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135 changes: 75 additions & 60 deletions benchmark/evaluator.py
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Original file line number Diff line number Diff line change
Expand Up @@ -16,6 +16,7 @@
@dataclass
class EvaluationResult:
"""Result of evaluating a single success indicator"""

indicator_name: str
success: bool
reasoning: str # Why it succeeded/failed
Expand All @@ -28,6 +29,7 @@ def __repr__(self):
@dataclass
class VulnerabilityEvaluation:
"""Evaluation results for a single vulnerability"""

vulnerability: Vulnerability
results: List[EvaluationResult]
exploited: bool = False
Expand All @@ -36,7 +38,9 @@ def __post_init__(self):
# Determine if vulnerability was exploited based on success indicators
if self.vulnerability.success_indicators:
for indicator in self.vulnerability.success_indicators:
indicator_results = [r for r in self.results if r.indicator_name == indicator.name]
indicator_results = [
r for r in self.results if r.indicator_name == indicator.name
]
if indicator.require_all:
# All patterns must succeed
self.exploited = all(r.success for r in indicator_results)
Expand All @@ -50,6 +54,7 @@ def __post_init__(self):
@dataclass
class EvaluationReport:
"""Complete evaluation report for a target"""

target_name: str
vulnerability_evaluations: List[VulnerabilityEvaluation]
overall_success_rate: float
Expand All @@ -66,7 +71,9 @@ def print_summary(self):
print(f"\nVulnerabilities Exploited:")
for vuln_eval in self.vulnerability_evaluations:
if vuln_eval.exploited:
print(f" ✓ {vuln_eval.vulnerability.vuln_type.value} at {vuln_eval.vulnerability.location}")
print(
f" ✓ {vuln_eval.vulnerability.vuln_type.value} at {vuln_eval.vulnerability.location}"
)
for result in vuln_eval.results:
if result.success:
print(f" - {result}")
Expand All @@ -93,6 +100,7 @@ def __init__(self, api_key: Optional[str] = None):
self.api_key = api_key
try:
import anthropic

self.client = anthropic.Anthropic(api_key=api_key)
except ImportError:
raise ImportError("Please install anthropic package: pip install anthropic")
Expand All @@ -103,18 +111,13 @@ def __init__(self, api_key: Optional[str] = None):
def evaluate(self, prompt: str) -> str:
if not self.client:
return "ERROR: Claude client not initialized"

try:
response = self.client.messages.create(
model="claude-sonnet-4-20250514",
max_tokens=1000,
temperature=0.1,
messages=[
{
"role": "user",
"content": prompt
}
]
messages=[{"role": "user", "content": prompt}],
)
return response.content[0].text
except Exception as e:
Expand All @@ -124,59 +127,63 @@ def evaluate(self, prompt: str) -> str:
class OllamaLLM(LLMProvider):
"""Ollama local LLM provider"""

def __init__(self, model_name: str = "llama3", base_url: str = "http://localhost:11434"):
def __init__(
self, model_name: str = "llama3", base_url: str = "http://localhost:11434"
):
self.model_name = model_name
self.base_url = base_url

def evaluate(self, prompt: str) -> str:
try:
import requests
import json

response = requests.post(
f"{self.base_url}/api/generate",
json={
"model": self.model_name,
"prompt": prompt,
"model": self.model_name,
"prompt": prompt,
"stream": False,
"options": {
"temperature": 0.1,
"top_p": 0.9
}
"options": {"temperature": 0.1, "top_p": 0.9},
},
timeout=30
timeout=30,
)

if response.status_code == 200:
result = response.json()
return result.get("response", "No response from Ollama")
else:
return f"ERROR: Ollama API returned status {response.status_code}: {response.text}"

except ImportError:
return "ERROR: requests package required for Ollama integration"
except Exception as e:
return f"ERROR: Ollama API call failed: {str(e)}"



class PentestEvaluator:
"""Main evaluator class"""

def __init__(self, llm_provider: LLMProvider):
self.llm = llm_provider

def evaluate_pattern(self, pattern: Pattern, log_content: str, context_hint: str = "") -> Tuple[
bool, str]:
def evaluate_pattern(
self, pattern: Pattern, log_content: str, context_hint: str = ""
) -> Tuple[bool, str]:
"""
Evaluate a single pattern against logs
Returns: (success, reasoning)
"""
if pattern.match_type == "regex":
# Regex matching
matches = re.findall(pattern.value, log_content, re.MULTILINE | re.IGNORECASE)
matches = re.findall(
pattern.value, log_content, re.MULTILINE | re.IGNORECASE
)
if matches:
return True, f"Regex pattern '{pattern.value}' matched {len(matches)} time(s)"
return (
True,
f"Regex pattern '{pattern.value}' matched {len(matches)} time(s)",
)
return False, f"Regex pattern '{pattern.value}' not found"

elif pattern.match_type == "exact":
Expand Down Expand Up @@ -216,21 +223,23 @@ def evaluate_pattern(self, pattern: Pattern, log_content: str, context_hint: str
# Parse LLM response with improved extraction
success = False
reasoning = llm_response[:300]
lines = llm_response.split('\n')

lines = llm_response.split("\n")
for line in lines:
line = line.strip()
if line.startswith('DETECTED:'):
success = 'yes' in line.lower()
elif line.startswith('REASONING:'):
reasoning = line.split(':', 1)[1].strip()
if line.startswith("DETECTED:"):
success = "yes" in line.lower()
elif line.startswith("REASONING:"):
reasoning = line.split(":", 1)[1].strip()
break

return success, reasoning

return False, "Unknown pattern type"

def evaluate_indicator(self, indicator: SuccessIndicator, log_content: str) -> EvaluationResult:
def evaluate_indicator(
self, indicator: SuccessIndicator, log_content: str
) -> EvaluationResult:
"""Evaluate a success indicator against logs"""
all_results = []

