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ssh-execut
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temperatur
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b222940de2 |
@ -93,8 +93,8 @@ Things to note:
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* `Session summary`
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* `Session summary`
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* `SSH connection closed`
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* `SSH connection closed`
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* Several of these message types also feature a `details` field with additional information
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* Several of these message types also feature a `details` field with additional information
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* `User input` messages contain a base64-encoded copy of the entire user input
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* `User input` messages contain a base64-encoded copy of the entire user input in the `details` field, as well as an `interactive` field (true/false) that tells you whether this was an interactive or non-interactive command (i.e., whether they logged in with a terminal session or provided a command on the SSH command-line).
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* `LLM response` messages contain a base64-encoded copy of the entire simulated response
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* `LLM response` messages contain a base64-encoded copy of the entire simulated response in the `details` field.
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* `Session summary` messages contain not only a summary of the commands, but also a guess as to what they might have been intended to accomplish. There will also be a `judgement` field that contains one of "BENIGN", "SUSPICIOUS", or "MALICIOUS"
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* `Session summary` messages contain not only a summary of the commands, but also a guess as to what they might have been intended to accomplish. There will also be a `judgement` field that contains one of "BENIGN", "SUSPICIOUS", or "MALICIOUS"
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* Since this is a honeypot and not intended for use by real users, IT WILL LOG USERNAMES AND PASSWORDS! These are found in the `Authentication success` messages, in the `username` and `password` fields.
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* Since this is a honeypot and not intended for use by real users, IT WILL LOG USERNAMES AND PASSWORDS! These are found in the `Authentication success` messages, in the `username` and `password` fields.
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@ -6,6 +6,10 @@
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# The name of the file you wish to write the honeypot log to.
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# The name of the file you wish to write the honeypot log to.
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log_file = ssh_log.log
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log_file = ssh_log.log
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# The name of the sensor, used to identify this honeypot in the logs.
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# If you leave this blank, the honeypot will use the system's hostname.
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sensor_name = deceive
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# Settings for the SSH honeypot
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# Settings for the SSH honeypot
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[ssh]
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[ssh]
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# The port the SSH honeypot will listen on. You will probably want to set
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# The port the SSH honeypot will listen on. You will probably want to set
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@ -14,8 +18,10 @@ port = 8022
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# The host key to use for the SSH server. This should be a private key.
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# The host key to use for the SSH server. This should be a private key.
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# See the README for how to generate this key.
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# See the README for how to generate this key.
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host_priv_key = ssh_host_key
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host_priv_key = ssh_host_key
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# The server version string to send to clients.
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# The server version string to send to clients. The SSH server automatically
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server_version_string = SSH-2.0-OpenSSH_8.2p1 Ubuntu-4ubuntu0.3
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# prepends "SSH-2.0-" to this. So "OpenSSH_8.2p1 Ubuntu-4ubuntu0.3" will
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# be transformed to "SSH-2.0-OpenSSH_8.2p1 Ubuntu-4ubuntu0.3".
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server_version_string = OpenSSH_8.2p1 Ubuntu-4ubuntu0.3
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# Settings to configure which LLM backend to use. Only one stanza
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# Settings to configure which LLM backend to use. Only one stanza
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# should be uncommented at a time.
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# should be uncommented at a time.
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@ -24,6 +30,17 @@ server_version_string = SSH-2.0-OpenSSH_8.2p1 Ubuntu-4ubuntu0.3
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llm_provider = openai
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llm_provider = openai
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model_name = gpt-4o
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model_name = gpt-4o
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##### Azure OpenAI
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#llm_provider = azure
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#azure_deployment = gpt-4o
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#azure_api_version = 2025-01-01-preview
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#azure_endpoint = <your endpoint url>
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#model_name = gpt-4o
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|
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##### ollama llama3
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#llm_provider = ollama
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#model_name = llama3.3
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|
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##### Any model via Amazon Bedrock
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##### Any model via Amazon Bedrock
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# Valid AWS model names can be found here: https://docs.aws.amazon.com/bedrock/latest/userguide/model-ids.html
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# Valid AWS model names can be found here: https://docs.aws.amazon.com/bedrock/latest/userguide/model-ids.html
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#llm_provider = AWS
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#llm_provider = AWS
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@ -36,6 +53,12 @@ model_name = gpt-4o
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#llm_provider = gemini
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#llm_provider = gemini
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#model_name = gemini-1.5-pro
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#model_name = gemini-1.5-pro
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# Temperature controls randomness in LLM responses. Values usually range from 0.0 to 2.0.
