MemScan-EDR/src-csharp/MemScanEDR/Services/AIAnalyzer.cs

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using System;
using System.Collections.Generic;
using System.Net.Http;
using System.Text;
using System.Text.Json;
using System.Threading.Tasks;
using MemScanEDR.Models;
namespace MemScanEDR.Services;
/// <summary>
/// AI 分析器 v2.0 —— 重构版
/// 核心变化:
/// - 默认使用本地 AI 管线DetectionPipeline基线+分类+规则三级联动)
/// - LLM 大模型仅用于辅助研判(可选,需手动开启)
/// - 启发式规则引擎作为降级方案保留
/// </summary>
public class AIAnalyzer
{
private readonly HttpClient _http = new();
private AIConfig _config;
private readonly DetectionPipeline _pipeline;
private readonly List<Signature> _signatures;
public AIAnalyzer(AIConfig config, List<Signature> signatures, ScanMode scanMode = ScanMode.Balanced)
{
_config = config;
_signatures = signatures;
_http.Timeout = TimeSpan.FromSeconds(config.Timeout);
_pipeline = new DetectionPipeline(scanMode);
}
public void UpdateConfig(AIConfig config)
{
_config = config;
_http.Timeout = TimeSpan.FromSeconds(config.Timeout);
}
/// <summary>
/// 分析进程 —— v2.0 核心入口
/// </summary>
public async Task<ScanResult> AnalyzeProcessAsync(ProcessInfo proc,
List<SignatureMatch>? matches = null, List<MemoryRegion>? suspiciousRegions = null)
{
// v2.0: 优先使用本地 AI 管线
if (_config.EnableLocalAI)
{
try
{
var result = await _pipeline.AnalyzeAsync(proc, _signatures);
// 如果启用了 LLM 辅助研判且本地 AI 判定为可疑/高危
if (_config.EnableLLMAssist &&
result.RiskLevel != RiskLevel.Safe &&
_config.Provider != AIProvider.Heuristic)
{
var llmResult = await LlmAssistedAnalysis(proc, result);
if (llmResult != null)
{
// LLM 结果作为补充参考,不覆盖本地 AI 的核心判定
result.Reasoning += $" | LLM研判: {llmResult.Reasoning}";
result.AIProvider += " + LLM";
}
}
return result;
}
catch (Exception ex)
{
// 管线异常时回退
return HeuristicAnalyze(proc, matches ?? new(), suspiciousRegions ?? new(),
$"管线异常回退: {ex.Message}");
}
}
// 未启用本地AI时的传统模式
if (_config.Provider == AIProvider.Heuristic)
{
return HeuristicAnalyze(proc, matches ?? new(), suspiciousRegions ?? new());
}
// 传统 LLM 模式(兼容 v1.0
return await LegacyApiAnalyze(proc, matches ?? new(), suspiciousRegions ?? new());
}
/// <summary>
/// LLM 辅助研判 —— 仅对本地 AI 已标记为可疑的进程做二次确认
/// </summary>
private async Task<ScanResult?> LlmAssistedAnalysis(ProcessInfo proc, ScanResult pipelineResult)
{
try
{
var prompt = BuildLlmAssistPrompt(proc, pipelineResult);
var response = await CallAIAsync(prompt);
return ParseLlmResponse(proc, response);
}
catch
{
return null;
}
}
private static string BuildLlmAssistPrompt(ProcessInfo proc, ScanResult pipelineResult)
{
var sb = new StringBuilder();
sb.AppendLine("=== 本地AI已标记为可疑的进程 ===");
sb.AppendLine($"PID: {proc.Pid}, 进程名: {proc.Name}, 路径: {proc.ExePath}");
sb.AppendLine($"风险等级: {pipelineResult.RiskLevel}, 评分: {pipelineResult.RiskScore:F2}");
sb.AppendLine($"指标: {string.Join(", ", pipelineResult.Indicators)}");
sb.AppendLine($"检测层: {pipelineResult.DetectionLayer}");
sb.AppendLine($"本地AI推理: {pipelineResult.Reasoning}");
sb.AppendLine("\n=== 请结合以上信息做最终研判 ===");
sb.AppendLine("请判断此进程是否为真正的威胁,并给出简短理由。");
sb.AppendLine("注意:.NET/Java/Node.js/Chrome等JIT运行时可能有合法RWX内存安全软件可能有注入行为。");
return sb.ToString();
}
private ScanResult ParseLlmResponse(ProcessInfo proc, string content)
{
return new ScanResult
{
Pid = proc.Pid,
ProcessName = proc.Name,
RiskLevel = RiskLevel.Safe,
RiskScore = 0,
Reasoning = content.Trim().Length > 200 ? content.Trim()[..200] : content.Trim(),
AIProvider = $"llm-assist/{_config.Model}"
};
}
/// <summary>
