in release_images } // List (of pairs) comprehension. // There is an implicit single-statement block after a for-in if no // curly braces are present. [ [user, file] | for file in files for user in file.viewers + [file.owner] if user.matches("@{domain}.{tld}$").groups.domain in ["styra", "google"] ] // Equivalent to the above, but with a set of unique user, file tuples and // explicit block syntax. { [user, file] | for file in files { for user in file.viewers + [file.owner] if user.matches("@{domain}.{tld}$").groups.domain in ["styra", "google"] ] } } ``` Rather than introduce a special syntax for reduction, Rego v2 provides the helper functions: `sum()`, `flatten()`, and `join()`. Additional functions will be added over time, but these helpers represent the most common use cases of reduction. A module represents a collection of functions and constants. Modules are in the root package unless otherwise indicated by a package declaration. Multiple modules may share the same package. Functions in modules within the same package are accessible within other modules without specifying the qualified function name, e.g. `module.func()`. Importing a module makes all symbols within that module accessible by either the fully qualified module name, or the simple module name (the last fragment of a qualified package identifier).