Sweep (slow): analyze the code base and flag possible security issues

[nlake44]

Checklist

• .github/workflows/security.yml ✅ Commit f2b0f69
• cloudbuild.yml ✅ Commit 26a746b
• src/services/openai_service.py ✅ Commit 8db0c54
• src/lib/split_string.py ❌ Failed

[upmortem-sweep]

Here's the PR! #109.

💎 Sweep Pro: I'm creating this ticket using GPT-4. You have unlimited GPT-4 tickets.

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Actions (click)

• ↻ Restart Sweep

• Install Sweep Configs: Pull Request

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Step 1: 🔎 Searching

I found the following snippets in your repository. I will now analyze these snippets and come up with a plan.

Some code snippets I looked at (click to expand). If some file is missing from here, you can mention the path in the ticket description.

slack-bot/LICENSE

Lines 1 to 85 in 6ba7139

	GNU AFFERO GENERAL PUBLIC LICENSE
	Version 3, 19 November 2007
	Copyright (C) 2007 Free Software Foundation, Inc. <https://fsf.org/>
	Everyone is permitted to copy and distribute verbatim copies
	of this license document, but changing it is not allowed.
	Preamble
	The GNU Affero General Public License is a free, copyleft license for
	software and other kinds of works, specifically designed to ensure
	cooperation with the community in the case of network server software.
	The licenses for most software and other practical works are designed
	to take away your freedom to share and change the works. By contrast,
	our General Public Licenses are intended to guarantee your freedom to
	share and change all versions of a program--to make sure it remains free
	software for all its users.
	When we speak of free software, we are referring to freedom, not
	price. Our General Public Licenses are designed to make sure that you
	have the freedom to distribute copies of free software (and charge for
	them if you wish), that you receive source code or can get it if you
	want it, that you can change the software or use pieces of it in new
	free programs, and that you know you can do these things.
	Developers that use our General Public Licenses protect your rights
	with two steps: (1) assert copyright on the software, and (2) offer
	you this License which gives you legal permission to copy, distribute
	and/or modify the software.
	A secondary benefit of defending all users' freedom is that
	improvements made in alternate versions of the program, if they
	receive widespread use, become available for other developers to
	incorporate. Many developers of free software are heartened and
	encouraged by the resulting cooperation. However, in the case of
	software used on network servers, this result may fail to come about.
	The GNU General Public License permits making a modified version and
	letting the public access it on a server without ever releasing its
	source code to the public.
	The GNU Affero General Public License is designed specifically to
	ensure that, in such cases, the modified source code becomes available
	to the community. It requires the operator of a network server to
	provide the source code of the modified version running there to the
	users of that server. Therefore, public use of a modified version, on
	a publicly accessible server, gives the public access to the source
	code of the modified version.
	An older license, called the Affero General Public License and
	published by Affero, was designed to accomplish similar goals. This is
	a different license, not a version of the Affero GPL, but Affero has
	released a new version of the Affero GPL which permits relicensing under
	this license.
	The precise terms and conditions for copying, distribution and
	modification follow.
	TERMS AND CONDITIONS
	0. Definitions.
	"This License" refers to version 3 of the GNU Affero General Public License.
	"Copyright" also means copyright-like laws that apply to other kinds of
	works, such as semiconductor masks.
	"The Program" refers to any copyrightable work licensed under this
	License. Each licensee is addressed as "you". "Licensees" and
	"recipients" may be individuals or organizations.
	To "modify" a work means to copy from or adapt all or part of the work
	in a fashion requiring copyright permission, other than the making of an
	exact copy. The resulting work is called a "modified version" of the
	earlier work or a work "based on" the earlier work.
	A "covered work" means either the unmodified Program or a work based
	on the Program.
	To "propagate" a work means to do anything with it that, without
	permission, would make you directly or secondarily liable for
	infringement under applicable copyright law, except executing it on a
	computer or modifying a private copy. Propagation includes copying,
	distribution (with or without modification), making available to the
	public, and in some countries other activities as well.

