python: move log injection out of experimental

- move from custom concept `LogOutput` to standard concept `Logging`
- remove `Log.qll` from experimental frameworks
  - fold models into standard models (naively for now)
    - stdlib:
      - make Logger module public
      - broaden definition of instance
      - add `extra` keyword as possible source
   - flak: add app.logger as logger instance
   - django: `add django.utils.log.request_logger` as logger instance
     (should we add the rest?)
- remove LogOutput from experimental concepts

python/ql/lib/semmle/python/security/dataflow/LogInjection.qll

@@ -0,0 +1,24 @@
+import python
+import semmle.python.Concepts
+import semmle.python.Concepts
+import semmle.python.dataflow.new.DataFlow
+import semmle.python.dataflow.new.TaintTracking
+import semmle.python.dataflow.new.RemoteFlowSources
+
+/**
+ * A taint-tracking configuration for tracking untrusted user input used in log entries.
+ */
+class LogInjectionFlowConfig extends TaintTracking::Configuration {
+  LogInjectionFlowConfig() { this = "LogInjectionFlowConfig" }
+
+  override predicate isSource(DataFlow::Node source) { source instanceof RemoteFlowSource }
+
+  override predicate isSink(DataFlow::Node sink) { sink = any(Logging write).getAnInput() }
+
+  override predicate isSanitizer(DataFlow::Node node) {
+    exists(CallNode call |
+      node.asCfgNode() = call.getFunction().(AttrNode).getObject("replace") and
+      call.getArg(0).getNode().(StrConst).getText() in ["\r\n", "\n"]
+    )
+  }
+}