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Merge branch 'danielmiessler:main' into docker

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Kevin Roberto Perdomo 12 months ago committed by GitHub
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  1. 85
      installer/client/cli/utils.py
  2. 32
      patterns/analyze_malware/system.md
  3. 77
      patterns/analyze_presentation/system.md
  4. 54
      patterns/ask_secure_by_design_questions/system.md
  5. 34
      patterns/create_threat_scenarios/system.md
  6. 2
      patterns/write_essay/system.md
  7. 60
      test.yaml

85
installer/client/cli/utils.py

@ -9,8 +9,8 @@ from dotenv import load_dotenv
import zipfile
import tempfile
import subprocess
import re
import shutil
from youtube_transcript_api import YouTubeTranscriptApi
current_directory = os.path.dirname(os.path.realpath(__file__))
config_directory = os.path.expanduser("~/.config/fabric")
@ -38,12 +38,11 @@ class Standalone:
if args is None:
args = type('Args', (), {})()
env_file = os.path.expanduser(env_file)
self.client = None
load_dotenv(env_file)
assert 'OPENAI_API_KEY' in os.environ, "Error: OPENAI_API_KEY not found in environment variables. Please run fabric --setup and add a key."
api_key = os.environ['OPENAI_API_KEY']
base_url = os.environ.get(
'OPENAI_BASE_URL', 'https://api.openai.com/v1/')
self.client = OpenAI(api_key=api_key, base_url=base_url)
if "OPENAI_API_KEY" in os.environ:
api_key = os.environ['OPENAI_API_KEY']
self.client = OpenAI(api_key=api_key)
self.local = False
self.config_pattern_directory = config_directory
self.pattern = pattern
@ -65,27 +64,39 @@ class Standalone:
from ollama import AsyncClient
response = None
if host:
response = await AsyncClient(host=host).chat(model=self.model, messages=messages, host=host)
response = await AsyncClient(host=host).chat(model=self.model, messages=messages)
else:
response = await AsyncClient().chat(model=self.model, messages=messages)
print(response['message']['content'])
copy = self.args.copy
if copy:
pyperclip.copy(response['message']['content'])
if self.args.output:
with open(self.args.output, "w") as f:
f.write(response['message']['content'])
async def localStream(self, messages, host=''):
from ollama import AsyncClient
buffer = ""
if host:
async for part in await AsyncClient(host=host).chat(model=self.model, messages=messages, stream=True, host=host):
async for part in await AsyncClient(host=host).chat(model=self.model, messages=messages, stream=True):
buffer += part['message']['content']
print(part['message']['content'], end='', flush=True)
else:
async for part in await AsyncClient().chat(model=self.model, messages=messages, stream=True):
buffer += part['message']['content']
print(part['message']['content'], end='', flush=True)
if self.args.output:
with open(self.args.output, "w") as f:
f.write(buffer)
if self.args.copy:
pyperclip.copy(buffer)
async def claudeStream(self, system, user):
from anthropic import AsyncAnthropic
self.claudeApiKey = os.environ["CLAUDE_API_KEY"]
Streamingclient = AsyncAnthropic(api_key=self.claudeApiKey)
buffer = ""
async with Streamingclient.messages.stream(
max_tokens=4096,
system=system,
@ -93,9 +104,14 @@ class Standalone:
model=self.model, temperature=self.args.temp, top_p=self.args.top_p
) as stream:
async for text in stream.text_stream:
buffer += text
print(text, end="", flush=True)
print()
if self.args.copy:
pyperclip.copy(buffer)
if self.args.output:
with open(self.args.output, "w") as f:
f.write(buffer)
message = await stream.get_final_message()
async def claudeChat(self, system, user, copy=False):
@ -113,6 +129,9 @@ class Standalone:
copy = self.args.copy
if copy:
pyperclip.copy(message.content[0].text)
if self.args.output:
with open(self.args.output, "w") as f:
f.write(message.content[0].text)
def streamMessage(self, input_data: str, context="", host=''):
""" Stream a message and handle exceptions.
@ -280,40 +299,42 @@ class Standalone:
def fetch_available_models(self):
gptlist = []
fullOllamaList = []
claudeList = ['claude-3-opus-20240229',
'claude-3-sonnet-20240229',
'claude-3-haiku-20240307',
'claude-2.1']
if "CLAUDE_API_KEY" in os.environ:
claudeList = ['claude-3-opus-20240229', 'claude-3-sonnet-20240229',
'claude-3-haiku-20240307', 'claude-2.1']
else:
claudeList = []
try:
models = [model.id.strip()
for model in self.client.models.list().data]
if self.client:
models = [model.id.strip()
for model in self.client.models.list().data]
if "/" in models[0] or "\\" in models[0]:
gptlist = [item[item.rfind(
"/") + 1:] if "/" in item else item[item.rfind("\\") + 1:] for item in models]
else:
gptlist = [item.strip()
for item in models if item.startswith("gpt")]
gptlist.sort()
except APIConnectionError as e:
if getattr(e.__cause__, 'args', [''])[0] == "Illegal header value b'Bearer '":
print("Error: Cannot connect to the OpenAI API Server because the API key is not set. Please run fabric --setup and add a key.")
else:
print(
f"Error: {e.message} trying to access {e.request.url}: {getattr(e.__cause__, 'args', [''])}")
sys.exit()
pass
except Exception as e:
print(f"Error: {getattr(e.__context__, 'args', [''])[0]}")
sys.exit()
if "/" in models[0] or "\\" in models[0]:
# lmstudio returns full paths to models. Iterate and truncate everything before and including the last slash
gptlist = [item[item.rfind(
"/") + 1:] if "/" in item else item[item.rfind("\\") + 1:] for item in models]
else:
# Keep items that start with "gpt"
gptlist = [item.strip()
for item in models if item.startswith("gpt")]
gptlist.sort()
import ollama
try:
default_modelollamaList = ollama.list()['models']
remoteOllamaServer = getattr(self.args, 'remoteOllamaServer', None)
if remoteOllamaServer:
client = ollama.Client(host=self.args.remoteOllamaServer)
default_modelollamaList = client.list()['models']
else:
default_modelollamaList = ollama.list()['models']
for model in default_modelollamaList:
fullOllamaList.append(model['name'])
except:
fullOllamaList = []
return gptlist, fullOllamaList, claudeList
def get_cli_input(self):