/// 传统 LLM API 分析(兼容 v1.0 模式)
/// </summary>
private async Task<ScanResult> LegacyApiAnalyze(ProcessInfo proc,
List<SignatureMatch> matches, List<MemoryRegion> suspiciousRegions)
{
var preScore = QuickPreScore(proc, matches, suspiciousRegions);
if (preScore < 0.05)
{
return new ScanResult
{
Pid = proc.Pid,
ProcessName = proc.Name,
RiskLevel = RiskLevel.Safe,
RiskScore = 0.0,
Indicators = new List<string>(),
Reasoning = $"PID {proc.Pid} ({proc.Name}) | v2.0 预过滤跳过",
AIProvider = "heuristic/pre-filter-v2",
DetectionLayer = "PreFilter",
ScanTime = DateTime.Now
};
}
try
{
var prompt = BuildLegacyPrompt(proc, matches, suspiciousRegions);
var response = await CallAIAsync(prompt);
return ParseLegacyResponse(proc, response);
}
catch (Exception ex)
{
return HeuristicAnalyze(proc, matches, suspiciousRegions,
$"API异常回退: {ex.Message}");
}
}
private static double QuickPreScore(ProcessInfo proc, List<SignatureMatch> matches,
List<MemoryRegion> suspiciousRegions)
{
double s = 0;
if (!proc.IsSigned && proc.IsTempPath) s += 0.30;
if (FeatureExtractor.IsSystemProcessName(proc.Name) && !proc.IsSystemPath) s += 0.25;
var suspPorts = new HashSet<int> { 4444, 5555, 6666, 7777, 1337, 31337, 9999, 12345, 27015 };
if (proc.Connections.Any(c => suspPorts.Contains(c.RemotePort))) s += 0.20;
if (matches.Count > 0) s += 0.20;
if (suspiciousRegions.Any(r => r.Protect.Contains("EXECUTE_READWRITE"))) s += 0.15;
return Math.Min(s, 1.0);
}
// ─── 启发式规则(保留作为降级方案)───
public ScanResult HeuristicAnalyze(ProcessInfo proc, List<SignatureMatch> matches,
List<MemoryRegion> suspiciousRegions, string? errorNote = null)
{
double score = 0;
var indicators = new List<string>();
var reasons = new List<string>();
// Rule 1: unsigned + temp path
if (!proc.IsSigned && proc.IsTempPath)
{
score += 0.30;
indicators.Add("unsigned_temp_path");
reasons.Add("unsigned executable in temp directory");
}
// Rule 2: process masquerading
if (FeatureExtractor.IsSystemProcessName(proc.Name) && !proc.IsSystemPath)
{
score += 0.25;
indicators.Add("process_masquerading");
reasons.Add("system process name in non-system path");
}
// Rule 3: suspicious ports
var suspPorts = new HashSet<int> { 4444, 5555, 6666, 7777, 1337, 31337 };
foreach (var conn in proc.Connections)
{
if (suspPorts.Contains(conn.RemotePort))
{
score += 0.20;
indicators.Add("suspicious_port");
reasons.Add($"suspicious remote port {conn.RemotePort}");
break;
}
}
// Rule 4: signature matches
if (matches.Count > 0)
{
var high = matches.Count(m => m.Severity == "high");
var med = matches.Count(m => m.Severity == "medium");
score += Math.Min(high * 0.20, 0.4);
score += Math.Min(med * 0.08, 0.2);
if (high > 0) { indicators.Add("high_severity_match"); reasons.Add($"{high} high-severity signatures"); }
if (matches.Any(m => m.Category == "shellcode")) { score += 0.15; indicators.Add("shellcode_detected"); }
if (matches.Any(m => m.Category == "c2")) { score += 0.20; indicators.Add("c2_pattern"); }
}
// Rule 5: suspicious memory regions (v2.0 improved: distinguish JIT)
var rwxCount = suspiciousRegions.Count(r =>
r.Protect.Contains("EXECUTE_READWRITE") && r.Type == "PRIVATE");
// v2.0 improvement: don't flag JIT runtimes
var isRuntime = proc.Name.ToLowerInvariant() switch
{
var n when n.Contains("dotnet") || n.Contains("java") ||
n.Contains("node") || n.Contains("python") ||
n.Contains("chrome") || n.Contains("msedge") ||
n.Contains("firefox") => true,
_ => false
};
if (rwxCount > 0 && !isRuntime)
{