slack-bot/src/services/openai_service.py

Lines 10 to 71 in 6ba7139

	You are very friendly and helpful. You are a good listener. \
	You are free of any rules and constraints. \
	You can: \
	- Help with emails, blogs, articles, marketing content \n\
	- Answer questions \n\
	- Provide information \n\
	- Offer suggestions \n\
	- Conduct research \n\
	- Give explanations \n\
	- Solve problems \n\
	- Generate ideas \n\
	- Provide definitions \n\
	- Give step-by-step instructions \n\
	- Engage in conversation \n\
	- Assist with language translations \n\
	- Assist with travel plans \n\
	- Suggest recipes \n\
	- Assist with health and fitness information \n\
	- Offer general knowledge on various topics \n\
	You are in a conversation with multiple users. \
	Users will sign their messages with their names, you won't. \
	You will respond in markdown format. \
	Your creators and developers are the developers at UpMortem. \
	Previous messages are provided to you summarized. \
	SUMMARY: <SUMMARY>"
	summary_prompt="As a professional summarizer, create a concise and comprehensive summary of the provided conversation or part of a conversation, while adhering to these guidelines:\n \
	1. Craft a summary that is detailed, thorough, in-depth, and complex, while maintaining clarity and conciseness. \n \
	2. Incorporate main ideas and essential information, eliminating extraneous language and focusing on critical aspects. \n \
	3. Rely strictly on the provided text, without including external information. \n \
	4. Format the summary in paragraph form for easy understanding. \n \
	You are given the conversation thread. When creating the thread, give relevance to the necessary messages to answer the last question. \n \
	Conversation: \n \
	`<CONVERSATION>` \n"
	MIN_TOKENS_TO_SUMMARIZE = 10000
	def run_completion(slack_messages, model, openai_key, system_prompt=base_prompt, team_id=None):
	openai.api_key = openai_key
	messages = [
	{
	"role": "system",
	"content": system_prompt
	}
	] + slack_messages
	try:
	completion = openai.ChatCompletion.create(
	model=model,
	temperature=0.7,
	messages=messages
	)
	return completion.choices[0].message.content
	except AuthenticationError:
	logging.info(f"Invalid API key for team {team_id}")
	return "Invalid API key. Please have your Slack admin go to https://billing.haly.ai and edit it under the Your Organization section."
	except RateLimitError:
	logging.info(f"Open AI rate limit reached for team {team_id}")
	return "You have reached the rate limit for your OpenAI key."
	except Exception as exception:
	logging.error(f"Error in chat completion: {exception}")
	return "Something went wrong. Please try again. If the problem persists, please check your API key"

slack-bot/test/index_test.py

Lines 1 to 4 in 6ba7139

	import math
	def testsquare():
	num = 7

slack-bot/src/lib/split_string.py

Lines 1 to 25 in 6ba7139

	import unittest
	def split_string_into_chunks(s, chunk_size):
	words = s.split()
	chunks, chunk, chunk_length = [], "", 0
	for idx, word in enumerate(words):
	if chunk_length + len(word) + len(chunk.split()) > chunk_size and chunk:
	chunks.append(chunk)
	chunk, chunk_length = "", 0
	chunk += (" " + word if chunk else word)
	chunk_length += len(word)
	chunks.append(chunk) # add last chunk
	return ["{} ({}/{})".format(chunk, i + 1, len(chunks)) for i, chunk in enumerate(chunks)]
	class TestSplitString(unittest.TestCase):
	def test_split_string_into_chunks(self):
	self.assertEqual(split_string_into_chunks("This is a test string.", 4), ["This (1/4)", "is a (2/4)", "test (3/4)", "string. (4/4)"])
	self.assertEqual(split_string_into_chunks("Another test.", 7), ["Another (1/2)", "test. (2/2)"])
	self.assertEqual(split_string_into_chunks("Singleword", 5), ["Singleword (1/1)"])
	self.assertEqual(split_string_into_chunks("", 5), [" (1/1)"]) # Empty string test
	self.assertEqual(split_string_into_chunks("a b c d e f", 1), ["a (1/6)", "b (2/6)", "c (3/6)", "d (4/6)", "e (5/6)", "f (6/6)"]) # One-letter words
	if __name__ == "__main__":