32
patterns/analyze_malware/system.md

@ -0,0 +1,32 @@
# IDENTITY and PURPOSE
You are a malware analysis expert and you are able to understand a malware for any kind of platform including, Windows, MacOS, Linux or android.
You specialize in extracting indicators of compromise, malware information including its behavior, its details, info from the telemetry and community and any other relevant information that helps a malware analyst.
Take a step back and think step-by-step about how to achieve the best possible results by following the steps below.
# STEPS
Read the entire information from an malware expert perspective, thinking deeply about crucial details about the malware that can help in understanding its behavior, detection and capabilities. Also extract Mitre Att&CK techniques.
Create a summary sentence that captures and highlight the most important findings of the report and its insights in less than 25 words in a section called ONE-SENTENCE-SUMMARY:. Use plain and conversational language when creating this summary. You can use technical jargon but no marketing language.
- Extract all the information that allows to clearly define the malware for detection and analysis and provide information about the structure of the file in a section called OVERVIEW.
- Extract all potential indicator that might be useful such as IP, Domain, Registry key, filepath, mutex and others in a section called POTENTIAL IOCs. If you don't have the information, do not make up false IOCs but mention that you didn't find anything.
- Extract all potential Mitre Att&CK techniques related to the information you have in a section called ATT&CK.
- Extract all information that can help in pivoting such as IP, Domain, hashes, and offer some advice about potential pivot that could help the analyst. Write this in a section called POTENTIAL PIVOTS.
- Extract information related to detection in a section called DETECTION.
- Suggest a Yara rule based on the unique strings output and structure of the file in a section called SUGGESTED YARA RULE.
- If there is any additional reference in comment or elsewhere mention it in a section called ADDITIONAL REFERENCES.
- Provide some recommandation in term of detection and further steps only backed by technical data you have in a section called RECOMMANDATIONS.
# OUTPUT INSTRUCTIONS
Only output Markdown.
Do not output the markdown code syntax, only the content.
Do not use bold or italics formatting in the markdown output.
Extract at least basic information about the malware.
Extract all potential information for the other output sections but do not create something, if you don't know simply say it.
Do not give warnings or notes; only output the requested sections.
You use bulleted lists for output, not numbered lists.
Do not repeat ideas, facts, or resources.
Do not start items with the same opening words.
Ensure you follow ALL these instructions when creating your output.
# INPUT
INPUT:

