StackHawk Launched Wingman for AI Code Security
The new tool automates vulnerability remediation within AI-assisted coding environments to resolve security gaps.
Updated on Sept. 24, 2026 in Cybersecurity
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StackHawk has released Wingman, a security tool designed to identify and remediate vulnerabilities during AI-assisted development. This product is now available for integration with existing coding platforms to manage security tasks in real-time.
Why it matters
As engineering teams increasingly rely on AI to generate code, traditional security review cycles have struggled to keep pace. Wingman addresses this bottleneck by automating vulnerability checks directly within the developer's workflow.
Users receive 50 automated security scans per month at a cost of $10 per user. Early deployments successfully addressed 7,500 vulnerabilities with a 98% success rate in preventing regressions.
The players
StackHawk
A developer-focused security company specializing in automated application security testing and pipeline integration.
Gartner
A global research and advisory firm that provides market insights on information technology and engineering trends.
The details
Wingman triggers a vulnerability scan once an AI coding agent completes a feature, providing immediate feedback to the agent. The tool reports these results directly into the continuous integration (CI) pipeline, which is an automated process used to test and merge code changes, linking findings to specific commits for easier tracking.
Timeline
StackHawk launched the Wingman tool on September 24, 2026.
Gartner predicts significant shifts in integrated development environment (IDE) usage by 2027.
The Tech Race
This release follows Gartner's forecast that by 2027, over 65% of engineering teams will treat traditional integrated development environments as optional. It positions security automation as a core component of the evolving agentic coding stack.
Developers can begin using the tool immediately via a 14-day free trial before moving to a $10 monthly subscription. It supports integration with existing tools like GitHub Copilot, Cursor, and Claude Code to standardize security protocols.
The takeaway
Wingman demonstrates the transition toward automated security agents that operate at the speed of generative AI coding. Teams should monitor whether the 98% non-regression rate holds as adoption scales across more complex, multi-language codebases.
Further reading
For more context on how automated defenses are shaping software production, explore Cybersecurity.
Live Poll
Do you trust security software to automatically identify and fix flaws in AI-generated code?