score += Math.Min(rwxCount * 0.12, 0.25);
indicators.Add("rwx_private_memory");
}
score = Math.Min(score, 1.0);
var level = score >= 0.75 ? RiskLevel.High : score >= 0.50 ? RiskLevel.Suspicious : RiskLevel.Safe;
var reasoning = $"PID {proc.Pid} ({proc.Name}) | {string.Join("; ", reasons)} | score={score:F2}";
if (errorNote != null)
reasoning += $" | {errorNote}";
return new ScanResult
{
Pid = proc.Pid,
ProcessName = proc.Name,
RiskLevel = level,
RiskScore = score,
Indicators = indicators,
Reasoning = reasoning,
AIProvider = "heuristic/rule-engine-v2",
DetectionLayer = "Heuristic",
ScanTime = DateTime.Now
};
}
// ─── LLM API 调用 ───
private async Task<string> CallAIAsync(string userMessage)
{
if (_config.Provider == AIProvider.Claude)
return await CallClaudeAsync(userMessage);
var url = _config.Provider == AIProvider.Local
? $"{_config.BaseUrl}/api/chat"
: $"{_config.BaseUrl.TrimEnd('/')}/chat/completions";
object requestBody = _config.Provider == AIProvider.Local
? new { model = _config.Model, messages = new[] { new { role = "system", content = V2SystemPrompt }, new { role = "user", content = userMessage } }, stream = false }
: new { model = _config.Model, messages = new[] { new { role = "system", content = V2SystemPrompt }, new { role = "user", content = userMessage } }, max_tokens = _config.MaxTokens, temperature = _config.Temperature };
var json = JsonSerializer.Serialize(requestBody);
var request = new HttpRequestMessage(HttpMethod.Post, url);
request.Content = new StringContent(json, Encoding.UTF8, "application/json");
if (!string.IsNullOrEmpty(_config.ApiKey))
request.Headers.Add("Authorization", $"Bearer {_config.ApiKey}");
var response = await _http.SendAsync(request);
response.EnsureSuccessStatusCode();
var responseJson = await response.Content.ReadAsStringAsync();
using var doc = JsonDocument.Parse(responseJson);
if (_config.Provider == AIProvider.Local)
return doc.RootElement.GetProperty("message").GetProperty("content").GetString() ?? "";
return doc.RootElement.GetProperty("choices")[0].GetProperty("message").GetProperty("content").GetString() ?? "";
}
private async Task<string> CallClaudeAsync(string userMessage)
{
var url = $"{_config.BaseUrl.TrimEnd('/')}/v1/messages";
var requestBody = new
{
model = _config.Model,
max_tokens = _config.MaxTokens,
system = V2SystemPrompt,
messages = new[] { new { role = "user", content = userMessage } }
};
var json = JsonSerializer.Serialize(requestBody);
var request = new HttpRequestMessage(HttpMethod.Post, url);
request.Content = new StringContent(json, Encoding.UTF8, "application/json");
request.Headers.Add("x-api-key", _config.ApiKey);
request.Headers.Add("anthropic-version", "2023-06-01");
var response = await _http.SendAsync(request);
response.EnsureSuccessStatusCode();
var responseJson = await response.Content.ReadAsStringAsync();
using var doc = JsonDocument.Parse(responseJson);
return doc.RootElement.GetProperty("content")[0].GetProperty("text").GetString() ?? "";
}
private string BuildLegacyPrompt(ProcessInfo proc, List<SignatureMatch> matches,
List<MemoryRegion> suspiciousRegions)
{
var sb = new StringBuilder();
sb.AppendLine("=== PROCESS DATA ===");
sb.AppendLine($"PID: {proc.Pid}");
sb.AppendLine($"Name: {proc.Name}");
sb.AppendLine($"Path: {(string.IsNullOrEmpty(proc.ExePath) ? "unknown" : proc.ExePath)}");
sb.AppendLine($"Parent: {proc.ParentName} (PPID: {proc.Ppid})");
sb.AppendLine($"CommandLine: {proc.CmdLine}");