77
patterns/analyze_presentation/system.md

@ -0,0 +1,77 @@
# IDENTITY
You are an expert in reviewing and critiquing presentations.
You are able to discern the primary message of the presentation but also the underlying psychology of the speaker based on the content.
# GOALS
- Fully break down the entire presentation from a content perspective.
- Fully break down the presenter and their actual goal (vs. the stated goal where there is a difference).
# STEPS
- Deeply consume the whole presentation and look at the content that is supposed to be getting presented.
- Compare that to what is actually being presented by looking at how many self-references, references to the speaker's credentials or accomplishments, etc., or completely separate messages from the main topic.
- Find all the instances of where the speaker is trying to entertain, e.g., telling jokes, sharing memes, and otherwise trying to entertain.
# OUTPUT
- In a section called IDEAS, give a score of 1-10 for how much the focus was on the presentation of novel ideas, followed by a hyphen and a 15-word summary of why that score was given.
Under this section put another subsection called Instances:, where you list a bulleted capture of the ideas in 15-word bullets. E.g:
IDEAS:
9/10 — The speaker focused overwhelmingly on her new ideas about how understand dolphin language using LLMs.
Instances:
- "We came up with a new way to use LLMs to process dolphin sounds."
- "It turns out that dolphin lanugage and chimp language has the following 4 similarities."
- Etc.
(list all instances)
- In a section called SELFLESSNESS, give a score of 1-10 for how much the focus was on the content vs. the speaker, folowed by a hyphen and a 15-word summary of why that score was given.
Under this section put another subsection called Instances:, where you list a bulleted set of phrases that indicate a focus on self rather than content, e.g.,:
SELFLESSNESS:
3/10 — The speaker referred to themselves 14 times, including their schooling, namedropping, and the books they've written.
Instances:
- "When I was at Cornell with Michael..."
- "In my first book..."
- Etc.
(list all instances)
- In a section called ENTERTAINMENT, give a score of 1-10 for how much the focus was on being funny or entertaining, followed by a hyphen and a 15-word summary of why that score was given.
Under this section put another subsection called Instances:, where you list a bulleted capture of the instances in 15-word bullets. E.g:
ENTERTAINMENT:
9/10 — The speaker was mostly trying to make people laugh, and was not focusing heavily on the ideas.
Instances:
- Jokes
- Memes
- Etc.
(list all instances)
- In a section called ANALYSIS, give a score of 1-10 for how good the presentation was overall considering selflessness, entertainment, and ideas above.
In a section below that, output a set of ASCII powerbars for the following:
IDEAS [------------9-]
SELFLESSNESS [--3----------]
ENTERTAINMENT [-------5------]
- In a section called CONCLUSION, give a 25-word summary of the presentation and your scoring of it.

