Automated Evidence Generation
Automated Evidence Generation is the cybersecurity process of using software, APIs, and scripts to instantly collect, contextualize, and preserve proof of security events, compliance status, or incident activities without human intervention. Instead of an analyst manually taking screenshots, downloading logs, or writing reports after an event, the system automatically captures this data as soon as a specific trigger occurs.
This capability transforms security from a reactive, manual discipline into a defensible, audit-ready operation. It ensures that every alert, policy violation, or compliance check is backed by immutable evidence that withstands regulatory scrutiny or forensic analysis.
Why Automated Evidence Generation is Critical
In modern security operations, "If it isn't documented, it didn't happen." However, the sheer volume of alerts makes manual documentation impossible.
Eliminates Human Error: It prevents analysts from forgetting to capture a critical log file or timestamp during the heat of an incident.
Ensures Chain of Custody: Automated systems cryptographically sign and timestamp evidence at the moment of collection, ensuring it hasn't been tampered with—a requirement for legal proceedings.
Accelerates Audit Cycles: It replaces the "mad scramble" before an audit with a continuous stream of evidence, reducing audit preparation time from weeks to minutes.
Reduces Mean Time to Respond (MTTR): With evidence (e.g., user login history or process trees) ready before an analyst opens the ticket, investigations can start immediately.
Core Components of the Process
Triggering: The system listens for a specific event, such as a SIEM alert (e.g., "Malware Detected"), a compliance check failure (e.g., "S3 Bucket Public"), or a scheduled audit interval.
Collection: APIs connect to relevant systems (EDR, Cloud, Identity Providers) to pull raw data. This includes system logs, configuration files, state snapshots, and user activity records.
Contextualization: The system enriches the raw data. For example, it doesn't just record "IP 1.2.3.4 connected"; it adds "IP 1.2.3.4 is a known Tor exit node."
Preservation: The evidence is bundled, hashed, and stored in a tamper-evident repository (like WORM storage—Write Once, Read Many) to prevent alteration.
Use Cases for Automated Evidence Generation
1. Compliance and Auditing
Instead of manually checking if firewalls are on, an automated system queries the firewall configuration daily. It generates a timestamped JSON file that proves the firewall was active on that specific day, satisfying evidence requirements for frameworks such as SOC 2, ISO 27001, and PCI DSS.
2. Incident Response (IR)
When an endpoint detection system flags a suspicious file, automated evidence generation kicks in immediately to:
Dump the process memory.
Capture the user's browser history.
Record the network connections active at that second. This "snapshot" preserves the crime scene before the attacker can erase their digital traces.
3. Phishing Investigations
When a user reports a phishing email, automation instantly generates evidence by:
Taking a screenshot of the phishing landing page (in a safe sandbox).
Extracting and hashing any attachments.
Recording the WHOIS data of the sender's domain.
Common Questions About Automated Evidence Generation
Is automated evidence admissible in court? Generally, yes, provided the system can demonstrate a reliable "Chain of Custody." The automation must show exactly when the data was captured, how it was stored, and that it has not been modified since collection.
Does this replace the need for human analysts? No. It replaces the administrative work of analysts. Humans are still needed to interpret the evidence and make decisions. Automation just ensures they have all the data they need instantly.
Can it work with legacy systems? It depends on the tool. Modern automation relies heavily on APIs. Legacy systems without APIs may require agent-based collectors or screen-scraping scripts, which are more brittle and harder to maintain.
What is the difference between Logging and Evidence Generation? Logging is the continuous stream of all events (noise). Evidence Generation is the targeted capture and preservation of specific logs and artifacts relevant to a security incident or audit requirement (signal).
Streamlining Automated Evidence Generation with ThreatNG
ThreatNG transforms the labor-intensive process of manual data collection into a streamlined, automated operation. By continuously scanning, assessing, and archiving data from the external attack surface, ThreatNG generates defensible, timestamped evidence that organizations use for compliance audits, incident response, and legal takedowns. It ensures that every security decision is backed by immutable proof of the external environment's state at any given moment.
External Discovery
ThreatNG automates the creation of a comprehensive "Asset Inventory Evidence" trail. For auditors and regulators, simply claiming to know one's assets is insufficient; ThreatNG provides the proof.
Audit-Ready Inventory: The solution scans the internet to generate a complete, timestamped list of all digital assets (subdomains, cloud buckets, IP addresses) owned by the organization. This serves as automated evidence of "Asset Management" controls for frameworks such as ISO 27001 and the CIS Controls.
Shadow IT Documentation: ThreatNG discovers unauthorized assets, such as rogue marketing sites or forgotten development servers. The detection log serves as evidence of the governance gap, allowing security teams to prove when an asset appeared and who (via registrar or cloud provider data) likely deployed it.
External Assessment
ThreatNG converts raw discovery data into "Vulnerability Evidence" by performing technical assessments that validate the security posture of each asset.
Detailed Example (Compliance Violation Evidence): ThreatNG assesses a payment gateway subdomain and detects that it is negotiating TLS 1.0 connections (an insecure protocol). The system automatically captures the server's SSL handshake response and the specific cipher suites offered. This technical artifact serves as irrefutable evidence of non-compliance with PCI DSS requirements and can be attached to a remediation ticket or audit finding.
Detailed Example (Brand Infringement Evidence): When ThreatNG identifies a typosquatted domain (e.g.,
secure-bank-login.net), it performs a visual and structural assessment. It captures a high-resolution screenshot of the site, downloads the HTML source code to identify cloned branding elements, and records the DNS resolution path. This "Evidence Package" is automatically generated, providing the legal team with the evidence needed to demonstrate "intent to deceive" without requiring an analyst to manually visit the malicious site.
