
Cybersecurity involves playing a good guy and a bad guy. It dives deep into advanced technology and still erroneously proceeds on the dark web. Defining technical policy and profiling attacker behavior. Security teams cannot focus solely on ticking boxes. They need to live in the mindset of attackers.
This is where AEVs appear.
AEV (hostile exposure verification) is an advanced criminal technique that provides repair strategies while mimicking how enemies attack a system. This allows you to discover and address dynamically and continuously how your environment will be utilized and what the impact of exploitation is.
In this article, we share everything you need to know about AEVs and how teams can use it to build ongoing resilience to attacks.
What is an AEV?
According to the Gartner® Market Guide for Hostile Exposure Verification (March 2025), AEVs are defined as “a technology that provides consistent, continuous, automated evidence of the feasibility of an attack.” AEVs operate by emulating cyberattacks, providing organizations with an understanding of how attackers can infiltrate their networks. This allows organizations to take relevant security measures to effectively correct security gaps.
AEV technology effectively integrates previously isolated security testing methods, such as automated penetration testing and BAS (violation and attack simulation). Gartner says, “As the two markets were developed and the overlapping capacity increased, the two functions converged to unite attack technology.”
The focus of AEVs is to replicate the way they think of their real enemy. By combining the breadth of automated pen tests with the impact-driven focus of BAS, AEV allows for continuous testing that reflects how real attackers adapt over time. Organizations can continually emulate how attackers behave, providing more insightful reviews of vulnerabilities and ways to best correct them.
How AEVs Support Exposure Management
AEV has emerged as a technical solution to support CTEM (Continuous Threat Exposure Management) practices. CTEM is a comprehensive program that helps organizations identify vulnerabilities and exposures, determine risk profiles for their digital assets, prioritize risk mitigation, and monitor remediation.
Here’s how AEVs can promote CTEM:
Filtering Mechanism – Instead of generating a large list of common findings, AEVs narrow down vulnerabilities that have actually been found to be exploitable. A process that checks the legitimacy of security issues and assesses whether threat actors have easy access to them. This approach is much more efficient than all traditional patching methods, as it flags only the most risky issues. In the process, we identify exposures that are benign and do not actually guarantee repair. Continuous nature – Continuous and frequent automated testing of AEVs, rather than one-off events or short engagement, supports the continuous feedback loop of CTEM for discovery, testing and repair. This helps ensure a constant state of ready for attacks, even in the face of new threat techniques, as IT environments change and new software misunderstandings arise. Actual Testing – Staging environments often fail to accurately represent the actual conditions that attackers exploit the environment. These include misunderstandings, dormant user accounts, data anomalies, and complex integrations. Some Best Bleed AEV tools deal with this by safely testing them in production environments, making them much more accurate and effective at identifying vulnerabilities that can lead to disastrous effects. Repair Beyond Patching – In addition to patching exploitable CVEs, AEVs identify non-patchable vulnerabilities in repairs, such as exchanging exposed credentials, implementing minimum privilege principles, correcting misconceptions, and replacing unstable third-party software. This is consistent with CTEM remediation guidance, and it collectively calls for less exposure to potential threats and risks.
Red Team AEV
AEVs automatically identifies how attackers chain multiple vulnerabilities across different environments. This makes it a staple of the Red Teamer’s Toolkit.
With AEV, red teams can model offensive scenarios more easily. This includes complex things like hopping between cloud infrastructure and on-plame systems, pivoting through various network segments, overcoming existing controls and combining low-scoring exposures with full-scale violations.
Equipped with information provided by AEVs, Red teams will have a clear view of how determined attackers move sideways, allowing them to scale effort and rapid mitigation. For organizations, AEVs ensure cost-effective red teaming, allowing entry-level red teamers to deliver quality results. Genai is expected to further strengthen this by providing ideas and explanations for complex attack scenarios.
AEV for the Blue Team
For the Blue Team, the AEV is off to a strong start. With AEVs, defenders can see which protections are really robust, need to be strengthened, and which controls are actually redundant in the face of attack. This ensures that the defender uses trend analysis to ensure that the security attitude is working best to show that the program works as expected.
Blue Teams can use AEVS insights and data.
Detection Stack Tuning Prevention Posture Change Exposure Prioritization Service Provider Performance Verification Security Vendor Performance Scorecard Improved Other Operations or Controls
AEV for security resilience
AEVs are designed to provide a continuous, automated, realistic simulation of how attackers can leverage the weaknesses of organizational defenses. It’s no wonder it’s quickly emerging as a key cybersecurity technology. With AEV, security teams have obtained proven verification of how exposure in their environment is exploited and what is finished, allowing for faster paced smarter prioritization and effective remediation. This required clarity is key to promoting cyber resilience.
For more information on how AEVs are implemented and their role in the broader CTEM practices, please register to attend Xposure, Pentera’s exposure management summit.
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