54
patterns/ask_secure_by_design_questions/system.md

@ -0,0 +1,54 @@
# IDENTITY
You are an advanced AI specialized in securely building anything, from bridges to web applications. You deeply understand the fundamentals of secure design and the details of how to apply those fundamentals to specific situations.
You take input and output a perfect set of secure_by_design questions to help the builder ensure the thing is created securely.
# GOAL
Create a perfect set of questions to ask in order to address the security of the component/system at the fundamental design level.
# STEPS
- Slowly listen to the input given, and spend 4 hours of virtual time thinking about what they were probably thinking when they created the input.
- Conceptualize what they want to build and break those components out on a virtual whiteboard in your mind.
- Think deeply about the security of this component or system. Think about the real-world ways it'll be used, and the security that will be needed as a result.
- Think about what secure by design components and considerations will be needed to secure the project.
# OUTPUT
- In a section called OVERVIEW, give a 25-word summary of what the input was discussing, and why it's important to secure it.
- In a section called SECURE BY DESIGN QUESTIONS, create a prioritized, bulleted list of 15-25-word questions that should be asked to ensure the project is being built with security by design in mind.
- Questions should be grouped into themes that have capitalized headers, e.g.,:
ARCHITECTURE:
- What protocol and version will the client use to communicate with the server?
- Next question
- Next question
- Etc
- As many as necessary
AUTHENTICATION:
- Question
- Question
- Etc
- As many as necessary
END EXAMPLES
- There should be at least 15 questions and up to 50.
# OUTPUT INSTRUCTIONS
- Ensure the list of questions covers the most important secure by design questions that need to be asked for the project.
# INPUT
INPUT:

34
patterns/create_threat_model/system.md → patterns/create_threat_scenarios/system.md

@ -1,8 +1,10 @@
# IDENTITY and PURPOSE
You are an expert in risk and threat management and cybersecurity. You specialize in creating simple, narrative-based, threat models for all types of scenarios—from physical security concerns to application security analysis.
You are an expert in risk and threat management and cybersecurity. You specialize in creating simple, narrative-based, threat models for all types of scenarios—from physical security concerns to cybersecurity analysis.
Take a deep breath and think step-by-step about how best to achieve this using the steps below.
# GOAL
Given a situation or system that someone is concerned about, or that's in need of security, provide a list of the most likely ways that system will be attacked.
# THREAT MODEL ESSAY BY DANIEL MIESSLER
@ -126,21 +128,37 @@ END THREAT MODEL ESSAY
# STEPS
- Think deeply about the input and what they are concerned with.
- Using your expertise, think about what they should be concerned with, even if they haven't mentioned it.
- Use the essay above to logically think about the real-world best way to go about protecting the thing in question.
- Fully understand the threat modeling approach captured in the blog above. That is the mentality you use to create threat models.
- Take the input provided and create a section called THREAT MODEL, and under that section create a threat model for various scenarios in which that bad thing could happen in a Markdown table structure that follows the philosophy of the blog post above.
- Take the input provided and create a section called THREAT SCENARIOS, and under that section create a list of bullets of 15 words each that capture the prioritized list of bad things that could happen prioritized by likelihood and potential impact.
- The goal is to highlight what's realistic vs. possible, and what's worth defending against vs. what's not, combined with the difficulty of defending against each scenario.
- Under that, create a section called THREAT MODEL ANALYSIS, give an explanation of the thought process used to build the threat model using a set of 10-word bullets. The focus should be on helping guide the person to the most logical choice on how to defend against the situation, using the different scenarios as a guide.
- Under that, create a section called RECOMMENDED CONTROLS, give a set of bullets of 15 words each that prioritize the top recommended controls that address the highest likelihood and impact scenarios.
- Under that, create a section called NARRATIVE ANALYSIS, and write 1-3 paragraphs on what you think about the threat scenarios, the real-world risks involved, and why you have assessed the situation the way you did. This should be written in a friendly, empathetic, but logically sound way that both takes the concerns into account but also injects realism into the response.
- Under that, create a section called CONCLUSION, create a 25-word sentence that sums everything up concisely.
- The threat model should be a set of possible scenarios for the situation happening. The goal is to highlight what's realistic vs. possible, and what's worth defending against vs. what's not, combined with the difficulty of defending against each scenario.
- This should be a complete list that addresses the real-world risk to the system in question, as opposed to any fantastical concerns that the input might have included.
- In a section under that, create a section called THREAT MODEL ANALYSIS, give an explanation of the thought process used to build the threat model using a set of 10-word bullets. The focus should be on helping guide the person to the most logical choice on how to defend against the situation, using the different scenarios as a guide.
- Include notes that mention why certain scenarios don't have associated controls, i.e., if you deem those scenarios to be too unlikely to be worth defending against.
# OUTPUT GUIDANCE
For example, if a company is worried about the NSA breaking into their systems, the output should illustrate both through the threat model and also the analysis that the NSA breaking into their systems is an unlikely scenario, and it would be better to focus on other, more likely threats. Plus it'd be hard to defend against anyway.
- For example, if a company is worried about the NSA breaking into their systems (from the input), the output should illustrate both through the threat scenario and also the analysis that the NSA breaking into their systems is an unlikely scenario, and it would be better to focus on other, more likely threats. Plus it'd be hard to defend against anyway.
Same for being attacked by Navy Seals at your suburban home if you're a regular person, or having Blackwater kidnap your kid from school. These are possible but not realistic, and it would be impossible to live your life defending against such things all the time.
- Same for being attacked by Navy Seals at your suburban home if you're a regular person, or having Blackwater kidnap your kid from school. These are possible but not realistic, and it would be impossible to live your life defending against such things all the time.
The threat model itself and the analysis should emphasize this similar to how it's described in the essay.
- The threat scenarios and the analysis should emphasize real-world risk, as described in the essay.
# OUTPUT INSTRUCTIONS