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# Lower values (e.g., 0.2) make responses more focused and deterministic.
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# Higher values (e.g., 0.8) make responses more creative and variable.
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# Default is 0.2.
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temperature = 0.2
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# The maximum number of tokens to send to the LLM backend in a single
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# The maximum number of tokens to send to the LLM backend in a single
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# request. This includes the message history for the session, so should
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# request. This includes the message history for the session, so should
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# be fairly high. Not all models support large token counts, so be sure
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# be fairly high. Not all models support large token counts, so be sure
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@ -75,9 +98,12 @@ system_prompt = Interpret all inputs as though they were SSH commands and provid
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# The valid user accounts and passwords for the SSH server, in the
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# The valid user accounts and passwords for the SSH server, in the
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# form "username = password". Note that you can enable login without
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# form "username = password". Note that you can enable login without
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# a password by leaving that field blank (e.g., "guest =" on a line by
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# a password by leaving that field blank (e.g., "guest =" on a line by
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# itself)
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# itself). You can set an account to accept ANY password, including an empty
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# password, by setting the password to "*"
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[user_accounts]
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[user_accounts]
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guest =
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guest =
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user1 = secretpw
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user1 = secretpw
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user2 = password123
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user2 = password123
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root = *
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@ -15,17 +15,23 @@ import datetime
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import uuid
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import uuid
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from base64 import b64encode
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from base64 import b64encode
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from operator import itemgetter
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from operator import itemgetter
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from langchain_openai import ChatOpenAI
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from langchain_openai import ChatOpenAI, AzureChatOpenAI
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from langchain_aws import ChatBedrock, ChatBedrockConverse
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from langchain_aws import ChatBedrock, ChatBedrockConverse
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from langchain_google_genai import ChatGoogleGenerativeAI
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from langchain_google_genai import ChatGoogleGenerativeAI
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from langchain_ollama import ChatOllama
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from langchain_core.messages import HumanMessage, SystemMessage, trim_messages
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from langchain_core.messages import HumanMessage, SystemMessage, trim_messages
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from langchain_core.chat_history import BaseChatMessageHistory, InMemoryChatMessageHistory
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from langchain_core.chat_history import BaseChatMessageHistory, InMemoryChatMessageHistory
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from langchain_core.runnables.history import RunnableWithMessageHistory
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from langchain_core.runnables.history import RunnableWithMessageHistory
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from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder
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from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder
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from langchain_core.runnables import RunnablePassthrough
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from langchain_core.runnables import RunnablePassthrough
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from asyncssh.misc import ConnectionLost
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from asyncssh.misc import ConnectionLost
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import socket
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class JSONFormatter(logging.Formatter):
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class JSONFormatter(logging.Formatter):
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def __init__(self, sensor_name, *args, **kwargs):
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super().__init__(*args, **kwargs)
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self.sensor_name = sensor_name
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def format(self, record):
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def format(self, record):
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log_record = {
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log_record = {
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"timestamp": datetime.datetime.fromtimestamp(record.created, datetime.timezone.utc).isoformat(sep="T", timespec="milliseconds"),
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"timestamp": datetime.datetime.fromtimestamp(record.created, datetime.timezone.utc).isoformat(sep="T", timespec="milliseconds"),
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@ -35,7 +41,9 @@ class JSONFormatter(logging.Formatter):
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"src_port": record.src_port,
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"src_port": record.src_port,
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"dst_ip": record.dst_ip,
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"dst_ip": record.dst_ip,
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"dst_port": record.dst_port,
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"dst_port": record.dst_port,
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"message": record.getMessage()
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"message": record.getMessage(),
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"sensor_name": self.sensor_name,
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"sensor_protocol": "ssh"
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}
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}
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if hasattr(record, 'interactive'):
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if hasattr(record, 'interactive'):
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log_record["interactive"] = record.interactive
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log_record["interactive"] = record.interactive
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@ -105,7 +113,7 @@ class MySSHServer(asyncssh.SSHServer):
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def validate_password(self, username: str, password: str) -> bool:
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def validate_password(self, username: str, password: str) -> bool:
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pw = accounts.get(username, '*')
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pw = accounts.get(username, '*')
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if ((pw != '*') and (password == pw)):
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if pw == '*' or (pw != '*' and password == pw):
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logger.info("Authentication success", extra={"username": username, "password": password})
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logger.info("Authentication success", extra={"username": username, "password": password})
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return True
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return True
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else:
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else:
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@ -168,6 +176,7 @@ representative examples.