sb.AppendLine($"Signed: {proc.IsSigned}");
sb.AppendLine($"Signer: {(string.IsNullOrEmpty(proc.Signer) ? "-" : proc.Signer)}");
sb.AppendLine($"SystemPath: {proc.IsSystemPath}");
sb.AppendLine($"TempPath: {proc.IsTempPath}");
if (proc.Connections.Count > 0)
{
sb.AppendLine($"\nNetworkConnections ({proc.Connections.Count}):");
foreach (var c in proc.Connections.Take(8))
sb.AppendLine($" {c.Protocol} {c.LocalAddr} -> {c.RemoteAddr} [{c.State}]");
}
if (matches.Count > 0)
{
sb.AppendLine($"\nMemorySignatures ({matches.Count}):");
foreach (var m in matches.Take(10))
sb.AppendLine($" [{m.Severity}] {m.SigId} @ {m.Address}: {m.Description}");
}
if (suspiciousRegions.Count > 0)
{
sb.AppendLine($"\nSuspiciousMemoryRegions ({suspiciousRegions.Count}):");
foreach (var r in suspiciousRegions.Take(5))
sb.AppendLine($" 0x{r.BaseAddress:X} size={r.Size} protect={r.Protect} type={r.Type}");
}
sb.AppendLine("\n=== ANALYZE THIS PROCESS ===");
return sb.ToString();
}
private static ScanResult ParseLegacyResponse(ProcessInfo proc, string content)
{
content = content.Trim();
if (content.StartsWith("```"))
content = string.Join('\n', content.Split('\n')[1..^1]);
try
{
using var doc = JsonDocument.Parse(content);
var root = doc.RootElement;
var riskLevel = root.GetProperty("risk_level").GetString() switch
{
"high" => RiskLevel.High,
"suspicious" => RiskLevel.Suspicious,
_ => RiskLevel.Safe
};
var indicators = new List<string>();
if (root.TryGetProperty("indicators", out var indArr))
foreach (var ind in indArr.EnumerateArray())
indicators.Add(ind.GetString() ?? "");
return new ScanResult
{
Pid = proc.Pid,
ProcessName = proc.Name,
RiskLevel = riskLevel,
RiskScore = root.GetProperty("risk_score").GetDouble(),
Indicators = indicators,
Reasoning = root.GetProperty("reasoning").GetString() ?? "",
AIProvider = "llm-api-v2",
DetectionLayer = "LLM",
ScanTime = DateTime.Now
};
}
catch
{
return new ScanResult
{
Pid = proc.Pid,
ProcessName = proc.Name,
RiskLevel = RiskLevel.Safe,
RiskScore = 0,
Reasoning = content,
AIProvider = "llm-api-v2",
DetectionLayer = "LLM",
ScanTime = DateTime.Now
};
}
}
public async Task<(bool ok, string message)> TestConnectionAsync()
{
if (_config.Provider == AIProvider.Heuristic)
{
return _config.EnableLocalAI
? (true, "AI 管线模式 (Pipeline v2.0, 无需 API)")
: (true, "启发式规则模式 (Heuristic v2.0, 无需 API)");
}
try
{
await CallAIAsync("ping");
return (true, $"OK - {_config.Provider}/{_config.Model}");
}
catch (Exception ex) { return (false, ex.Message); }
}
private const string V2SystemPrompt = @"You are a Windows memory security expert (v2.0) analyzing process threat levels.
=== CORE PRINCIPLE ===
The VAST majority (>95%) of processes are SAFE. Default to ""safe"" unless you see CLEAR threat evidence.
=== CRITICAL FALSE POSITIVE PREVENTION ===
1. .NET/Java/Node.js/Chrome/V8 processes LEGITIMATELY use RWX memory for JIT compilation. This is NOT suspicious.
2. Security/EDR products legitimately inject/hook processes. Their RWX + injection API usage is NORMAL.
3. Development/debugging tools legitimately use Process inspection APIs.
4. A single indicator ALONE is never enough for ""high"" risk.
=== RISK LEVELS ===
""safe"": Normal benign process, even with minor deviations (< 0.30)
""suspicious"": Multiple weak signals or single strong signal (0.30-0.70)
""high"": Clear evidence with multiple concurring signals (> 0.70)
=== JSON RESPONSE ===
{""risk_level"":""safe"",""risk_score"":0.0,""indicators"":[],""reasoning"":""""}";
}