diff --git a/SECURITY.md b/SECURITY.md
index 87a16f17538..ac3a97e7f63 100644
--- a/SECURITY.md
+++ b/SECURITY.md
@@ -229,10 +229,10 @@ and [the Google OSS VRP
 rules](https://bughunters.google.com/about/rules/6521337925468160/google-open-source-software-vulnerability-reward-program-rules)).
 
 **Note**: Although the iterative exploration of TF API via fuzzing
-`tf.raw_ops.xxx` symbols is the best way to uncover code weakeness, please bear
-in mind that this is not a typical usecase that has security implications. It is
+`tf.raw_ops.xxx` symbols is the best way to uncover code weakness, please bear
+in mind that this is not a typical use case that has security implications. It is
 better to try to translate the vulnerability to something that can be exploited
-during training or inference of a model (i.e., build a model that when given a
+during training or inference of a model (i.e., build a model tha when given a
 specific input would produce unwanted behavior). Alternatively, if the
 TensorFlow API is only used in ancillary tooling, consider the environment where
 the tool would run. For example, if `saved_model_cli` tool would crash on
@@ -254,7 +254,7 @@ In addition, please include the following information along with your report:
 *   Your name and affiliation (if any).
 *   A description of the technical details of the vulnerabilities. It is very
     important to let us know how we can reproduce your findings.
-*   A minimal example of the vulnerabity.
+*   A minimal example of the vulnerability.
 *   An explanation of who can exploit this vulnerability, and what they gain
     when doing so -- write an attack scenario. This will help us evaluate your
     report quickly, especially if the issue is complex.