Crate tau_engine

Expand description

Tau Engine

This crate provides a library that tags documents by running and matching rules over them. The engine makes use of a Pratt parser and a tree solver in order to evaluate the detection logic of a rule against a document, if the outcome is true the document is considered tagged by that rule.

Rules

A rule is used to tag a document and is made up of three parts:

detection: the logic used to evaluate a document.
true positives: example documents that must evaluate to true for the given detection.
true negatives: example documents that must evaluate to false for the given detection.

The detection block is made up of a condition, and identifiers. This allows for simple but expressive rules, below is a brief summary (see Rules for more):

Identifiers

Identifiers are used to help keep the condition concise and generally contain the core of the matching logic. They consist of Key/Value pairs which allow for the extraction of data from the document and the evaluate of its value. It should be noted that mappings are treated as conjunctions, while sequences are treated as disjunctions.

Identifiers make use of the following matching logic:

foobar: an exact match of foobar
foobar*: starts with foobar
*foobar: ends with foobar
*foobar*: contains foobar
?foobar: regex foobar

Any of the above can be made case insensitive with the i prefix, for example:

ifoobar
ifoobar*

Escaping can be achieved with a combination of ' and ".

Condition

The condition is just a boolean expression and supports the following:

and: logical conjunction
or: logical disjunction
==: equality comparison
>, >=, <, <=: numeric comparisons
not: negate
all(i): make sequences behave as conjunctions
of(i, x): ensure a sequence has a minimum number of matches

Examples

detection:
  A:
    foo.bar: foobar

  condition: A

true_positives:
- foo:
    bar: foobar

true_negatives:
- foo:
    bar: foo

Documents

A document is anything that can provide data to the engine in a meaningful way, usually through Key/Value pairs, i.e: an event log, json object, yaml file, etc. Implementations are achieved with the Document trait.

Solving

This is an example of how you can tag a document against a provided rule:

use std::borrow::Cow;

use tau_engine::{Document, Rule, Value};

// Define a document.
struct Foo {
    foo: String,
}
impl Document for Foo {
    fn find(&self, key: &str) -> Option<Value<'_>> {
        match key {
            "foo" => Some(Value::String(Cow::Borrowed(&self.foo))),
            _ => None,
        }
    }
}

// Write a rule.
let rule = r#"
detection:
  A:
    foo: foobar
  condition: A
true_positives:
- foo: foobar
true_negatives:
- foo: foo
"#;

// Load and validate a rule.
let rule = Rule::load(rule).unwrap();
assert_eq!(rule.validate().unwrap(), true);

// Create a document.
let foo = Foo {
    foo: "foobar".to_owned(),
};

// Evalute the document with the rule.
assert_eq!(rule.matches(&foo), true);

Features

The following are a list of features that can be enabled or disabled:

core: Exposes some of Tau Engine’s internals.
ignore_case: Force the engine to always be case insensitive, this will ignore the i prefix and for that reason is not compatible with case sensitive rules.
json: Enable serde json support, this will allow the tau-engine to solve on serde_json::Value.

JSON

When JSON support is enabled for the tau-engine, the result is a solver that can now reason over any document that can be deserialized into serde_json::Value.

use tau_engine::{Document, Rule};

// Write a rule.
let rule = r#"
detection:
  A:
    foo: foobar
  condition: A
true_positives:
- foo: foobar
true_negatives:
- foo: foo
"#;

// Load and validate a rule.
let rule = Rule::load(rule).unwrap();
assert_eq!(rule.validate().unwrap(), true);

// Create a document.
let foo = json!({
    "foo": "foobar",
});

// Evalute the document with the rule.
assert_eq!(rule.matches(&foo), true);