Solving Application Security Challenges With AI-Powered Agents
Agentic AI involves using artificial intelligence agents to autonomously perform tasks and solve problems, and it has many exciting use cases in application security. Agentic AI can be used to generate tailored reports, run threat models before and after a significant release, and support developers with code reviews and security training. AI agents help over-stretched AppSec and DevSecOps engineers with the most tedious manual tasks in their workflows, enabling faster remediation and more secure software.
Agentic AI’s Potential to Transform AppSec
AI agents can be used for numerous application security tasks that typically require tedious manual work. Examples include:
Reporting
Agentic AI can generate specific, tailored reports on application security that align with specific compliance standards, such as SOC 2, PCI, or HIPAA. Rather than manually sorting through data from various security scanners to pull the specific information needed for compliance reporting, AppSec engineers can have an AI agent automatically perform the same task in a matter of minutes.
Threat Modeling
Agentic AI can run threat models before and after the release of a major feature to help the AppSec team better understand what the specific architectural security risks could be. An AI agent can perform threat modeling much faster than human engineers to reduce the impact on ultra-tight development timelines.
Code Reviews
Agentic AI can also support development teams by providing automatic code reviews and integrated code security training. It can evaluate specific code changes in pull requests and security best practices and provide very fast feedback on the security of new code within the context of the larger code base.
Remediation Recommendations
When an AI agent detects a vulnerability in code, it can provide steps for a developer to take to resolve the issue, streamlining the remediation process. These recommendations can be tailored to the context of the runtime environment and the specific compliance requirements. Agents can also provide multiple options for developers to choose from depending on the context of the situation.
Why Development and Security Teams Are Turning to Agentic AI
Application security and DevSecOps engineers have extremely hectic lives, with a never-ending backlog of problems to manage. In addition to triaging security issues and assigning them to the relevant team, they’re also responsible for understanding the potential security risks of new features within the larger product. They perform threat modeling to proactively seek out security weaknesses in the architecture of the application, and also conduct developer training and awareness programs to help development teams understand code security best practices. They’re constantly drowning in all of these different tasks that often involve very tedious manual work, especially when it comes to assessing the risks of services, and understanding what vulnerabilities need to be resolved.
Agentic AI can be extremely helpful in offloading a lot of the manual work needed to secure applications. AI agents excel at automating the really tedious stuff that bogs down human engineers, such as understanding the top risks in a hundred different services very quickly, and providing the compliance context for each risk. They free up valuable time for overworked AppSec teams so that humans can focus on making critical security decisions.
The Benefits and Drawbacks of Agentic AI in AppSec
As discussed above, the primary benefit of agentic AI for application security teams is the time saved on tedious, manual work. This in turn means that issues are resolved faster, allowing development teams to release secure software at a much quicker pace. Agentic AI’s threat modeling capabilities also help AppSec teams proactively identify risks with greater speed and accuracy, streamlining the development process while improving application security.
One hurdle to successful adoption is that AI agents need to train on large quantities of data to be able to tell an AppSec team why certain security issues matter in the context of everything else happening in the organization. They need access to data from ticket management systems, cloud environments, network traffic, and access control systems, for example. Handling all these integrations can be tricky, and this level of access must be managed securely to prevent sensitive data exposure.
A major drawback is a lack of trust in AI agents from developers and AppSec engineers. It’s important to recognize that agentic AI isn’t meant to solve all security use cases, and keep humans in the loop. It’s inadvisable to let AI agents automatically make code fixes and push updates without developer intervention. Rather, agentic AI should provide multiple ideas and options for developers to resolve issues themselves.
Learn More About AppSec Automation With Jit
Jit is an AppSec automation tool designed to empower developers to remediate security issues with a streamlined, integrated experience. It unifies all the security scanners needed for secure development in a single platform, including built-in SAST, secrets detection, DAST, and SBOM. Jit’s Context Engine helps development teams prioritize and focus on high-risk issues while filtering out the noise. Its dev-native UX empowers developers to resolve issues with features like change-based scanning and automatic fix suggestions. Jit’s dashboards make it easy for dev teams to monitor the security posture of their services and prioritize risks, and its Security Plans help align product security with business objectives like SOC2 compliance or Minimum Viable Security. Plus, Jit easily integrates with all the tools in your pipeline to provide a simplified developer experience.
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