Guest author: Or Hillel, Green Lamp

Applications have become the foundation of how organisations deliver services, connect with customers, and manage important operations. Every transaction, interaction, and workflow runs on a web app, mobile interface, or API. That central role has made applications one of the most attractive and frequently-targeted points of entry for attackers.

As software grows more complex, spanning microservices, third-party libraries, and AI-powered functionality, so do the security risks. Traditional scanning methods struggle to keep up with rapid release cycles and distributed architectures. This has opened the door for AI-driven application security tools, which bring automation, pattern recognition, and predictive capabilities to a field that once relied heavily on manual reviews and static checks.

Best practices for using AI AppSec tools

To get the most value from AI-powered application security, teams should follow some key best practices:

1. Shift security left: Integrate tools early in the SDLC so issues are caught before production.
2. Combine approaches: Use AI tools alongside traditional SAST, DAST, and manual reviews to cover all bases.
3. Enable continuous learning: Choose solutions that improve over time by ingesting threat intelligence and user feedback.
4. Keep humans in the loop: AI should augment, not replace, human judgment. Security experts are still needed for complex decision-making.
5. Align with compliance: Ensure AI-powered findings can be mapped to regulatory requirements like SOC 2, HIPAA, or GDPR.

The 5 best AI-powered AppSec tools of 2025

1. Apiiro

Apiiro is reinventing the way organisations assess and manage risk in the modern software supply chain. It moves beyond legacy scanning to implement true risk intelligence, offering full-stack, contextual analysis powered by deep AI.

Apiiro brings visibility not only to what vulnerabilities exist in code and dependencies, but also to how changes, developer actions, and business context interact to shape risk. Its AI systems process data from source control, CI/CD pipelines, cloud configurations, and user access patterns, allowing it to prioritise remediation based on business impact.

2. Mend.io

Mend.io has rapidly evolved into a cornerstone of the AI-driven AppSec ecosystem, addressing the full spectrum of risks facing software teams today. Using machine learning and advanced analytics, Mend.io is purpose-built to handle the security challenges of code produced by both humans and artificial intelligence.

Leading organisations are attracted to Mend.io’s unified platform, which delivers seamless coverage for source code, open source, containers, and AI-generated functional logic. Its capabilities extend far beyond detection, enabling rapid, automated, and context-rich remediation that saves engineering time and reduces business exposure.

3. Burp Suite

Burp Suite has long been a foundational tool for web application security professionals, but its latest AI-driven evolution makes it essential for defending cutting-edge app landscapes. Today, Burp Suite combines traditional manual penetration testing strengths with sophisticated machine learning, delivering smarter scanning and deeper insight than ever before.

Where legacy DAST (Dynamic Application Security Testing) tools might struggle with modern, dynamic, or API-rich applications, Burp Suite’s AI modules adapt to changes in real time, learning from traffic patterns and user behaviours to uncover anomalies and hard-to-spot vulnerabilities.

4. PentestGPT

PentestGPT represents the future of automated offensive security, using generative AI to simulate the tactics of contemporary adversaries. Unlike pattern-based scanners, PentestGPT can devise new attack paths, generate custom payloads, and think creatively about bypassing controls and protections.

PentestGPT blends autonomous testing with educational support: security analysts, testers, and developers can interact with the platform conversationally, gaining hands-on guidance for complex scenarios and real-world exploit development.

5. Garak

Garak is an emerging leader specialising in security for AI-driven applications, specifically, large language models, generative agents, and their integration into wider software systems. As organisations increasingly embed AI into customer interactions, business logic, and automation, new risks have arisen that traditional AppSec tools simply weren’t built to address.

Garak is designed to probe and harden these AI-infused interfaces, ensuring models respond safely and preventing AI-specific exploits like prompt injections and privacy breaches.

Core features of AI-driven AppSec tools

While not every solution offers the same features, most AI-powered application security tools share several core capabilities:

1. Intelligent vulnerability detection

AI models trained on massive datasets of known exploits can spot coding errors, misconfigurations, and insecure dependencies more accurately than static rule-based tools. They adapt over time, improving detection with each new dataset.

2. Automated remediation guidance

One of the major pain points in AppSec is not just finding vulnerabilities but knowing how to fix them. AI tools can generate remediation advice tailored to the specific context, often offering code suggestions or step-by-step fixes.

3. Continuous monitoring and real-time analysis

Instead of one-time scans, AI-powered tools continuously monitor applications in production. They analyse runtime behaviour, API calls, and data flows to spot anomalies that could indicate an active attack.

4. Risk prioritisation

AI can evaluate the severity of each vulnerability based on exploitability, business impact, and external threat intelligence. The ensures that teams focus on the issues most likely to cause real damage.

5. Integration with DevOps workflows

Modern AppSec tools embed directly into CI/CD pipelines, issue trackers, and developer environments. AI accelerates these processes by automating tasks that previously slowed down builds or required manual oversight.

Building resilient software in an AI world

AI-powered application security is not a single tool, process, or department, it’s the foundation on which resilient, innovative, and trusted software is built. In 2025, the leaders in this space are not just those who scan for vulnerabilities, but those who can learn, adapt, and protect at the velocity of AI-driven innovation.

From comprehensive risk intelligence and agile remediation to the defense of AI-generated code and AI agents themselves, today’s AppSec solutions are reshaping what’s possible, and what’s necessary, for digital security in any industry.

Guest author: Or Hillel, Green Lamp