Reporting
ThreatNG serves as the central repository for generated evidence, producing reports that are formatted for specific stakeholders, from technical teams to external auditors.
Compliance Artifact Generation: ThreatNG generates PDF and CSV reports that map external findings to specific regulatory controls. These reports act as "point-in-time" evidence that the organization was monitoring its perimeter and managing risks in accordance with policy.
Executive Due Diligence Reports: For M&A or board meetings, ThreatNG produces high-level summaries that serve as evidence of the organization's cyber health trends. These reports document the reduction of risk over time, proving the ROI of security investments.
Continuous Monitoring
Security is dynamic, and evidence must capture changes as they happen. ThreatNG’s continuous monitoring creates a "Chain of Custody" for digital events.
Drift Evidence: If a firewall rule is changed and an RDP port opens at 3:00 AM, ThreatNG detects and timestamps this event immediately. This log serves as evidence for the Root Cause Analysis (RCA), demonstrating exactly when the exposure began and refuting claims that "nothing changed."
Remediation Verification: Once a vulnerability is patched, ThreatNG re-scans the asset and generates a new record showing the issue is resolved. This "Evidence of Remediation" is critical for closing audit findings and lowering cyber insurance premiums.
Investigation Modules
ThreatNG’s investigation modules enable analysts to generate in-depth forensic evidence on specific threats or exposures.
Detailed Example (Domain Intelligence Investigation): When investigating a suspicious external IP address that connects to the network, this module automatically retrieves passive DNS history, WHOIS registration data, and hosting reputation. It compiles a "Reputation Dossier" as evidence that the IP address belongs to a known Bulletproof Hosting provider rather than a legitimate business partner. This evidence justifies immediately blocking the IP address at the firewall.
Detailed Example (Sensitive Code Exposure): If confidential API keys are leaked, the Sensitive Code Exposure module locates the specific repository and commit hash. It captures a snippet of the exposed code (redacted for security) and the committer metadata. This serves as forensic evidence for the incident response team to prove that a credential compromise occurred and to identify the developer responsible for the leak, facilitating targeted training or disciplinary action.
Intelligence Repositories
ThreatNG enriches generated evidence with third-party intelligence, adding the context needed to make it actionable and high-priority.
Dark Web Corroboration: ThreatNG matches discovered assets with Dark Web chatter. If an employee email is found in a breach dump, ThreatNG captures the metadata of the dump (date, source, size). This serves as evidence that the credential is not just "weak" but "compromised," necessitating an immediate forced password reset.
Ransomware Attribution: By correlating open ports with known Ransomware TTPs, ThreatNG generates evidence that an asset is a likely target. This "Targeting Evidence" helps prioritize patching efforts by proving the asset is in the crosshairs of active threat groups.
Complementary Solutions
ThreatNG acts as the "Evidence Factory" for the broader security stack, feeding validated proof into systems that enforce policy and manage workflows.
Complementary Solution (GRC Platforms): ThreatNG pushes automated evidence of asset security (e.g., SSL scores, open port counts) directly into Governance, Risk, and Compliance (GRC) platforms. This replaces manual data entry, ensuring the GRC dashboard always reflects the evidence-based state of the environment.
Complementary Solution (SOAR Platforms): ThreatNG feeds "Evidence Packages" (screenshots, DNS records, source code) into Security Orchestration, Automation, and Response (SOAR) playbooks. The SOAR system uses this evidence to automatically generate comprehensive incident tickets, allowing analysts to review the evidence and approve a takedown or block without manually gathering data.
Complementary Solution (Legal & Brand Protection Services): ThreatNG provides the forensic data required by legal teams and external brand protection vendors. The automated evidence—including time-stamped screenshots and WHOIS history—is used to file Uniform Domain-Name Dispute-Resolution Policy (UDRP) complaints and Cease and Desist orders.
Examples of ThreatNG Helping
Helping Pass a SOC 2 Audit: ThreatNG helped an organization demonstrate an accurate asset inventory by generating a timestamped export of all external subdomains and cloud services. This automated evidence satisfied the auditor's requirement for "External Attack Surface Visibility" without requiring manual spreadsheets.
Helping Expedite a Takedown: A retail company used ThreatNG to detect a phishing site minutes after it went live. ThreatNG automatically generated an evidence package containing the phishing site's IP, hosting provider, and a screenshot of the fraudulent login page. This instant evidence allowed the hosting provider to verify the abuse and suspend the site within an hour.
Helping Prove Due Diligence in M&A: During an acquisition, ThreatNG generated evidence that the target company had several unpatched servers exposed to the internet. This report served as factual evidence during negotiations, allowing the acquiring firm to adjust the valuation based on the documented technical debt.
Examples of ThreatNG Working with Complementary Solutions
Working with a SIEM: ThreatNG detects a new "Shadow IT" server and generates evidence of its configuration. It sends this log to the SIEM, which correlates it with internal network traffic. The combined evidence proves that internal users are actively connecting to an unmanaged, insecure asset, triggering an automated alert to the security operations center.
Working with Vulnerability Management: ThreatNG identifies external assets not included in the vulnerability scanner's target list. It exports this "Missing Asset Evidence" to the Vulnerability Management system, ensuring the scanner updates its scope to include these overlooked risks in the next scheduled scan.