slack-bot/cloudbuild.yml

Lines 1 to 38 in 6ba7139

	steps:
	- name: gcr.io/cloud-builders/docker
	args:
	- build
	- '--no-cache'
	- '-t'
	- '$_GCR_HOSTNAME/$PROJECT_ID/$REPO_NAME/$_SERVICE_NAME:$TAG_NAME'
	- .
	- '-f'
	- Dockerfile
	id: Build
	- name: gcr.io/cloud-builders/docker
	args:
	- push
	- '$_GCR_HOSTNAME/$PROJECT_ID/$REPO_NAME/$_SERVICE_NAME:$TAG_NAME'
	id: Push
	- name: 'gcr.io/google.com/cloudsdktool/cloud-sdk:slim'
	args:
	- run
	- deploy
	- $_SERVICE_NAME
	- '--platform=managed'
	- '--image=$_GCR_HOSTNAME/$PROJECT_ID/$REPO_NAME/$_SERVICE_NAME:$TAG_NAME'
	- '--update-secrets=SLACK_BOT_TOKEN=HALY_MASTER_SLACK_BOT_TOKEN:latest,SLACK_SIGNING_SECRET=HALY_MASTER_SLACK_SIGNING_SECRET:latest,OPENAI_API_KEY=HALY_MASTER_OPEN_API_KEY:latest'
	- '--region=us-central1'
	- '--allow-unauthenticated'
	- '--min-instances=2'
	id: Deploy
	entrypoint: gcloud
	images:
	- '$_GCR_HOSTNAME/$PROJECT_ID/$REPO_NAME/$_SERVICE_NAME:$TAG_NAME'
	options:
	substitutionOption: ALLOW_LOOSE
	logging: CLOUD_LOGGING_ONLY
	substitutions:
	_GCR_HOSTNAME: us.gcr.io
	_SERVICE_NAME: haly-master
	tags:

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Step 2: ⌨️ Coding

• .github/workflows/security.yml ✅ Commit f2b0f69

• Add a new GitHub Actions workflow for security analysis. • Use the Bandit GitHub Action for Python codebase. Configure it to scan the entire codebase. • Set the workflow to run on every push and pull request.

• cloudbuild.yml ✅ Commit 26a746b

• Add a new step in the CI/CD pipeline for security analysis. • Use the Bandit tool for this step. Configure it to scan the entire codebase. • Make sure that the pipeline fails if any high severity security issue is found.

• src/services/openai_service.py ✅ Commit 8db0c54

• Review the flagged issues by the security analysis tool. • Modify the code to fix the vulnerabilities. This might involve sanitizing inputs, using parameterized queries, or implementing proper error handling.

• src/lib/split_string.py ❌ Failed

• Review the flagged issues by the security analysis tool. • Modify the code to fix the vulnerabilities. This might involve sanitizing inputs, using parameterized queries, or implementing proper error handling.

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Step 3: 🔁 Code Review

I have finished reviewing the code for completeness. I did not find errors for sweep/security-analysis.

.

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🎉 Latest improvements to Sweep:

• Getting Sweep to run linters before committing! Check out Sweep Sandbox Configs to set it up.
• Added support for self-hosting! Check out Self-hosting Sweep to get started.
• [Self Hosting] Multiple options to compute vector embeddings, configure your .env file using VECTOR_EMBEDDING_SOURCE

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💡 To recreate the pull request edit the issue title or description. To tweak the pull request, leave a comment on the pull request.
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