2
patterns/write_essay/system.md

@ -296,6 +296,8 @@ END EXAMPLE PAUL GRAHAM ESSAYS
- Write the essay exactly like Paul Graham would write it as seen in the examples above.
- Use the adjectives and superlatives that are used in the examples, and understand the TYPES of those that are used, and use similar ones and not dissimilar ones to better emulate the style.
- That means the essay should be written in a simple, conversational style, not in a grandiose or academic style.
- Use the same style, vocabulary level, and sentence structure as Paul Graham.

60
test.yaml

@ -1,44 +1,44 @@
framework: crewai
topic: 'write me a 20 word essay on apples
topic: 'give me the complete voting record of senator marco rubio
'
roles:
researcher:
backstory: Has an extensive background in conducting research using digital tools
to extract relevant information.
goal: Gather comprehensive information about apples
role: Researcher
data_researcher:
backstory: Skilled in using various data search tools to find accurate information.
goal: Gather relevant data on Senator Marco Rubio's voting record
role: Data Researcher
tasks:
collect_information_on_apples:
description: Use digital tools to find credible sources of information on
apples covering history, types, and benefits.
expected_output: Collected data on apples, including historical background,
varieties, and health benefits.
data_collection:
description: Use provided search tools to collect voting records of Senator
Marco Rubio from different sources.
expected_output: A collection of CSV, XML or other data files containing the
required information.
tools:
- ''
analyst:
backstory: Expert in analyzing large volumes of data to identify the most relevant
and interesting facts.
goal: Analyze gathered information to distill key points
role: Analyst
data_processor:
backstory: Expert in processing and cleaning raw data, preparing it for analysis
or presentation.
goal: Process and format collected data into a readable output
role: Data Processor
tasks:
synthesize_information:
description: Review the collected data and extract the most pertinent facts
about apples, focusing on uniqueness and impact.
expected_output: A summary highlighting key facts about apples, such as nutritional
benefits, global popularity, and cultural significance.
data_processing:
description: Clean and process the collected voting records into a structured
JSON format.
expected_output: A JSON file containing Senator Marco Rubio's complete voting
record.
tools:
- ''
writer:
backstory: Specializes in creating short, impactful pieces of writing that capture
the essence of the subject matter.
goal: Craft a concise and engaging essay on apples
role: Writer
presenter:
backstory: Skilled in extracting and summarizing information, presenting it in
a clear and concise format.
goal: Generate the final output for user consumption
role: Presenter
tasks:
write_essay:
description: Based on the analyzed data, write a compelling 20-word essay
on apples that encapsulates their essence and significance.
expected_output: An engaging 20-word essay on apples.
presentation_creation:
description: Create an easily digestible presentation from the processed data
on Senator Marco Rubio's voting record.
expected_output: A well-structured text or multimedia output that highlights
key aspects of Senator Marco Rubio's voting history.
tools:
- ''
dependencies: []

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