Analysieren Sie KI-integrierte XDR-Anbieter und erstellen Sie einen Excel-Bericht

import pandas as pd from openpyxl import Workbook from openpyxl.styles import Font, Alignment, PatternFill from openpyxl.utils import get_column_letter # Data structure: [Company, Products with AI, Unique Differentiator, AI Handling of Telemetry with Example] data = [ ["Cato Networks", "Cato XDR (part of Cato SASE Cloud)", "AI is embedded in the cloud-native SASE architecture, analyzing network and security telemetry in a single inline path without requiring additional sensors.", "AI correlates raw network flows, DNS queries, and endpoint events in real time. Example: Detects a DNS tunneling beacon by analyzing frequency and entropy of queries, then automatically blocks the domain and isolates the infected host."], ["Cisco", "Cisco XDR (with SecureX and Secure Analytics)", "Leverages Cisco Talos threat intelligence and integrates AI across network, endpoint, and cloud telemetry with a focus on automated response via SecureX orchestration.", "AI uses behavioral models on NetFlow and endpoint process data to identify anomalies. Example: Spikes in outbound SMB traffic from a workstation trigger an AI model that flags potential data exfiltration, then auto-creates a quarantine policy."], ["CrowdStrike", "Falcon XDR (with Falcon Insight, Falcon OverWatch)", "Uses the CrowdStrike Threat Graph with graph-based AI to correlate trillions of events per day, and its OverWatch team augments AI with human threat hunting.", "AI builds a behavioral baseline for each endpoint and uses graph analytics to link seemingly unrelated events. Example: A PowerShell script spawning from a document is correlated with a rare parent process and a known adversary technique, triggering an automated containment action."], ["Elastic Security XDR", "Elastic Security (with Elasticsearch and ML)", "Open and extensible platform where AI/ML models are built on the Elastic Stack, allowing custom anomaly detection and natural language search queries.", "AI uses unsupervised ML on normalized ECS data (process, network, file) to detect outliers. Example: A sudden increase in failed logins from a new geolocation combined with unusual process creation is flagged as a credential stuffing attempt, and the user is prompted for MFA."], ["Fortinet", "FortiXDR (with FortiAI and FortiAnalyzer)", "Integrates AI across the Fortinet Security Fabric, using FortiAI for on-premise deep learning and automated playbooks that span network, endpoint, and email.", "AI fuses telemetry from FortiGate firewalls, FortiEDR, and email gateways. Example: A malicious macro in an email attachment is detected by AI, which then automatically blocks the sender, quarantines the file on all endpoints, and updates IPS signatures."], ["Google Cloud (Mandiant Advantage XDR)", "Mandiant Advantage XDR (with Google Cloud Security AI Workbench)", "Combines Mandiant frontline expertise with Google's Gemini AI models, providing generative AI for investigation summaries and natural language threat hunting.", "AI ingests telemetry from Google Chronicle and third-party sources, using Gemini to summarize complex attack chains. Example: A user asks in natural language 'show me all lateral movement in the last hour', and AI generates a graph of compromised hosts with recommended containment steps."], ["Microsoft (Microsoft 365 Defender XDR)", "Microsoft 365 Defender (with Copilot for Security)", "AI is deeply integrated across identity, endpoint, email, and cloud apps, with Copilot providing generative AI assistance for incident response and hunting.", "AI uses Microsoft's Intelligent Security Graph to correlate signals from Azure AD, Defender for Endpoint, and Office 365. Example: A risky sign-in from a Tor exit node combined with a suspicious email forwarding rule triggers AI to automatically disable the user account and reset sessions."], ["Palo Alto Networks", "Cortex XDR (with Cortex XSIAM and AIOps)", "Uses a data lake approach with AI-driven detection and response, and its XSIAM platform automates data ingestion and uses AI for root cause analysis.", "AI processes petabytes of raw telemetry (endpoint, network, cloud) using deep learning models. Example: A rare combination of a scheduled task creation