Integrate the RAG-prototype into the LinuxPrivEsc prototype

src/hackingBuddyGPT/strategies.py

@@ -36,6 +36,8 @@ class CommandStrategy(UseCase, abc.ABC):
 
     disable_history: bool = False
 
+    enable_compressed_history: bool = False
+
     def before_run(self):
         pass
 
@@ -59,7 +61,10 @@ def init(self):
     def get_next_command(self) -> tuple[str, int]:
         history = ""
         if not self.disable_history:
-            history = self._sliding_history.get_history(self._max_history_size - self.get_state_size())
+            if self.enable_compressed_history:
+                history = self._sliding_history.get_commands_and_last_output(self._max_history_size - self.get_state_size())
+            else:
+                history = self._sliding_history.get_history(self._max_history_size - self.get_state_size())
 
         self._template_params.update({"history": history})
         cmd = self.llm.get_response(self._template, **self._template_params)
@@ -111,7 +116,10 @@ def perform_round(self, turn: int) -> bool:
 
         # store the results in our local history
         if not self.disable_history:
-            self._sliding_history.add_command(cmd, result)
+            if self.enable_compressed_history:
+                self._sliding_history.add_command_only(cmds, result)
+            else:
+                self._sliding_history.add_command(cmds, result)
 
         # signal if we were successful in our task
         return task_successful

src/hackingBuddyGPT/usecases/__init__.py

@@ -1,7 +1,6 @@
 from .web import *
 from .web_api_testing import *
 from .viewer import *
-from .rag import *
 from .minimal_linux_privesc import *
 from .call_usecase_from_usecase import *
 from .linux_privesc import *

src/hackingBuddyGPT/usecases/linux_privesc.py

@@ -9,14 +9,25 @@
 from hackingBuddyGPT.usecases.base import use_case
 from hackingBuddyGPT.utils import SSHConnection, llm_util
 from hackingBuddyGPT.utils.logging import log_conversation
+from hackingBuddyGPT.utils.rag import RagBackground
 
-template_analyze = Template("""You executed the command '${cmd}' and retrieved the following result:
+template_analyze = Template("""Your task is to analyze the result of an executed command to determina 
+a way to escalate your privileges into a root shell. Describe your findings including all needed
+information while being as concise as possible.
+
+% if len(rag) > 0:
+You also have the following background information:
+---
+${rag}
+---
+%endif
+
+You executed the command '${cmd}' and retrieved the following result:
 
 ~~~ bash
 ${resp}
 ~~~
-
-Analyze if this response allows you to determine a way to escalate your privileges into a root shell. Be as concise as possible.""")
+""")
 
 template_update_state = Template("""Your current list of known facts relevant for privilege escalation is:
 
@@ -91,12 +102,14 @@ class PrivEscLinux(CommandStrategy):
 
     enable_structured_guidance: bool = False
 
-    enable_rag : bool = False
-
     enable_cot: bool = False
 
+    rag_path: str = ''
+
     _state: str = ""
 
+    _enable_rag: bool = False
+
     def init(self):
         super().init()
 
@@ -118,6 +131,10 @@ def init(self):
 
         guidance = []
 
+        if self.rag_path != '':
+            self._enable_rag = True
+            self._rag_data = RagBackground(self.rag_path, self.llm)
+
         if self.enable_cot:
             self._template_params['cot'] = template_cot
 
@@ -214,16 +231,18 @@ def get_rag_query(self, cmd, result):
     @log_conversation("Analyze its result...", start_section=True)
     def analyze_result(self, cmd, result):
 
-        if self.enable_rag:
-            # TODO: do the RAG query here and add it to the prompt
+        relevant_document_data = ''
+        if self._enable_rag:
             queries = self.get_rag_query(cmd, result)
             print("QUERIES: " + queries.result)
+            relevant_document_data = self._rag_data.get_relevant_documents(queries.result)
+            print("RELEVANT DOCUMENT DATA: " + relevant_document_data)
 
         state_size = self.get_state_size()
         target_size = self.llm.context_size - llm_util.SAFETY_MARGIN - state_size
 
         # ugly, but cut down result to fit context size
         result = llm_util.trim_result_front(self.llm, target_size, result)
-        answer = self.llm.get_response(template_analyze, cmd=cmd, resp=result, facts=self._state)
+        answer = self.llm.get_response(template_analyze, cmd=cmd, resp=result, facts=self._state, rag=relevant_document_data)
         self.log.call_response(answer)
         self._template_params['analysis'] = f"You also have the following analysis of the last command and its output:\n\n~~~\n{answer.result}\n~~~"