RampEli BlockTutorial
We proactively fixed ~100 security issues in 6 days with 0 humans
Summary
Ramp Security Engineering describes a six-day experiment in which home-grown agents found, validated, and fixed nearly 100 latent backend security issues, including some high-severity findings, without human involvement until pull-request review. The issues had not been uncovered by penetration testing, bug bounty testing, static analysis, or trials of 10+ code-scanning vendors, and all were patched within a week of discovery. The pipeline used specialized vulnerability detectors, adversarial manager agents that rejected 40% of initial proposals in sample testing, integration tests for validation, and an internal coding agent that generated patches. Live interactive validation struggled with complex preconditions, so test-based validation became the main approach; a human team member still reviewed and landed each pull request.
Context
Tooling-based security programs require people to find, validate, fix, and confirm findings, creating labor-intensive handoffs and organizational bottlenecks. The post says this burden can cause teams to ignore lower-severity issues and erode trust when effort is spent on low-impact findings.
Approach / What changed
A coordinator launched specialized detector agents in parallel, then passed findings to adversarial manager agents for critique. A validator wrote integration tests that reproduced vulnerabilities and confirmed fixes, while an internal coding agent used those tests to generate patches and open pull requests for human review.
Takeaways
Specialized detectors with focused context windows produced higher-signal initial findings than generic prompts or multipurpose detectors.
In sample testing, adversarial managers rejected 40% of detector proposals, and human review confirmed all rejected proposals were false positives.
Agents struggled to configure complex live-environment preconditions, so integration-test validation replaced interactive testing for most findings.
Source and freshness
- Source
- builders.ramp.com
- Published
- Added to Yomu
- Last updated
Summaries are generated from the original by a language model. Check the original before relying on it.
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