Update overview.md (#1080)

Minor spelling correction in the second sentence of the second paragraph.

docs/prompt_hacking/defensive_measures/overview.md

@@ -7,4 +7,4 @@ sidebar_position: 0
 Preventing prompt injection can be extremely difficult, and there exist few robust defenses against it(@crothers2022machine)(@goodside2021gpt). However, there are some commonsense
 solutions. For example, if your application does not need to output free-form text, do not allow such outputs. There are many different ways to defend a prompt. We will discuss some of the most common ones here.
 
-This chapter covers additional commonsense strategies like filtering out words. It also cover prompt improvement strategies (instruction defense, post-prompting, different ways to enclose user input, and XML tagging). Finally, we discuss using an LLM to evaluate output and some more model specific approaches. 
+This chapter covers additional commonsense strategies like filtering out words. It also covers prompt improvement strategies (instruction defense, post-prompting, different ways to enclose user input, and XML tagging). Finally, we discuss using an LLM to evaluate output and some more model specific approaches.