and a new DLL loaded in a critical server is flagged as a potential persistence mechanism, and AI automatically rolls back the changes."], ["SentinelOne", "Singularity XDR (with Purple AI)", "Purple AI provides a natural language interface for threat hunting and automated response, with a focus on autonomous endpoint protection and real-time AI models.", "AI uses behavioral AI on endpoint telemetry (process, network, file) with storylines that group related events. Example: A ransomware attack is detected by AI observing mass file encryption patterns, then it automatically kills the process and restores files from shadow copies."], ["Sophos", "Sophos XDR (with Sophos AI and MTR)", "AI is embedded in the Sophos Central platform, with managed threat response (MTR) analysts using AI to prioritize alerts and automate remediation.", "AI correlates telemetry from Sophos Intercept X, firewall, and email. Example: A phishing email with a malicious link is clicked, AI detects the subsequent C2 beacon via network telemetry, and automatically blocks the domain and isolates the endpoint."], ["Symantec", "Symantec XDR (with Symantec AI and EDR)", "Part of Broadcom, uses AI across its integrated cyber defense platform, focusing on web, email, and endpoint telemetry with a strong reputation engine.", "AI uses a global threat intelligence feed and behavioral analytics. Example: A zero-day exploit attempt is detected by AI analyzing unusual API calls in a browser process, then it automatically blocks the exploit and quarantines the file."], ["Trellix", "Trellix XDR (with Trellix AI and MVISION)", "Combines AI with human expertise from Trellix Labs, using a single agent for endpoint and network telemetry, and emphasizes automated threat containment.", "AI uses supervised and unsupervised learning on telemetry from MVISION EDR and network sensors. Example: A lateral movement attempt using SMB is detected by AI correlating multiple failed logins and a new service creation, then it automatically blocks the source IP."], ["VMware Carbon Black Cloud XDR", "Carbon Black Cloud XDR (with VMware Contexa)", "Uses VMware Contexa threat intelligence and AI to provide cross-cloud visibility, with a focus on endpoint telemetry and integration with VMware NSX for network segmentation.", "AI analyzes endpoint process and network telemetry, using Contexa to enrich with global threat context. Example: A suspicious process communicating with a known malicious IP is flagged, and AI automatically applies a micro-segmentation policy to isolate the workload."] ] # Create DataFrame df = pd.DataFrame(data, columns=["Company", "Products with AI", "Unique Differentiator", "AI Handling of Telemetry with Example"]) # Clean text: remove brackets, quotes, and HTML tags def clean_text(text): text = text.replace("{", "").replace("}", "") text = text.replace("'", "").replace('"', "") text = text.replace("<", "").replace(">", "") return text df = df.applymap(clean_text) # Write to Excel with formatting output_file = "AI_XDR_Vendor_Comparison.xlsx" with pd.ExcelWriter(output_file, engine="openpyxl") as writer: df.to_excel(writer, sheet_name="AI XDR Vendors", index=False) # Get workbook and worksheet workbook = writer.book worksheet = writer.sheets["AI XDR Vendors"] # Set column widths column_widths = [20, 35, 50, 60] for i, width in enumerate(column_widths, 1): worksheet.column_dimensions[get_column_letter(i)].width = width # Style header row header_font = Font(bold=True, size=12, color="FFFFFF") header_fill = PatternFill(start_color="1F4E78", end_color="1F4E78", fill_type="solid") for col in range(1, 5): cell = worksheet.cell(row=1, column=col) cell.font = header_font cell.fill = header_fill cell.alignment = Alignment(horizontal="center", vertical="center") # Style data rows data_font = Font(size=11) for row in range(2, len(df) + 2): for col in range(1, 5): cell = worksheet.cell(row=row, column=col) cell.font = data_font cell.alignment = Alignment(vertical="top", wrap_text=True) # Add alternating row colors alt_fill = PatternFill(start_color="D9E1F2", end_color="D9E1F2", fill_type="solid") for row in range(2, len(df) + 2): if row % 2 == 0: for col in range(1, 5): worksheet.cell(row=row, column=col).fill = alt_fill print(f"Excel file created: {output_file}")