Merge pull request #2514 from python-discord/fix_filters

Use the right variables in antispam

6 files changed, 6 insertions, 6 deletions

diff --git a/bot/exts/filtering/_filters/antispam/chars.py b/bot/exts/filtering/_filters/antispam/chars.py
index 5c4fa201c..1b28b781c 100644
--- a/bot/exts/filtering/_filters/antispam/chars.py
+++ b/bot/exts/filtering/_filters/antispam/chars.py
@@ -34,7 +34,7 @@ class CharsFilter(UniqueFilter):
         relevant_messages = list(takewhile(lambda msg: msg.created_at > earliest_relevant_at, ctx.content))
 
         detected_messages = {msg for msg in relevant_messages if msg.author == ctx.author}
-        total_recent_chars = sum(len(msg.content) for msg in relevant_messages)
+        total_recent_chars = sum(len(msg.content) for msg in detected_messages)
 
         if total_recent_chars > self.extra_fields.threshold:
             ctx.related_messages |= detected_messages
diff --git a/bot/exts/filtering/_filters/antispam/emoji.py b/bot/exts/filtering/_filters/antispam/emoji.py
index 0511e4a7b..b3bc63c1d 100644
--- a/bot/exts/filtering/_filters/antispam/emoji.py
+++ b/bot/exts/filtering/_filters/antispam/emoji.py
@@ -43,7 +43,7 @@ class EmojiFilter(UniqueFilter):
         # Convert Unicode emojis to :emoji: format to get their count.
         total_emojis = sum(
             len(DISCORD_EMOJI_RE.findall(demojize(CODE_BLOCK_RE.sub("", msg.content))))
-            for msg in relevant_messages
+            for msg in detected_messages
         )
 
         if total_emojis > self.extra_fields.threshold:
diff --git a/bot/exts/filtering/_filters/antispam/links.py b/bot/exts/filtering/_filters/antispam/links.py
index 76fe53e70..ca6e9d031 100644
--- a/bot/exts/filtering/_filters/antispam/links.py
+++ b/bot/exts/filtering/_filters/antispam/links.py
@@ -39,7 +39,7 @@ class DuplicatesFilter(UniqueFilter):
 
         total_links = 0
         messages_with_links = 0
-        for msg in relevant_messages:
+        for msg in detected_messages:
             total_matches = len(LINK_RE.findall(msg.content))
             if total_matches:
                 messages_with_links += 1
diff --git a/bot/exts/filtering/_filters/antispam/mentions.py b/bot/exts/filtering/_filters/antispam/mentions.py
index f3c945e16..eb5a5e41b 100644
--- a/bot/exts/filtering/_filters/antispam/mentions.py
+++ b/bot/exts/filtering/_filters/antispam/mentions.py
@@ -55,7 +55,7 @@ class DuplicatesFilter(UniqueFilter):
         # We would need to deal with codeblocks, escaping markdown, and any discrepancies between
         # our implementation and discord's Markdown parser which would cause false positives or false negatives.
         total_recent_mentions = 0
-        for msg in relevant_messages:
+        for msg in detected_messages:
             # We check if the message is a reply, and if it is try to get the author
             # since we ignore mentions of a user that we're replying to
             reply_author = None
diff --git a/bot/exts/filtering/_filters/antispam/newlines.py b/bot/exts/filtering/_filters/antispam/newlines.py
index b15a35219..f3830fdd7 100644
--- a/bot/exts/filtering/_filters/antispam/newlines.py
+++ b/bot/exts/filtering/_filters/antispam/newlines.py
@@ -43,7 +43,7 @@ class NewlinesFilter(UniqueFilter):
 
         # Identify groups of newline characters and get group & total counts
         newline_counts = []
-        for msg in relevant_messages:
+        for msg in detected_messages:
             newline_counts += [len(group) for group in NEWLINES.findall(msg.content)]
         total_recent_newlines = sum(newline_counts)
         # Get maximum newline group size
diff --git a/bot/exts/filtering/_filters/antispam/role_mentions.py b/bot/exts/filtering/_filters/antispam/role_mentions.py
index 49de642fa..151dc49be 100644
--- a/bot/exts/filtering/_filters/antispam/role_mentions.py
+++ b/bot/exts/filtering/_filters/antispam/role_mentions.py
@@ -33,7 +33,7 @@ class DuplicatesFilter(UniqueFilter):
         earliest_relevant_at = arrow.utcnow() - timedelta(seconds=self.extra_fields.interval)
         relevant_messages = list(takewhile(lambda msg: msg.created_at > earliest_relevant_at, ctx.content))
         detected_messages = {msg for msg in relevant_messages if msg.author == ctx.author}
-        total_recent_mentions = sum(len(msg.role_mentions) for msg in relevant_messages)
+        total_recent_mentions = sum(len(msg.role_mentions) for msg in detected_messages)
 
         if total_recent_mentions > self.extra_fields.threshold:
             ctx.related_messages |= detected_messages