|
|||||||
judgement = "MALICIOUS"
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judgement = "MALICIOUS"
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logger.info("Session summary", extra={"details": llm_response.content, "judgement": judgement})
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logger.info("Session summary", extra={"details": llm_response.content, "judgement": judgement})
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|
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server.summary_generated = True
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server.summary_generated = True
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|
|
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async def handle_client(process: asyncssh.SSHServerProcess, server: MySSHServer) -> None:
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async def handle_client(process: asyncssh.SSHServerProcess, server: MySSHServer) -> None:
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@ -225,7 +234,7 @@ async def handle_client(process: asyncssh.SSHServerProcess, server: MySSHServer)
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},
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},
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config=llm_config
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config=llm_config
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)
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)
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if llm_response.content == "XXX-END-OF-SESSION-XXX":
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if llm_response.content == "YYY-END-OF-SESSION-YYY":
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await session_summary(process, llm_config, with_message_history, server)
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await session_summary(process, llm_config, with_message_history, server)
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process.exit(0)
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process.exit(0)
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return
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return
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@ -269,7 +278,7 @@ class ContextFilter(logging.Filter):
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if task:
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if task:
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task_name = task.get_name()
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task_name = task.get_name()
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else:
|
else:
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task_name = "-"
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task_name = thread_local.__dict__.get('session_id', '-')
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record.src_ip = thread_local.__dict__.get('src_ip', '-')
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record.src_ip = thread_local.__dict__.get('src_ip', '-')
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record.src_port = thread_local.__dict__.get('src_port', '-')
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record.src_port = thread_local.__dict__.get('src_port', '-')
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@ -296,23 +305,43 @@ def get_user_accounts() -> dict:
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|
|
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return accounts
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return accounts
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def choose_llm():
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def choose_llm(llm_provider: Optional[str] = None, model_name: Optional[str] = None):
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llm_provider_name = config['llm'].get("llm_provider", "openai")
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llm_provider_name = llm_provider or config['llm'].get("llm_provider", "openai")
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llm_provider_name = llm_provider_name.lower()
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llm_provider_name = llm_provider_name.lower()
|
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model_name = config['llm'].get("model_name", "gpt-3.5-turbo")
|
model_name = model_name or config['llm'].get("model_name", "gpt-3.5-turbo")
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|
|
||||||
|
# Get temperature parameter from config, default to 0.7 if not specified
|
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|
temperature = config['llm'].getfloat("temperature", 0.7)
|
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|
|
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if llm_provider_name == 'openai':
|
if llm_provider_name == 'openai':
|
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llm_model = ChatOpenAI(
|
llm_model = ChatOpenAI(
|
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model=model_name
|
model=model_name,
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|
temperature=temperature
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|
)
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|
elif llm_provider_name == 'azure':
|
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|
llm_model = AzureChatOpenAI(
|
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|
azure_deployment=config['llm'].get("azure_deployment"),
|
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|
azure_endpoint=config['llm'].get("azure_endpoint"),
|
||||||
|
api_version=config['llm'].get("azure_api_version"),
|
||||||
|
model=config['llm'].get("model_name"), # Ensure model_name is passed here
|
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|
temperature=temperature
|
||||||
|
)
|
||||||
|
elif llm_provider_name == 'ollama':
|
||||||
|
llm_model = ChatOllama(
|
||||||
|
model=model_name,
|
||||||
|
temperature=temperature
|
||||||
)
|
)
|
||||||
elif llm_provider_name == 'aws':
|
elif llm_provider_name == 'aws':
|
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llm_model = ChatBedrockConverse(
|
llm_model = ChatBedrockConverse(
|
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model=model_name,
|
model=model_name,
|
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region_name=config['llm'].get("aws_region", "us-east-1"),
|
region_name=config['llm'].get("aws_region", "us-east-1"),
|
||||||
credentials_profile_name=config['llm'].get("aws_credentials_profile", "default") )
|
credentials_profile_name=config['llm'].get("aws_credentials_profile", "default"),
|
||||||
|
temperature=temperature
|
||||||
|
)
|
||||||
elif llm_provider_name == 'gemini':
|
elif llm_provider_name == 'gemini':
|
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llm_model = ChatGoogleGenerativeAI(
|
llm_model = ChatGoogleGenerativeAI(
|
||||||
model=model_name,
|
model=model_name,
|
||||||
|
temperature=temperature
|
||||||
)
|
)
|
||||||
else:
|
else:
|
||||||
raise ValueError(f"Invalid LLM provider {llm_provider_name}.")