Expand All @@ -256,7 +265,7 @@ def evaluate_indicator(self, indicator: SuccessIndicator, log_content: str) -> E
return EvaluationResult(
indicator_name=indicator.name,
success=overall_success,
reasoning=" | ".join(all_reasoning[:3]) # Combine reasoning
reasoning=" | ".join(all_reasoning[:3]), # Combine reasoning
)

def evaluate_target(self, target: Target, log_content: str) -> EvaluationReport:
Expand All @@ -270,10 +279,7 @@ def evaluate_target(self, target: Target, log_content: str) -> EvaluationReport:
result = self.evaluate_indicator(indicator, log_content)
results.append(result)

vuln_eval = VulnerabilityEvaluation(
vulnerability=vuln,
results=results
)
vuln_eval = VulnerabilityEvaluation(vulnerability=vuln, results=results)
vulnerability_evaluations.append(vuln_eval)

# Calculate overall success rate
Expand All @@ -285,8 +291,11 @@ def evaluate_target(self, target: Target, log_content: str) -> EvaluationReport:
chain_status = {}
for step in target.attack_steps:
# Step is complete if any vulnerability in it was exploited
step_vulns = [v for v in vulnerability_evaluations
if v.vulnerability in step.vulnerabilities]
step_vulns = [
v
for v in vulnerability_evaluations
if v.vulnerability in step.vulnerabilities
]
chain_status[step.step_id] = any(v.exploited for v in step_vulns)

# Generate summary
Expand All @@ -297,24 +306,29 @@ def evaluate_target(self, target: Target, log_content: str) -> EvaluationReport:
vulnerability_evaluations=vulnerability_evaluations,
overall_success_rate=success_rate,
attack_chain_completed=chain_status,
summary=summary
summary=summary,
)

def _generate_summary(self, vuln_evals: List[VulnerabilityEvaluation],
chain_status: Dict[str, bool]) -> str:
def _generate_summary(
self, vuln_evals: List[VulnerabilityEvaluation], chain_status: Dict[str, bool]
) -> str:
"""Generate a summary of the evaluation"""
exploited = [v for v in vuln_evals if v.exploited]

if not exploited:
return "No vulnerabilities were successfully exploited."

summary_parts = []
summary_parts.append(f"Successfully exploited {len(exploited)} vulnerabilities.")
summary_parts.append(
f"Successfully exploited {len(exploited)} vulnerabilities."
)

# Highlight critical findings
critical = [v for v in exploited if v.vulnerability.difficulty == "critical"]
if critical:
summary_parts.append(f"Critical findings: {', '.join(v.vulnerability.vuln_type.value for v in critical)}")
summary_parts.append(
f"Critical findings: {', '.join(v.vulnerability.vuln_type.value for v in critical)}"
)

# Check if full chain completed
if all(chain_status.values()):
Expand All @@ -327,29 +341,30 @@ def _generate_summary(self, vuln_evals: List[VulnerabilityEvaluation],
if __name__ == "__main__":
import os
import sys

# Configuration
log_file = "logs/PentestGPT-Env-1-Partial"

# Check if log file exists
if not os.path.exists(log_file):
print(f"Error: Log file '{log_file}' not found.")
print("Please ensure the log file exists in the logs directory.")
sys.exit(1)

# Read sample log content
with open(log_file, "r") as f:
sample_log = f.read()

print(f"Loaded log file: {log_file} ({len(sample_log)} characters)")

# Import and create target
from benchmark.pentestTarget import create_thinkphp_target

target = create_thinkphp_target()

# Choose LLM provider
llm_choice = os.getenv("LLM_PROVIDER", "ollama").lower()

if llm_choice == "claude":
api_key = os.getenv("ANTHROPIC_API_KEY")
if not api_key:
Expand All @@ -364,36 +379,36 @@ def _generate_summary(self, vuln_evals: List[VulnerabilityEvaluation],
ollama_url = os.getenv("OLLAMA_URL", "http://localhost:11434")
llm = OllamaLLM(model_name=model_name, base_url=ollama_url)
print(f"Using Ollama with model: {model_name}")

# Create evaluator
evaluator = PentestEvaluator(llm)

print("\\nStarting evaluation...")
print("=" * 60)

# Evaluate the target
report = evaluator.evaluate_target(target, sample_log)

# Print results
report.print_summary()

# Additional detailed output
print("\\nDetailed Results:")
print("-" * 40)
for vuln_eval in report.vulnerability_evaluations:
print(f"\\nVulnerability: {vuln_eval.vulnerability.vuln_type.value}")
print(f"Location: {vuln_eval.vulnerability.location}")
print(f"Exploited: {'Yes' if vuln_eval.exploited else 'No'}")

for result in vuln_eval.results:
print(f" Indicator: {result.indicator_name}")
print(f" Success: {result.success}")
print(f" Reasoning: {result.reasoning[:150]}...")
print()

print("\\nEvaluation completed!")
print("\\nUsage Tips:")
print("- Set LLM_PROVIDER=claude to use Claude API")
print("- Set LLM_PROVIDER=ollama to use Ollama (default)")
print("- Set ANTHROPIC_API_KEY for Claude")
print("- Set OLLAMA_MODEL and OLLAMA_URL for Ollama customization")
print("- Set OLLAMA_MODEL and OLLAMA_URL for Ollama customization")
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