Adversarial Exposure Validation
Adversarial Exposure Validation (AEV) is a proactive, continuous cybersecurity framework that tests and validates an organization's security posture by safely emulating the tactics, techniques, and procedures (TTPs) of real-world threat actors. Its fundamental goal is to move beyond simply identifying theoretical vulnerabilities to providing empirical evidence that exposures are actually exploitable within the unique context of a target environment.
Methodology and Attacker Simulation
AEV works by automating and orchestrating sophisticated, multi-stage attack scenarios that mirror genuine adversary behavior. It consolidates elements from multiple traditional testing methods into a continuous process:
Reconnaissance and Discovery: The process begins by continuously mapping the external attack surface to identify all exposed assets, services, and misconfigurations, just as a hacker would.
TTP Emulation: AEV tools replicate known attacker behaviors, often leveraging frameworks like MITRE ATT&CK®. This involves exploiting weaknesses such as misconfigured systems, unpatched software, and weak credentials.
Attack Path Validation: The most crucial step is proving the feasibility of a complete attack chain. AEV simulates how an attacker could chain multiple low-severity exposures (e.g., a misconfigured API, a leaked token, and a weak server patch) to achieve a high-impact objective, such as lateral movement or data exfiltration.
Value in Risk Prioritization
AEV transforms risk management by providing clarity and confidence to security teams.
Focus on Exploitability: It eliminates "vulnerability fatigue" by filtering out theoretical or low-impact findings that cannot actually be compromised. The security team can then focus remediation efforts on the issues that are demonstrably exploitable and pose the highest risk to critical business assets.
Security Control Validation: The process continuously tests whether existing security controls—such as firewalls, intrusion prevention systems, and endpoint detection and response (EDR) solutions—are actually capable of detecting and preventing attacks, not just in theory, but in the live production environment.
AEV is considered a core component of a Continuous Threat Exposure Management (CTEM) strategy, providing the ongoing, evidence-based validation needed to adapt defenses to the evolving threat landscape dynamically.
ThreatNG is exceptionally effective at providing foundational Adversarial Exposure Validation (AEV) intelligence by continuously assessing an organization's attack surface, which directly informs and guides automated attack simulations. It identifies and verifies the publicly exposed vulnerabilities and credentials that attackers (the "adversaries") use as initial access points.
ThreatNG's Role in Adversarial Validation
External Discovery and Continuous Monitoring
ThreatNG provides the initial, crucial step for AEV: Discovery and Inventory. It performs purely external, unauthenticated discovery, which is key because any successful external AEV scenario must first locate the target asset. This mirrors the adversary's reconnaissance phase and prevents security teams from operating with blind spots (Shadow IT).
The platform’s Continuous Monitoring ensures this discovery remains up to date. Suppose a new server is deployed or a credential is compromised (creating a new entry point for an adversary). In that case, ThreatNG detects it immediately, allowing security teams to validate and remediate the exposure before a scheduled test or a real attack.
External Assessment and Examples
ThreatNG's ratings quantify the susceptibility of the organization to an adversarial attack, helping to prioritize which exposures should be validated first:
Non-Human Identity (NHI) Exposure Security Rating: This metric assesses the risk of attackers using leaked credentials for initial access and lateral movement, a key part of any adversarial simulation.
Example: The discovery of a hardcoded AWS Access Key ID or a GitHub Access Token confirms an exploitable exposure. In an AEV program, this exposed key would serve as the initial credential to test how far the adversary could move laterally within the cloud environment.
Subdomain Takeover Susceptibility: This checks for a critical external vulnerability that attackers frequently exploit to gain initial access.
Example: ThreatNG identifies a sub-domain pointing to an unclaimed WordPress service, validating a "dangling DNS" state. An AEV tool can then simulate the takeover to confirm whether it can host malicious content or steal session cookies, thereby proving the exploit's exposure.
Cyber Risk Exposure: This rating includes checks for external misconfigurations that enable adversarial access, such as Exposed Ports and Missing Headers.
Example: ThreatNG discovers a publicly exposed RDP port (TCP 3389). This external finding validates the exposure, allowing the AEV tool to run a simulated brute-force attack against that port to validate the effectiveness of the underlying Windows security policy.
Investigation Modules and Examples
The investigation modules provide the specific, actionable TTP (Tactics, Techniques, and Procedures) context that AEV requires:
Sensitive Code Exposure: This module directly identifies the secrets that fuel AEV scenarios. The Code Repository Exposure submodule pinpoints the exact location of Access Credentials and Security Credentials.
Example: Finding a leaked PGP private key block provides an attacker with a high-privilege credential, which an AEV tool can safely use to test the lateral movement phase of the simulation.
Technology Stack: ThreatNG discovers the organization's technology stack (e.g., Jenkins, Docker, Apache). This context allows AEV tools to select the most relevant and practical exploit scenarios based on known vulnerabilities for that specific software.
External GRC Assessment: This capability provides evidence to validate compliance controls by assessing exposed assets against frameworks such as PCI DSS and NIST CSF.
Intelligence Repositories and Reporting
ThreatNG enhances the validation process with threat-informed context:
Vulnerabilities (DarCache Vulnerability): This repository integrates KEV (vulnerabilities actively being exploited) and EPSS (likelihood of exploitation) data. This allows the security team to prioritize validation efforts on exposed assets that align with real-world threat actor TTPs, focusing AEV resources where they matter most.
Compromised Credentials (DarCache Rupture): This confirms if a discovered exposure has already been compromised on the dark web. This linkage provides a maximum-priority signal for AEV, validating that the exposure is actively targeted.
Reporting: ThreatNG provides Security Ratings and Prioritized Reports with Legal-Grade Attribution, converting the initial discovery into verifiable evidence to guide AEV and remediation efforts.
Complementary Solutions
ThreatNG’s external intelligence forms the necessary feed for internal AEV and security tools:
Breach and Attack Simulation (BAS) Platforms: ThreatNG identifies a publicly exposed vulnerability (the door). This finding can be automatically fed to a BAS platform. The BAS platform can then use that validated external finding as the starting point to execute the internal simulation (lateral movement, data exfiltration), testing the detection and response of the security controls.
Security Orchestration, Automation, and Response (SOAR) Platforms: A critical alert from ThreatNG confirming a Sensitive Code Exposure provides high-certainty evidence. The SOAR platform can automatically use this alert to trigger a pre-defined playbook, instantly revoking the exposed credential and initiating a forensic clone of the compromised repository.
Cloud Security Posture Management (CSPM) Tools: ThreatNG’s external discovery of a high-risk misconfiguration (e.g., an Open Exposed Cloud Bucket) can be shared with a CSPM tool. The CSPM tool can then use this external proof to trigger an immediate, authenticated internal scan and remediation workflow for that specific cloud asset.