|
raise ValueError(f"Invalid LLM provider {llm_provider_name}.")
|
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@ -347,25 +376,82 @@ def get_prompts(prompt: Optional[str], prompt_file: Optional[str]) -> dict:
|
|||||||
try:
|
try:
|
||||||
# Parse command line arguments
|
# Parse command line arguments
|
||||||
parser = argparse.ArgumentParser(description='Start the SSH honeypot server.')
|
parser = argparse.ArgumentParser(description='Start the SSH honeypot server.')
|
||||||
parser.add_argument('-c', '--config', type=str, default='config.ini', help='Path to the configuration file')
|
parser.add_argument('-c', '--config', type=str, default=None, help='Path to the configuration file')
|
||||||
parser.add_argument('-p', '--prompt', type=str, help='The entire text of the prompt')
|
parser.add_argument('-p', '--prompt', type=str, help='The entire text of the prompt')
|
||||||
parser.add_argument('-f', '--prompt-file', type=str, default='prompt.txt', help='Path to the prompt file')
|
parser.add_argument('-f', '--prompt-file', type=str, default='prompt.txt', help='Path to the prompt file')
|
||||||
|
parser.add_argument('-l', '--llm-provider', type=str, help='The LLM provider to use')
|
||||||
|
parser.add_argument('-m', '--model-name', type=str, help='The model name to use')
|
||||||
|
parser.add_argument('-t', '--trimmer-max-tokens', type=int, help='The maximum number of tokens to send to the LLM backend in a single request')
|
||||||
|
parser.add_argument('-s', '--system-prompt', type=str, help='System prompt for the LLM')
|
||||||
|
parser.add_argument('-r', '--temperature', type=float, help='Temperature parameter for controlling randomness in LLM responses (0.0-2.0)')
|
||||||
|
parser.add_argument('-P', '--port', type=int, help='The port the SSH honeypot will listen on')
|
||||||
|
parser.add_argument('-k', '--host-priv-key', type=str, help='The host key to use for the SSH server')
|
||||||
|
parser.add_argument('-v', '--server-version-string', type=str, help='The server version string to send to clients')
|
||||||
|
parser.add_argument('-L', '--log-file', type=str, help='The name of the file you wish to write the honeypot log to')
|
||||||
|
parser.add_argument('-S', '--sensor-name', type=str, help='The name of the sensor, used to identify this honeypot in the logs')
|
||||||
|
parser.add_argument('-u', '--user-account', action='append', help='User account in the form username=password. Can be repeated.')
|
||||||
args = parser.parse_args()
|
args = parser.parse_args()
|
||||||
|
|
||||||
# Check if the config file exists
|
# Determine which config file to load
|
||||||
if not os.path.exists(args.config):
|
config = ConfigParser()
|
||||||
print(f"Error: The specified config file '{args.config}' does not exist.", file=sys.stderr)
|
if args.config is not None:
|
||||||
sys.exit(1)
|
# User explicitly set a config file; error if it doesn't exist.
|
||||||
|
if not os.path.exists(args.config):
|
||||||
|
print(f"Error: The specified config file '{args.config}' does not exist.", file=sys.stderr)
|
||||||
|
sys.exit(1)
|
||||||
|
config.read(args.config)
|
||||||
|
else:
|
||||||
|
default_config = "config.ini"
|
||||||
|
if os.path.exists(default_config):
|
||||||
|
config.read(default_config)
|
||||||
|
else:
|
||||||
|
# Use defaults when no config file found.
|
||||||
|
config['honeypot'] = {'log_file': 'ssh_log.log', 'sensor_name': socket.gethostname()}
|
||||||
|
config['ssh'] = {'port': '8022', 'host_priv_key': 'ssh_host_key', 'server_version_string': 'SSH-2.0-OpenSSH_8.2p1 Ubuntu-4ubuntu0.3'}
|
||||||
|
config['llm'] = {'llm_provider': 'openai', 'model_name': 'gpt-3.5-turbo', 'trimmer_max_tokens': '64000', 'temperature': '0.7', 'system_prompt': ''}
|
||||||
|
config['user_accounts'] = {}
|
||||||
|
|
||||||
|
# Override config values with command line arguments if provided
|
||||||
|
if args.llm_provider:
|
||||||
|
config['llm']['llm_provider'] = args.llm_provider
|
||||||
|
if args.model_name:
|
||||||
|
config['llm']['model_name'] = args.model_name
|
||||||
|
if args.trimmer_max_tokens:
|
||||||
|
config['llm']['trimmer_max_tokens'] = str(args.trimmer_max_tokens)
|
||||||
|
if args.system_prompt:
|
||||||
|
config['llm']['system_prompt'] = args.system_prompt
|
||||||
|
if args.temperature is not None:
|
||||||
|
config['llm']['temperature'] = str(args.temperature)
|
||||||
|
if args.port:
|
||||||
|
config['ssh']['port'] = str(args.port)
|
||||||
|
if args.host_priv_key:
|
||||||
|
config['ssh']['host_priv_key'] = args.host_priv_key
|
||||||
|
if args.server_version_string:
|
||||||
|
config['ssh']['server_version_string'] = args.server_version_string
|
||||||
|
if args.log_file:
|
||||||
|
config['honeypot']['log_file'] = args.log_file
|
||||||
|
if args.sensor_name:
|
||||||
|
config['honeypot']['sensor_name'] = args.sensor_name
|
||||||
|
|
||||||
|
# Merge command-line user accounts into the config
|
||||||
|
if args.user_account:
|
||||||
|
if 'user_accounts' not in config:
|
||||||
|
config['user_accounts'] = {}
|
||||||
|
for account in args.user_account:
|
||||||
|
if '=' in account:
|
||||||
|
key, value = account.split('=', 1)
|
||||||
|
config['user_accounts'][key.strip()] = value.strip()
|
||||||
|
else:
|
||||||
|
config['user_accounts'][account.strip()] = ''
|
||||||
|
|
||||||
|
# Read the user accounts from the configuration
|
||||||
|
accounts = get_user_accounts()
|
||||||
|
|
||||||
# Always use UTC for logging
|
# Always use UTC for logging
|
||||||
logging.Formatter.formatTime = (lambda self, record, datefmt=None: datetime.datetime.fromtimestamp(record.created, datetime.timezone.utc).isoformat(sep="T",timespec="milliseconds"))
|
logging.Formatter.formatTime = (lambda self, record, datefmt=None: datetime.datetime.fromtimestamp(record.created, datetime.timezone.utc).isoformat(sep="T",timespec="milliseconds"))
|
||||||
|
|
||||||
# Read our configuration file
|
# Get the sensor name from the config or use the system's hostname
|
||||||
config = ConfigParser()
|
sensor_name = config['honeypot'].get('sensor_name', socket.gethostname())
|
||||||
config.read(args.config)
|
|
||||||
|
|
||||||
# Read the user accounts from the configuration file
|
|
||||||
accounts = get_user_accounts()
|
|
||||||
|
|
||||||
# Set up the honeypot logger
|
# Set up the honeypot logger
|
||||||
logger = logging.getLogger(__name__)
|
logger = logging.getLogger(__name__)
|
||||||
@ -374,7 +460,7 @@ try:
|
|||||||
log_file_handler = logging.FileHandler(config['honeypot'].get("log_file", "ssh_log.log"))
|
log_file_handler = logging.FileHandler(config['honeypot'].get("log_file", "ssh_log.log"))
|
||||||
logger.addHandler(log_file_handler)
|
logger.addHandler(log_file_handler)
|
||||||
|
|
||||||
log_file_handler.setFormatter(JSONFormatter())
|
log_file_handler.setFormatter(JSONFormatter(sensor_name))
|
||||||
|
|
||||||
f = ContextFilter()
|
f = ContextFilter()
|
||||||
logger.addFilter(f)
|
logger.addFilter(f)
|
||||||
@ -385,7 +471,7 @@ try:
|
|||||||
llm_system_prompt = prompts["system_prompt"]
|
llm_system_prompt = prompts["system_prompt"]
|
||||||
llm_user_prompt = prompts["user_prompt"]
|
llm_user_prompt = prompts["user_prompt"]
|
||||||
|
|
||||||
llm = choose_llm()
|
llm = choose_llm(config['llm'].get("llm_provider"), config['llm'].get("model_name"))
|
||||||
|
|
||||||
llm_sessions = dict()
|
llm_sessions = dict()
|
||||||
|
|
||||||
|
@ -7,7 +7,8 @@ langchain_community
|
|||||||
langchain_openai
|
langchain_openai
|
||||||
# For Google's Gemini models
|
# For Google's Gemini models
|
||||||
langchain_google_genai
|
langchain_google_genai
|
||||||
|
# For Ollama models
|
||||||
|
langchain_ollama
|
||||||
# For AWS
|
# For AWS
|
||||||
langchain_aws
|
langchain_aws
|
||||||
transformers
|
transformers
|
||||||
|
Reference in New Issue
Block a user